iPhylo

Roderic D. M. Page

Saturday, November 12, 2016

EOL Traitbank JSON-LD is broken

Follow eol on twitter One of the most interesting aspects of EOL is "TraitBank", which has been described in a recent paper:

Cynthia S. Parr, Katja S. Schulz, Jennifer Hammock, Nathan Wilson, Patrick Leary, Jeremy Rice, & Robert J. Corrigan. (2016). TraitBank: Practical semantics for organism attribute data. Semantic Web, 7(6), 577–588. https://doi.org/10.3233/SW-150190

TraitBank is available in JSON-LD, and so is potentially part of the Semantic Web. Unfortunately, the JSON-LD provided by TraitBank is broken, to the point that it's hard to believe that anyone's actually consuming the JSON-LD. I know that Google is using EOL data for their knowledge panels, but anyone using TraitBank JSON-LD in a semantic web client is going to run into problems.

First off, let's look at the example provided in the above paper, http://eol.org/api/traits/328067 which returns data for Potos flavus.

{
  "@context": {
    "@vocab": "http://schema.org/",
    "dwc:taxonID": {
      "@type": "@id"
    },
    "dwc:resourceID": {
      "@type": "@id"
    },
    "dwc:relatedResourceID": {
      "@type": "@id"
    },
    "dwc:relationshipOfResource": {
      "@type": "@id"
    },
    "dwc:vernacularName": {
      "@container": "@language"
    },
    "eol:associationType": {
      "@type": "@id"
    },
    "rdfs:label": {
      "@container": "@language"
    },
    "dc": "http://purl.org/dc/terms/",
    "dwc": "http://rs.tdwg.org/dwc/terms/",
    "eolterms": "http://eol.org/schema/terms/",
    "eol": "http://eol.org/schema/",
    "rdfs": "http://www.w3.org/2000/01/rdf-schema#",
    "gbif": "http://rs.gbif.org/terms/1.0/",
    "foaf": "http://xmlns.com/foaf/0.1/"
  },
  "@type": "DataFeedItem",
  "dateModified": "2016-09-30",
  "item": {
    "@id": 328067,
    "@type": "dwc:Taxon",
    "scientificName": "Potos flavus (Schreber, 1774)",
    "dwc:taxonRank": "species",
    "dwc:parentNameUsageID": "http://eol.org/pages/14191",
    "potentialAction": {
      "@type": "EntryPoint",
      "target": {
        "@type": "Related",
        "url": "http://eol.org/pages/328067",
        "actionPlatform": [
          "http://schema.org/DesktopWebPlatform",
          "http://schema.org/IOSPlatform",
          "http://schema.org/AndroidPlatform"
        ]
      }
    },
    "sameAs": [
      "http://www.iucnredlist.org/details/41679",
      "http://genomics.senescence.info/species/entry.php?species=Potos_flavus",
      "http://commons.wikimedia.org/wiki/Potos_flavus",
      "http://www.biolib.cz/en/taxon/id1790/",
      "http://www.iucnredlist.org/apps/redlist/details/41679",
      "http://www.discoverlife.org/mp/20q?search=Potos+flavus",
      "http://www.eco-index.org/search/keyword_complete.cfm?keyword=Potos flavus",
      "http://calphotos.berkeley.edu/cgi/img_query?seq_num=31541&one=T",
      "http://www.conabio.gob.mx/conocimiento/ise/fichasnom/Potosflavus00.pdf",
      "http://darnis.inbio.ac.cr/ubis/FMPro?-DB=UBIPUB.fp3&-lay=WebAll&-error=norec.html&-Format=detail.html&-Op=eq&-Find=&id=1689",
      "http://lod.taxonconcept.org/ses/2mOvV.html",
      "http://neotropnathistory.lifedesks.org/pages/45271",
      "http://www.boldsystems.org/index.php/Taxbrowser_Taxonpage?taxid=73392",
      "http://www.catalogueoflife.org/annual-checklist/details/species/id/6902599",
      "http://www.catalogueoflife.org/annual-checklist/details/species/id/6902599",
      "http://genomics.senescence.info/species/entry.php?species=Potos_flavus",
      "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=621964",
      "http://en.wikipedia.org/w/index.php?title=Kinkajou",
      "http://www.iucnredlist.org/apps/redlist/details/41679",
      "http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&id=29067",
      "http://eol.org/pages/328067",
      "http://animaldiversity.ummz.umich.edu/accounts/Potos_flavus/"
    ],
    "vernacularNames": [
      {
        "@language": "af",
        "@value": "rolbeer",
        "gbif:isPreferredName": true
      },
      {
        "@language": "af",
        "@value": "rolstaartbeer"
      },
      {
        "@language": "de",
        "@value": "wickelbär",
        "gbif:isPreferredName": true
      },
      {
        "@language": "en",
        "@value": "Kinkajou",
        "gbif:isPreferredName": true
      },
      {
        "@language": "en",
        "@value": "honey bear"
      },
      {
        "@language": "es",
        "@value": "Ak' a' mash",
        "gbif:isPreferredName": true
      },
      {
        "@language": "es",
        "@value": "Chosna"
      },
      {
        "@language": "es",
        "@value": "Cusu"
      },
      {
        "@language": "es",
        "@value": "Martilla"
      },
      {
        "@language": "es",
        "@value": "Martucha"
      },
      {
        "@language": "es",
        "@value": "Mico de noche"
      },
      {
        "@language": "es",
        "@value": "Mico león"
      },
      {
        "@language": "es",
        "@value": "Mono michi"
      },
      {
        "@language": "es",
        "@value": "Perro de monte"
      },
      {
        "@language": "fi",
        "@value": "Kinkaju",
        "gbif:isPreferredName": true
      },
      {
        "@language": "fr",
        "@value": "Kinkajou, Singe de nuit",
        "gbif:isPreferredName": true
      },
      {
        "@language": "nl",
        "@value": "rolstaartbeer",
        "gbif:isPreferredName": true
      },
      {
        "@language": "nl",
        "@value": "nachtaap"
      },
      {
        "@language": "pt-BR",
        "@value": "Jupará",
        "gbif:isPreferredName": true
      }
    ],
    "traits": [
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949469",
        "eol:traitUri": "http://eol.org/resources/704/measurements/basalmetrate113",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "metabolic rate",
        "dwc:measurementType": "http://www.owl-ontologies.com/unnamed.owl#Metabolic_rate",
        "value": "731.33",
        "units": "mL/hr O2",
        "eol:dataPointId": 949469,
        "http://purl.obolibrary.org/obo/VT_0001259": "http://eol.org/resources/704/measurements/metratemass113",
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Basal metabolic rate was measured when individual(s) were experiencing neither heat nor cold stress (i.e. are in their thermoneutral zone); are resting and calm; and are post–absorptive (are not digesting or absorbing a meal) and data were only accepted where there was also a measure of body mass for the same individual(s). Based on information from primary and secondary literature sources. This value represents a single measure of central tendency for this species. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "731.33",
        "dwc:measurementUnit": "http://eol.org/schema/terms/mlO2perhour",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_46140963",
        "eol:traitUri": "http://eol.org/resources/737/measurements/e5775a49cc4bbe3f3ae5c391776a467a",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "population trend",
        "dwc:measurementType": "http://iucn.org/population_trend",
        "value": "Decreasing",
        "eol:dataPointId": 46140963,
        "dc:source": "http://eol.org/resources/737",
        "dwc:measurementValue": "Decreasing",
        "dwc:scientificName": "Potos flavus (Schreber, 1774)",
        "eolterms:resource": "http://eol.org/resources/737"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_46140962",
        "eol:traitUri": "http://eol.org/resources/737/measurements/25c8b74374d04260b047bd57570e094b",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "habitat",
        "dwc:measurementType": "http://rs.tdwg.org/dwc/terms/habitat",
        "value": "terrestrial habitat",
        "eol:dataPointId": 46140962,
        "dc:source": "http://eol.org/resources/737",
        "dwc:measurementValue": "http://purl.obolibrary.org/obo/ENVO_00002009",
        "dwc:scientificName": "Potos flavus (Schreber, 1774)",
        "eolterms:resource": "http://eol.org/resources/737"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949459",
        "eol:traitUri": "http://eol.org/resources/704/measurements/maxlongevity138",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "total life span",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001661",
        "value": "348",
        "units": "months",
        "eol:dataPointId": 949459,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Maximum adult age measured either through direct observation, capture-recapture estimates, projected from physical wear or unspecified, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001114",
        "dwc:measurementValue": "348",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000035",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949460",
        "eol:traitUri": "http://eol.org/resources/704/measurements/littersperyear728",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "litters per year",
        "dwc:measurementType": "http://eol.org/schema/terms/LittersPerYear",
        "value": "1",
        "eol:dataPointId": 949460,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Number of litters per female per year using non-captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "1",
        "dwc:scientificName": "Potos flavus",
        "dwc:sex": "http://purl.obolibrary.org/obo/PATO_0000383"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949461",
        "eol:traitUri": "http://eol.org/resources/704/measurements/littersize1554",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "clutch/brood/litter size",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001933",
        "value": "1.11",
        "eol:dataPointId": 949461,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Number of offspring born per litter per female, either counted before birth, at birth or after birth, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "1.11",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949462",
        "eol:traitUri": "http://eol.org/resources/704/measurements/interbirthinterval291",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "inter-birth interval",
        "dwc:measurementType": "http://eol.org/schema/terms/InterBirthInterval",
        "value": "365",
        "units": "days",
        "eol:dataPointId": 949462,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "The length of time between successive births of the same female(s) after a successful or unspecified litter using non-captive, wild, provisioned, or unspecified populations; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "365",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus",
        "dwc:sex": "http://purl.obolibrary.org/obo/PATO_0000383"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949463",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grmaxlat1392",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "latitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000319",
        "value": "23.72",
        "units": "decimal degrees",
        "eol:dataPointId": 949463,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001114",
        "dwc:measurementValue": "23.72",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949464",
        "eol:traitUri": "http://eol.org/resources/704/measurements/midrangelong3692",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "longitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000318",
        "value": "-68.67",
        "units": "decimal degrees",
        "eol:dataPointId": 949464,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001110",
        "dwc:measurementValue": "-68.67",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949465",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grminlong4209",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "longitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000318",
        "value": "-102.55",
        "units": "decimal degrees",
        "eol:dataPointId": 949465,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001113",
        "dwc:measurementValue": "-102.55",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_45346815",
        "eol:traitUri": "http://eol.org/resources/976/measurements/m_00269876",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "geographic distribution includes",
        "dwc:measurementType": "http://eol.org/schema/terms/Present",
        "value": "Southern Mesoamerican Pacific mangroves",
        "eol:dataPointId": 45346815,
        "dc:source": "http://www.worldwildlife.org/publications/wildfinder-database",
        "dc:bibliographicCitation": "World Wildlife Fund. 2006. WildFinder: Online database of species distributions, ver. Jan-06. www.worldwildlife.org/WildFinder",
        "dwc:measurementValue": "http://eol.org/schema/terms/Southern_Mesoamerican_Pacific_mangroves",
        "dwc:scientificName": "Potos flavus",
        "dc:contributor": "Compiler: Sarah Miller",
        "dwc:measurementRemarks": "Biome: Mangroves
Realm: Neotropical",
        "eolterms:resource": "http://eol.org/resources/976"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_45346814",
        "eol:traitUri": "http://eol.org/resources/976/measurements/m_00269875",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "geographic distribution includes",
        "dwc:measurementType": "http://eol.org/schema/terms/Present",
        "value": "Southern Atlantic mangroves",
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        "eol:dataPointId": 949467,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Dispersal Age: Age at which young permanently leave the parent, parental group, social group or any associated territories, using non-captive, wild, non-provisioned or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Based on information from primary and secondary literature sources. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "160",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949468",
        "eol:traitUri": "http://eol.org/resources/704/measurements/dietbreadth467",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "diet breadth",
        "dwc:measurementType": "http://eol.org/schema/terms/DietBreadth",
        "value": "4",
        "eol:dataPointId": 949468,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Number of dietary categories eaten by each species measured using any qualitative or quantitative dietary measure, over any period of time, using any assessment method, for non-captive or non-provisioned populations; adult or age unspecified individuals, male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Categories were defined as vertebrate, invertebrate, fruit, flowers/nectar/pollen, leaves/branches/bark, seeds, grass and roots/tubers.  Based on information from primary and secondary literature sources. See source for details.",
        "dwc:measurementValue": "4",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949470",
        "eol:traitUri": "http://eol.org/resources/704/measurements/ageateyeopening149",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "age at eye opening",
        "dwc:measurementType": "http://eol.org/schema/terms/AgeAtEyeOpening",
        "value": "16.95",
        "units": "days",
        "eol:dataPointId": 949470,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Age at which both eyes are fully open after birth using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Based on information from primary and secondary literature sources. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "16.95",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949471",
        "eol:traitUri": "http://eol.org/resources/704/measurements/homerangeindiv237",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "home range",
        "dwc:measurementType": "http://www.owl-ontologies.com/unnamed.owl#Home_range",
        "value": "0.21",
        "units": "km^2",
        "eol:dataPointId": 949471,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Size of the area within which everyday activities of individuals are typically restricted, estimated by either direct observation, radio telemetry, trapping or unspecified methods over any duration of time, using non-captive populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "0.21",
        "dwc:measurementUnit": "http://eol.org/schema/terms/squarekilometer",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949472",
        "eol:traitUri": "http://eol.org/resources/704/measurements/homerange266",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "home range",
        "dwc:measurementType": "http://www.owl-ontologies.com/unnamed.owl#Home_range",
        "value": "0.22",
        "units": "km^2",
        "eol:dataPointId": 949472,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Size of the area within which everyday activities of individuals or groups (of any type) are typically restricted, estimated by either direct observation, radio telemetry, trapping or unspecified methods over any duration of time, using non-captive populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "0.22",
        "dwc:measurementUnit": "http://eol.org/schema/terms/squarekilometer",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949473",
        "eol:traitUri": "http://eol.org/resources/704/measurements/habitatbreadth530",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "habitat breadth",
        "dwc:measurementType": "http://eol.org/schema/terms/HabitatBreadth",
        "value": "2",
        "eol:dataPointId": 949473,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Number of habitat layers used by each species measured using any qualitative or quantitative time measure, for non-captive populations; adult or age unspecified individuals, male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Categories were defined as above ground dwelling, aquatic, fossorial and ground dwelling. Based on information from primary and secondary literature sources.  See source for details.",
        "dwc:measurementValue": "2",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949474",
        "eol:traitUri": "http://eol.org/resources/704/measurements/gestationlen520",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "gestation period duration",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0002292",
        "value": "116.8",
        "units": "days",
        "eol:dataPointId": 949474,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Gestation Length: Length of time of non-inactive fetal growth, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Gestation was measured between specified start and end points as follows: Start points – conception, fertilization, first observed copulation, fertilization, implantation, laying, palpably pregnant, removal of pouch young, capture (except marsupials) or unspecified. End points – birth, hatching or unspecified.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "116.8",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949475",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grarea125",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "geographic range (size of area)",
        "dwc:measurementType": "http://eol.org/schema/terms/GeographicRangeArea",
        "value": "12770952.51",
        "units": "km^2",
        "eol:dataPointId": 949475,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Geographic Range (Area): Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Area was calculated using the total extent of a species range with a global equal-area projection (Mollweide).",
        "dwc:measurementValue": "12770952.51",
        "dwc:measurementUnit": "http://eol.org/schema/terms/squarekilometer",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949476",
        "eol:traitUri": "http://eol.org/resources/704/measurements/weaningage363",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "weaning age",
        "dwc:measurementType": "http://eol.org/schema/terms/WeaningAge",
        "value": "109.13",
        "units": "days",
        "eol:dataPointId": 949476,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Weaning Age: Age when primary nutritional dependency on the mother ends and independent foraging begins to make a major contribution to the offspring’s energy requirements, measured as either weaning/lactation length, nutritionally independent, first solid food, last observed nursing, age at first flight (bats only), age at pouch exit or length of teat Attachment (marsupials only) or unspecified definition, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "109.13",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949477",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grmidrangelat2607",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "latitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000319",
        "value": "0.3",
        "units": "decimal degrees",
        "eol:dataPointId": 949477,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001110",
        "dwc:measurementValue": "0.3",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949478",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grminlat3805",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "latitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000319",
        "value": "-23.1",
        "units": "decimal degrees",
        "eol:dataPointId": 949478,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001113",
        "dwc:measurementValue": "-23.1",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949479",
        "eol:traitUri": "http://eol.org/resources/704/measurements/grmaxlong3243",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "longitude",
        "dwc:measurementType": "http://semanticscience.org/resource/SIO_000318",
        "value": "-34.79",
        "units": "decimal degrees",
        "eol:dataPointId": 949479,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Digital geographic range maps of all extant, non-marine mammals from Sechrest (2003) were converted to the Wilson and Reeder (2005) taxonomy. These ranges were used to generate measures of geographic range extent and occupancy. Spatial analyses were performed using ArcGIS (version 9.0) (ESRI 2005) for areas and R (R Development Core Team 2005) for geographic coordinates.  Value calculated using a global geographic projection.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001114",
        "dwc:measurementValue": "-34.79",
        "dwc:measurementUnit": "http://eol.org/schema/terms/decimaldegrees",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949480",
        "eol:traitUri": "http://eol.org/resources/704/measurements/hupopdenmean2854",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "human population density",
        "dwc:measurementType": "http://eol.org/schema/terms/HumanPopulationDensity",
        "value": "25.77",
        "units": "individuals per square kilometer",
        "eol:dataPointId": 949480,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Variables describing the anthropogenic and environmental conditions within the geographic range of a species were generated based on the extent of digital species range maps from Sechrest (2003) converted to the Wilson and Reeder (2005) taxonomy. The species ranges were first gridded at 0.5 degrees using a global geographic projection and species were scored as present in each cell if any of the range intersected that cell. Summary statistics for a species were then calculated by summarizing the value for each anthropogenic and environmental variable (gridded to the same extent) for all the cells the species was present.  The summary statistics for each variable was adjusted for the fact that area varies with latitude by multiplying each cell by the area and then dividing by the total area of cells for that variable for a species. Mean Human Population Density calculated using the Gridded Population of the World (GPW) (CIESIN and CIAT 2005) for 1995.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001109",
        "dwc:measurementValue": "25.77",
        "dwc:measurementUnit": "http://eol.org/schema/terms/individualspersquarekilometer",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949481",
        "eol:traitUri": "http://eol.org/resources/704/measurements/aetmean1232",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "actual evapotranspiration rate in geographic range",
        "dwc:measurementType": "http://eol.org/schema/terms/AETinRange",
        "value": "1306.64",
        "units": "millimeters per month",
        "eol:dataPointId": 949481,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Variables describing the environmental conditions within the geographic range of a species were generated based on the extent of digital species range maps from Sechrest (2003) converted to the Wilson and Reeder (2005) taxonomy. The species ranges were first gridded at 0.5 degrees using a global geographic projection and species were scored as present in each cell if any of the range intersected that cell. Summary statistics for a species were then calculated by summarizing the value for each environmental variable (gridded to the same extent) for all the cells the species was present.  The summary statistics for each variable was adjusted for the fact that area varies with latitude by multiplying each cell by the area and then dividing by the total area of cells for that variable for a species.  Mean Monthly AET from 1920 to 1980 (mm) was calculated using the Global Resource Information Database of UNEP and is available from http://www.grid.unep.ch/data/grid/gnv183.php.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001109",
        "dwc:measurementValue": "1306.64",
        "dwc:measurementUnit": "http://eol.org/schema/terms/millimeterspermonth",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949482",
        "eol:traitUri": "http://eol.org/resources/704/measurements/adultbodymass768",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "body mass",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001259",
        "value": "2441.81",
        "units": "g",
        "eol:dataPointId": 949482,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Mass of adult (or age unspecified) live or freshly-killed specimens (excluding pregnant females) using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Based on information from primary and secondary literature sources. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "2441.81",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000021",
        "dwc:scientificName": "Potos flavus",
        "dwc:lifeStage": "http://www.ebi.ac.uk/efo/EFO_0001272"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949491",
        "eol:traitUri": "http://eol.org/resources/704/measurements/activitycycle556",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "behavioral circadian rhythm",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001502",
        "value": "nocturnal",
        "eol:dataPointId": 949491,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Activity cycle of each species measured for non-captive populations; adult or age unspecified individuals, male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Species were defined as (1) nocturnal only, (2) nocturnal/crepuscular, cathemeral, crepuscular or diurnal/crepuscular and (3) diurnal only.  Based on information from primary and secondary literature sources.  See source for details.",
        "dwc:measurementValue": "http://www.owl-ontologies.com/unnamed.owl#Nocturnal",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949483",
        "eol:traitUri": "http://eol.org/resources/704/measurements/socialgrpsize618",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "social group size",
        "dwc:measurementType": "http://eol.org/schema/terms/SocialGroupSize",
        "value": "1",
        "eol:dataPointId": 949483,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Social Group Size: Number of individuals, adults or definition unspecified in a group that spends the majority of their time in a 24 hour cycle together where there is some indication that these individuals form a social cohesive unit, measured over any duration of time, using non-captive populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "1",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949484",
        "eol:traitUri": "http://eol.org/resources/704/measurements/sexualmaturityage215",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "onset of fertility",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0002683",
        "value": "858.41",
        "units": "days",
        "eol:dataPointId": 949484,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Sexual Maturity Age: Age when individuals are first physically capable of reproducing, defined as either physically sexually mature, age at first mating or unspecified (males and females), age at first estrus or age at first pregnancy (females only), age at spermatogenesis or age at testes descent (males only), using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals, primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "858.41",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000033",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949485",
        "eol:traitUri": "http://eol.org/resources/704/measurements/populationdensity532",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "animal population density",
        "dwc:measurementType": "http://purl.bioontology.org/ontology/CSP/2383-1863",
        "value": "34.21",
        "units": "individuals per square kilometer",
        "eol:dataPointId": 949485,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Population Density: Number of individuals per square kilometer, estimated with either direct, indirect or unspecified counts, measured in any area size within a human, ecological or unspecified boundary, over any duration of time, using non-captive, non-provisioned populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "34.21",
        "dwc:measurementUnit": "http://eol.org/schema/terms/individualspersquarekilometer",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949486",
        "eol:traitUri": "http://eol.org/resources/704/measurements/neonateheadbodylen38",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "body length (VT)",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001256",
        "value": "183.03",
        "units": "mm",
        "eol:dataPointId": 949486,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Neonate Head Body Length: Total length from tip of nose to anus or base of tail of live, freshly-killed, or museum specimens of infants at either a near term embryonic stage, birth, immediately after birth or up to an age of seven days after birth, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "183.03",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000016",
        "dwc:scientificName": "Potos flavus",
        "dwc:lifeStage": "http://purl.bioontology.org/ontology/CSP/0070-1441"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949487",
        "eol:traitUri": "http://eol.org/resources/704/measurements/neonatalbodymass321",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "body mass",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/VT_0001259",
        "value": "171.84",
        "units": "g",
        "eol:dataPointId": 949487,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Neonatal Body Mass: Mass of live or freshly-killed specimens of infants at either a near term embryonic stage, birth, immediately after birth or up to an age of seven days after birth, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "171.84",
        "dwc:measurementUnit": "http://purl.obolibrary.org/obo/UO_0000021",
        "dwc:scientificName": "Potos flavus",
        "dwc:lifeStage": "http://purl.bioontology.org/ontology/CSP/0070-1441"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949492",
        "eol:traitUri": "http://eol.org/resources/704/measurements/trophiclevel1154",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "trophic level",
        "dwc:measurementType": "http://eol.org/schema/terms/TrophicLevel",
        "value": "omnivore",
        "eol:dataPointId": 949492,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Trophic level of each species measured using any qualitative or quantitative dietary measure, over any period of time, using any assessment method, for non-captive or non-provisioned populations; adult or age unspecified individuals, male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. See source for details.  Species were defined as (1) http://www.owl-ontologies.com/unnamed.owl#Primary__Herbivore, (2) http://www.owl-ontologies.com/unnamed.owl#Omnivore and (3) http://www.owl-ontologies.com/unnamed.owl#Primary__Carnivore",
        "dwc:measurementValue": "http://www.owl-ontologies.com/unnamed.owl#Omnivore",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949493",
        "eol:traitUri": "http://eol.org/resources/704/measurements/terrestriality1036",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "terrestriality",
        "dwc:measurementType": "http://eol.org/schema/terms/Terrestriality",
        "value": "above ground dwelling",
        "eol:dataPointId": 949493,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Degree of terrestriality of each species measured using any qualitative or quantitative time measure, for non-captive populations; adult or age unspecified individuals, male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities. Species were defined as (1) fossorial and/or ground dwelling only and (2) above ground dwelling.  See source for details.",
        "dwc:measurementValue": "http://eol.org/schema/terms/aboveGroundDwelling",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949494",
        "eol:traitUri": "http://eol.org/resources/704/measurements/teatnumber630",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "teat number",
        "dwc:measurementType": "http://purl.obolibrary.org/obo/CMO_0000445",
        "value": "2",
        "eol:dataPointId": 949494,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Total number of teats present, using captive, wild, provisioned, or unspecified populations; male, female, or sex unspecified individuals; primary, secondary, or extrapolated sources; all measures of central tendency; in all localities.  See source for details.",
        "eolterms:statisticalMethod": "http://eol.org/schema/terms/average",
        "dwc:measurementValue": "2",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949495",
        "eol:traitUri": "http://eol.org/resources/704/measurements/hupopdenchange1541",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "human population density change",
        "dwc:measurementType": "http://eol.org/schema/terms/HumanPopulationDensityChange",
        "value": "0.12",
        "eol:dataPointId": 949495,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Variables describing the anthropogenic and environmental conditions within the geographic range of a species were generated based on the extent of digital species range maps from Sechrest (2003) converted to the Wilson and Reeder (2005) taxonomy. The species ranges were first gridded at 0.5 degrees using a global geographic projection and species were scored as present in each cell if any of the range intersected that cell. Summary statistics for a species were then calculated by summarizing the value for each anthropogenic and environmental variable (gridded to the same extent) for all the cells the species was present.  The summary statistics for each variable was adjusted for the fact that area varies with latitude by multiplying each cell by the area and then dividing by the total area of cells for that variable for a species.  Human Population Density Change calculated using the Gridded Population of the World (GPW) (CIESIN and CIAT 2005) for 1990 and 1995 as: (1995–1990)/1990.",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001109",
        "dwc:measurementValue": "0.12",
        "dwc:scientificName": "Potos flavus"
      },
      {
        "@id": "http://eol.org/pages/328067/data#data_point_949488",
        "eol:traitUri": "http://eol.org/resources/704/measurements/precipmean1381",
        "@type": "dwc:MeasurementOrFact",
        "predicate": "precipitation in geographic range",
        "dwc:measurementType": "http://eol.org/schema/terms/PrecipitationInRange",
        "value": "153.67",
        "units": "millimeters per month",
        "eol:dataPointId": 949488,
        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
        "dwc:measurementMethod": "Variables describing the environmental conditions within the geographic range of a species were generated based on the extent of digital species range maps from Sechrest (2003) converted to the Wilson and Reeder (2005) taxonomy. The species ranges were first gridded at 0.5 degrees using a global geographic projection and species were scored as present in each cell if any of the range intersected that cell. Summary statistics for a species were then calculated by summarizing the value for each environmental variable (gridded to the same extent) for all the cells the species was present.  The summary statistics for each variable was adjusted for the fact that area varies with latitude by multiplying each cell by the area and then dividing by the total area of cells for that variable for a species.  Mean Monthly Precipitation was calculated using data from ftp://ftp.ngdc.noaa.gov/Solid_Earth/Ecosystems/GEDII_a/datasets/a03/lc.htm",
        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001109",
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      },
      {
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        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
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        "eolterms:statisticalMethod": "http://semanticscience.org/resource/SIO_001109",
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      {
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        "dc:source": "Data set supplied by Kate E. Jones.  The data can also be accessed at Ecological Archives E090-184-D1, http://esapubs.org/archive/ecol/E090/184/, http://esapubs.org/archive/ecol/E090/184/PanTHERIA_1-0_WR05_Aug2008.txt",
        "dc:bibliographicCitation": "Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O'Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.",
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        "dwc:measurementRemarks": "Confidence in the longevity data (data quality) is classified as: 'low' (only used for species without an established maximum longevity in AnAge), 'questionable', 'acceptable' and 'high'. This qualifier is based on the reliability of the original reference from which maximum longevity was obtained, sample size, whether a given species has been studied and reproduces in captivity, and whether there are any conflicting reports.",
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        "eol:dataPointId": 3088888,
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      }
    ]
  }
}

If I paste this into the JSON-LD playground and try and convert it to N-Quads I get a flurry of errors. Here are some of the problems (see also EOL JSON-LD not valid #352:

The @id for the EOL taxon is a number instead of a URI

The field "@id": 328067 should be "@id": "http://eol.org/pages/328067". Identifiers on the Semantic Web are URIs not numbers.

Vernacular names can't have additional fields

EOL sometimes indicates the preferred vernacular name like this:

      {
        "@language": "es",
        "@value": "Ak' a' mash",
        "gbif:isPreferredName": true
      },

This is not valid syntax and breaks RDF parsers.

URIs as strings

In several places EOL outputs URIs as simple strings rather than as URIs. For example, to indicate that the parent taxon of Potos flavus is the genus Potos the JSON-LD has:

"dwc:parentNameUsageID": "http://eol.org/pages/14191",

But this is simply saying that the string value for "dwc:parentNameUsageID" is "http://eol.org/pages/14191". In JSON-LD this should be:

"dwc:parentNameUsageID":{"@id":"http:\/\/eol.org\/pages\/14191"}

This syntax ensures that http://eol.org/pages/14191 is interpreted as a URI, which also means clients "know" that they can resolve that URI to get more information.

Predicates with missing (hence wrong) namespace

A number of predicates in the JSON-LD don't have a namespace specified, hence they default to being part of the schema.org vocabulary. For example, this statement:

"scientificName": "Potos flavus (Schreber, 1774)",

results in "scientificName" being interpreted as "http://schema.org/scientificName" (because "http://schema.org/" is set as the default @vocab). This is incorrect, "scientificName" should be "dwc:scientificName".

Then there are predicates such as "predicate" and "value" in the data sections that missing the correct namespace (in this case http://www.w3.org/1999/02/22-rdf-syntax-ns#). For example,

{
  "@id": "http://eol.org/pages/328067/data#data_point_46140963",
  "eol:traitUri": "http://eol.org/resources/737/measurements/e5775a49cc4bbe3f3ae5c391776a467a",
  "@type": "dwc:MeasurementOrFact",
  "predicate": "population trend",
  "dwc:measurementType": "http://iucn.org/population_trend",
  "value": "Decreasing",
  "eol:dataPointId": 46140963,
  "dc:source": "http://eol.org/resources/737",
  "dwc:measurementValue": "Decreasing",
  "dwc:scientificName": "Potos flavus (Schreber, 1774)",
  "eolterms:resource": "http://eol.org/resources/737"
}

(This example also has URIs as dumb strings, not as URIs).

Anyone constructing, say, SPARQL queries on this data is going to be using terms such as predicate that don't exist.

Some data records have the predicate "units" - I haven't yet figured out what, if any, vocabulary that predicate comes from.

Summary

I think TraitBank has a lot of potential, and welcome the use of JSON-LD and the schema.org vocabulary. These are both steps forward in the goal of interoperable biodiversity data. But this data will only become interoperable if we take care to ensure that the data we output is what we say it is. EOL TraitBank JSON-LD isn't valid JSON-LD. This also illustrates a bigger problem, we are continually building systems that don't have users. If anyone was using TraitBank JSON-LD with standard Semantic Web clients, they would be up in arms about this. The best way to avoid these situations is for the developers to be users as well (see GBIF, biodiversity informatics and the "platform rant"). Until we "dog food" our own services we will continue to produce data and services that are less than useful. If EOL was itself built on TraitBank, I doubt we'd have these problems.

Friday, September 30, 2016

Guest post: It's 2016 and your data aren't UTF-8 encoded?

The following is a guest post by Bob Mesibov.

According to w3techs, seven out of every eight websites in the Alexa top 10 million are UTF-8 encoded. This is good news for us screenscrapers, because it means that when we scrape data into a UTF-8 encoded document, the chances are good that all the characters will be correctly encoded and displayed.

It's not quite good news for two reasons.

In the first place, one out of eight websites is encoded with some feeble default like ISO-8859-1, which supports even fewer characters than the closely related windows-1252. Those sites will lose some widely-used punctuation when read as UTF-8, unless the webpage has been carefully composed with the HTML equivalents of those characters. You're usually safe (but see below) with big online sources like Atlas of Living Australia (ALA), APNI, CoL, EoL, GBIF, IPNI, IRMNG, NCBI Taxonomy, The Plant List and WoRMS, because these declare a UTF-8 charset in a meta tag in webpage heads. (IPNI's home page is actually in ISO-8859-1, but its search results are served as UTF-8 encoded XML.)

But a second problem is that just because a webpage declares itself to be UTF-8, that doesn't mean every character on the page sings from the Unicode songbook. Very odd characters may have been pulled from a database and written onto the page as-is. In ALA I recently found an ancient rune — the High Octet Preset control character (HOP, hex 81):

http://biocache.ala.org.au/occurrences/6191ca90-873b-44f8-848d-befc29ad7513 http://biocache.ala.org.au/occurrences/5077df1f-b70a-465b-b22b-c8587a9fb626

HOP replaces ü on these pages and is invisible in your browser, but a screenscrape will capture the HOP and put SchHOPrhoff in your UTF-8 document.

Another example of ALA's fidelity to its sources is its coding of the degree symbol, which is a single-byte character (hex b0) in windows-1252, e.g. in Excel spreadsheets, but a two-byte character (hex c2 b0) in Unicode. In this record, for example:

http://biocache.ala.org.au/occurrences/5e3a2e05-1e80-4e1c-9394-ed6b37441b20

the lat/lon was supplied (says ALA) as 37Â°56'9.10"S 145Â° 0'43.74"E. Or was it? The lat/lon could have started out as 37°56'9.10"S 145°0'43.74"E in UTF-8. Somewhere along the line the lat/lon was converted to windows-1252 and the Â° characters were generated, resulting in geospatial gibberish.

When a program fails to understand a character's encoding, it usually replaces the mystery character with a ?. A question mark is a perfectly valid character in commonly used encodings, which means the interpretation failure gets propagated through all future re-uses of the text, both on the Web and in data dumps. For example,

http://biocache.ala.org.au/occurrences/dfbbc42d-a422-47a2-9c1d-3d8e137687e4

gives N?crophores for Nécrophores. The history of that particular character failure has been lost downstream, as is the case for myriads of other question marks in online biodiversity data.

In my experience, the situation is much worse in data dumps from online sources. It's a challenge to find a dump without question marks acting as replacement characters. Many of these question marks appear in author and place names. Taxonomists with eastern European names seem to fare particularly badly, sometimes with more than one character variant appearing in the same record, as in the Australian Faunal Directory (AFD) offering of Wêgrzynowicz, W?grzynowicz and Węgrzynowicz for the same coleopterist. Question marks also frequently replace punctuation, such as n-dashes, smart quotes and apostrophes (e.g. O?Brien (CoL) and L?Échange and d?Urville (AFD)).

Character encoding issues create major headaches for data users. It would be a great service to biodiversity informatics if data managers compiled their data in UTF-8 encoding or took the time to convert to UTF-8 and fix any resulting errors before publishing to the Web or uploading to aggregators.

This may be a big ask, given that at least one data manager I've talked to had no idea how characters were encoded in the institution's database. But as ALA's Miles Nicholls wrote back in 2009, "Note that data should always be shared using UTF-8 as the character encoding". Biodiversity informatics is a global discipline and UTF-8 is the global standard for encoding.

Readers needing some background on character encoding will find this and especially this helpful, and a very useful tool to check for encoding problems in small blocks of text is here.

GBIF 2016 Ebbe Nielsen Challenge entries

The GBIF 2016 Ebbe Nielsen Challenge has received 15 submissions. You can view them here: Screenshot 2016 09 30 14 01 05 Unlike last year where the topic was completely open, for the second challenge we've narrowed the focus to "Analysing and addressing gaps and biases in primary biodiversity data". As with last year, judging is limited to the jury (of which I'm a member), however anyone interested in biodiversity informatics can browse the submissions. Although you can't leave comments directly on the submissions within the GBIF Challenge pages, each submission also appears on the portfolio page of the person/organisation that created the entry, so you can leave comments there (follow the link at the bottom of the page for each submission to see it on the portfolio page).

Wednesday, September 07, 2016

Guest post: Absorbing task or deranged quest: an attempt to track all genus names ever published

YtNkVT2U This guest post by Tony Rees describes his quest to track all genus names ever published (plus a subset of the species…).

A “holy grail” for biodiversity informatics is a suitably quality controlled, human- and machine-queryable list of all the world’s species, preferably arranged in a suitable taxonomic hierarchy such as kingdom-phylum-class-order-family-genus or other. To make it truly comprehensive we need fossils as well as extant taxa (dinosaurs as well as dinoflagellates) and to cover all groups from viruses to vertebrates (possibly prions as well, which are, well, virus-like). Linnaeus had some pretty good attempts in his day, and in the internet age the challenge has been taken up by a succession of projects such as the “NODC Taxonomic Code” (a precursor to ITIS, the Integrated Taxonomic Information System - currently 722,000 scientific names), the Species 2000 consortium, and the combined ITIS+SP2000 product “Catalogue of Life”, now in its 16th annual edition, with current holdings of 1,635,250 living and 5,719 extinct valid (“accepted”) species, plus an additional 1,460,644 synonyms (information from http://www.catalogueoflife.org/annual-checklist/2016/info/ac). This looks pretty good until one realises that as well as the estimated “target” of 1.9 million valid extant species there are probably a further 200,000-300,000 described fossils, all with maybe as many synonyms again, making a grand total of at least 5 million published species names to acquire into a central “quality assured” system, a task which will take some time yet.

Ten years ago, in 2006, the author participated in a regular meeting of the steering committee for OBIS, the Ocean Biogeographic Information System which, like GBIF, aggregates species distribution data (for marine species in this context) from multiple providers into a single central search point. OBIS was using the Catalogue of Life (CoL) as its “taxonomic backbone” (method for organising its data holdings) and, again like GBIF, had come up against the problem of what to do with names not recognised in the then-latest edition of CoL, which was at the time less than 50% complete (information on 884,552 species). A solution occurred to me that since genus names are maybe only 10% as numerous as species names, and every species name includes its containing genus as the first portion of its binomial name (thanks, Linnaeus!), an all-genera index might be a tractable task (within a reasonable time frame) where an all-species index was not, and still be useful for allocating incoming “not previously seen” species names to an appropriate position in the taxonomic hierarchy. OBIS, in particular, also wished to know if species (or more exactly, their parent genera) were marine (to be displayed) or nonmarine (hide), similar with extant versus fossil taxa. Sensing a challenge, I offered to produce such a list, in my mind estimating that it might require 3 months full-time, or the equivalent 6 months in part time effort to complete and supply back to OBIS for their use.

To cut a long story short… the project, which I christened the Interim Register of Marine and Nonmarine Genera or IRMNG (originally at CSIRO in Australia, now hosted on its own domain “www.irmng.org” and located at VLIZ in Belgium) has successfully acquired over 480,000 published genus names, including valid names, synonyms and a subset of published misspellings, all allocated to families (most) or higher ranks (remainder) in an internally coherent taxonomic structure, most with marine/nonmarine and extant/fossil flags, all with the source from which I acquired them, sources for the flags, and more; also for perhaps 50% of genera, lists of associated species from wherever it has been convenient to acquire them (Catalogue of Life 2006 being a major source, but many others also used). My estimated 6 months has turned into 10 years and counting, but I do figure that the bulk of the basic “names acquisition” has been done for all groups (my estimate: over 95% complete) and it is rare (although not completely unknown) for me to come across genus names not yet held, at least for the period 1753-2014 which is the present coverage of IRMNG; present effort is therefore concentrated on correcting internal errors and inconsistencies, and upgrading the taxonomic placement (to family) for the around 100,000 names where this is not yet held (also establishing the valid name/synonym status of a similar number of presently “unresolved” generic names).

With the move of the system from Australia to VLIZ, completed within the last couple of months, there is the facility to utilise all of the software and features presently developed at VLIZ that currently runs WoRMS, the World Register of Marine Species and its many associated subsidiary databases, as well as (potentially) look at forming a distributed editing network for IRMNG in the future, as already is the case for WoRMS, presuming that others are see a value in maintaining IRMNG as a useful resource e.g. for taxonomic name resolution, detection of potential homonyms both within and across kingdoms, and generally acting as a hierarchical view of “all life” to at least genus level. A recently implemented addition to IRMNG is to hold ION identifiers (also used in BioNames), for the subset of names where ION holds the original publication details, enabling “deep links” to both ION and BioNames wherein the original publication can often be displayed, as previously described elsewhere in this Blog. Similar identifiers for plants are not yet held in the system but could be, (for example Index Fungorum identifiers for fungi), for cases where the potential linked system adds value in giving, for example, original publication details and onward links to the primary literature.

All in all I feel that the exercise has been of value not only to OBIS (the original “client”) but also to other informatics systems such as GBIF, Encyclopedia of Life, Atlas of Living Australia, Open Tree of Life and others who have all taken advantage of IRMNG data to add to their systems, either for the marine/nonmarine and extant/fossil flags or as an addition to their primary taxonomic backbones, or both. In addition it has allowed myself, the founding IRMNG compiler, to “scratch the taxonomic itch” and finally flesh out what is meant by statements that a certain group contains x families or y genera, and what these actually might be. Finally, many users of the system via its web interface have commented over time on how useful it is to be able to input “any” name, known or unknown, with a good chance that IRMNG can tell them something about the genus (or genus possible options, in the case of homonyms) as well as the species, in many cases, as well as discriminate extant from fossil taxon names, something not yet offered to any significant extent by the current Catalogue of Life.

Readers of iPhylo are encouraged to try IRMNG as a “taxonomic name resolution service” by visiting www.irmng.org and of course, welcome to contact me with suggestions of missed names (concentrating at genus level at the present time) or any other ideas for improvement (which I can then submit for consideration to the team at VLIZ who now provide the technical support for the system).

Tuesday, August 30, 2016

GRBio: A Call for Community Curation - what community?

Singlefig 98253 jpg David Schindel and colleagues recently published a paper in the Biodiversity Data Journal:

Schindel, D., Miller, S., Trizna, M., Graham, E., & Crane, A. (2016, August 26). The Global Registry of Biodiversity Repositories: A Call for Community Curation. BDJ. Pensoft Publishers. http://doi.org/10.3897/bdj.4.e10293

The paper is a call for the community to help grow a database (GRBio) on biodiversity repositories, a database that will "will require community input and curation".

Reading this, I'm struck by the lack of a clear sense of what that community might be. In particular: who is this database for, and who is most likely to build it? I suspect that these are two different sets of people.

Who is it for?

It strikes me that the primary target for GrBio is people who care about cleaning up and linking data. This is very small set of people. While cleaned data is nice, and cleaned and linked data is great, by itself it's not much use until it finds its way into useful tools. Why would taxonomists, curators, and other people working with biodiversity data care about GrBio? What can it give them? Ultimately, we'd like things such as the ability to find any specimen in the world online using simply it's museum collection code. We'd like to track usage of that code in other databases, such as GenBank and BOLD, and in the primary literature. These are all nice things, but they won't happen simply because we have a curated list of natural history collections.

Who will curate it?

Arguably there are only two active communities who care about the contents of GrBio on a scale to actually contribute. One is GBIF, which is building its own registry of collections as more and more natural history collections move their collections online. GBIF's registry is primarily for digital access points to collection data, which don't necessarily readily map to physical collections listed by GrBio. If GrBo is to be relevant, it needs to have mappings between its data and GBIF.

But the community that I suspect will really care about this, to the point that they'd actively engage in editing the data, is not the biodiversity community. Rather, it's people who edit Wikipedia and Wikidata.

I was at one of the GrBio workshops and gave a short presentation, which included this slide:

GrBio Workshop talk de Roderic Page

If you search for a major museum on Google, on the right you will often see a rich "knowledge panel" giving much of the information that GrBio wants to capture (museum name, location, etc.), often with a link to the Wikipedia page for that institution (see http://g.co/kg/m/01t372 for a detailed view of the knowledge panel for the NHM). GrBio can't compete with Wikipedia for richness of content (just think of all the Wikipedia pages in languages other than English). Google's database is mostly hidden, but we can get some of the same data from Wikidata, e.g. the Natural History Museum is entity Q309388 on Wikidata.

From my perspective, the smart move to make is not to appeal to an overstretched community of biodiversity researchers, many of whom are suffering from "project fatigue" as yet more acronyms compete for their attention. Instead, position the project as adding to the already existing database of natural history institutions that is growing in Wikidata. GrBio could either link to Wikidata and Wikipedia pages for institutions, or simply move it's data editing efforts to Wikidata and have GrBio be (at most) a search interface to that data. The notion of having a separate database for the world's collections might not be the best way to achieve GrBio's goals. A lot of people involved in both Wikipedia and Wikidata care about cultural institutions (of which natural history museums and herbaria are examples), those are the people GrBio should be engaging with.

Friday, August 26, 2016

Displaying original species descriptions in BioNames

B8e253dc3be3d84f2c69c51b0af86c03 400x400 The goal of my BioNames project is to link every taxonomic name to its original description (initially focussing on animal names). The rationale is that taxonomy is based on evidence, and yet most of this evidence is buried in a non-digitised and/or hard to find literature. Surfacing this information not only makes taxonomic evidence accessible (see Surfacing the deep data of taxonomy), it also surfaces a lot of basic biological information. In many cases the original taxonomic description will be an important source of information about what a species looks like, where it lives, and what it does.

To date I've focussed on linking names to publications, such as articles, on the grounds that this is the unit of citation in science. It's also the unit most often digitised and assigned an identifier, such as a DOI. But often taxonomists cite not an article but the individual page on which the description appears. In web-speak, taxonomists cite "fragment identifiers". Page-level identifiers are not often encountered in the digital world, in part because many digital representations don't have "pages". But this doesn't mean that we can't have identifiers for parts of an article, for example in Fragment Identifiers and DOIs Martin Fenner gives examples of ways to link to specific parts of an online article. His examples work if the article is displayed as HTML. If we are working with XML (say, for a journal published by Pensoft), then we can use XPath to refer to sections of a document. Ultimately it would be nice to have stable identifiers for document fragments linked to taxonomic names, so that we can readily go from name to description (even better if that description was in machine-readable form). You could think of these as locators for "taxonomic treatments", e.g. Miller et al. 2015.

As a quick and dirty approach to this I've reworked BioNames to be able to show the page where a species name is first published. This only works if a number of conditions are met:

The BioName database has the page number ("micro reference") for the name.
BioNames has the full text for the article, either from BioStor or a PDF.
The taxonomic name has been found in that text (e.g., by the Global Names GNRD service).

If these conditions are met, then BioNames will display the page, like this example (Belobranchus segura Keith, Hadiaty & Lord 2012: Screenshot 2016 08 26 16 13 50

Both the page image and OCR text (if available) are displayed. This is a first step towards (a) making stable identifiers available for these pages, and (b) making the text accessible for machine reading.

For some more examples, try Heterophasia melanoleuca kingi Eames 2002 (bird), Echinoparyphium anatis Fischthal & Kuntz 1976 (trematode), Bathymodiolus brooksi Gustafson, Turner, Lutz & Vrijenhoek 1998 (bivalve), Amolops cremnobatus Inger & Kottelat 1998 (frog), Leptothorax caesari Espadaler 1997 (ant), and Daipotamon minos Ng & Trontelj 1996 (crab).

Thursday, August 18, 2016

GBIF Challenge: €31,000 in prizes for analysing and addressing gaps and biases in primary biodiversity data

Full width In a classic paper Boggs (1949) appealed for an “atlas of ignorance”, an honest assessment of what we know we don’t know:

Boggs, S. W.. (1949). An Atlas of Ignorance: A Needed Stimulus to Honest Thinking and Hard Work. Proceedings of the American Philosophical Society, 93(3), 253–258. Retrieved from http://www.jstor.org/stable/3143475

This is the theme of this year's GBIF Challenge: Analysing and addressing gaps and biases in primary biodiversity data. "Gaps" can be gaps in geographic coverage, taxa group, or types of data. GBIF is looking for ways to access the nature of the gaps in the data it is aggregating from its network of contributors.

How to enter

Details on how to enter are on the Challenge website, deadline is September 30th.

Ideas

One approach to gap analysis is to compare what we expect to see with what we actually have. For example, we might take a “well-known” group of organisms and use that to benchmark GBIF’s data coverage. A drawback is that the “well-known” organisms tend to be the usual suspects (birds, mammals, fish, etc.), and there is the issue of whether the chosen group is a useful proxy for other taxa. Another approach is to base the estimate of ignorance on the data itself. For example, OBIS has computed Hurlbert's index of biodiversity for its database, e.g. http://data.unep-wcmc.org/datasets/16 Screenshot 2016 08 18 15 13 59 Can we scale these methods to the 600+ million records in GBIF? There are some clever methods for using resampling methods (such as the bootstrap) on large data sets that might be relevant, see http://www.unofficialgoogledatascience.com/2015/08/an-introduction-to-poisson-bootstrap_26.html.

Another approach might be to compare different datasets for the same taxa, particularly if one data set is not in GBIF. Or perhaps we can compare datasets for the same taxa collected by different methods.

Or we could look at taxonomic gaps. In an earlier post The Zika virus, GBIF, and the missing mosquitoes I noted that GBIF's coverage of vectors of the Zika virus was very poor. How well does GBIF cover vectors and other organisms relevant to human health? Maybe we could generalise this to explore other taxa. It might, for example, be interesting to compare degree of coverage for a species with some measure of the "importance" of that species. Measures of importance could be based on, say, number of hits in Google Scholar for that species, size of Wikipedia page (see Wikipedia mammals and the power law), etc.

Gaps might also be gaps in data completeness, quality, or type.

Summary

This post has barely scratched the surface of what is possible. But I think one important thing to bear in mind is that the best analyses of gaps are those that lead to "actionable insights", in other words, if you are going to enter the challenge (and please do, it's free to enter and there's money to be won), how does you entry help GBIF and the wider biodiversity community decide what to do about gaps?

BioStor updates: nicer map, reference matching service

BioStor now has 150,000 articles. When I wrote a paper describing how BioStor worked it had 26,784 articles, so things have progressed somewhat!

I continue to tweak the interface to BioStor, trying different ways to explore the articles.

Spatial search

I've tweaked spatial search in BioStor. As blogged about previously I replaced the Google Maps interface with Leaflet.js, enabling you to draw a search area on the map and see a set of articles that mention that area. I've changed the base map to the prettier "terrain" map from Stamen, and added back the layer showing all the localities in BioStor. This gives you a much better sense of the geographic coverage in BioStor. This search interface still needs work, but is a fun way to discover content.

Reference matching

In the "Labs" section of the web site I've added a demonstration of BioStor's reconciliation service. This service is based on the Freebase reconciliation service used by tools such as OpenRefine, see Reconciliation Service API. The goal is to demonstrate a simple way to locate references in BioStor, simply paste references, one per line, click Match and BioStor will attempt to find those references for you.

This service is really intended to be used by tools like OpenRefine, but this web page helps me debug the service.

Suggestions?

BioStor is part labour of love, part albatross around my neck. I'm always open to suggestions for improvements, or for articles to add (but remember that all content must first have been scanned and in the Biodiversity Heritage Library). If you are involved in publishing a journal and are interested in getting it into BHL, please get in touch.

Wednesday, August 17, 2016

Containers, microservices, and data

Docker Some notes on containers, microservices, and data. The idea of packaging software into portable containers and running them either locally or in the cloud is very attractive (see Docker). Some use cases I'm interested in exploring.

Microservices

In Towards a biodiversity knowledge graph (doi:10.3897/rio.2.e8767) I listed a number of services that are essentially self contained, such as name parsers, reconciliation tools, resolvers, etc. Each of these could be packaged up and made into containers.

Databases

We can use containers to package database servers, such as CouchDB, ElasticSearch, and triple stores. Using containers means we don't need to go through the hassle of installing the software locally. Interested in RDF? Spin up a triple store, play with it, then switch it off if you decide it's not for you. If it proves useful, you can move it to the cloud and scale up (e.g., sloppy.io).

Data

A final use case is to put individual datasets in a container. For exmaple, imagine that we have a large Darwin Core Archive. We can distribute this as a simple zip file, but you can't do much with this unless you have code to parse Darwin Core. But imagine we combine that dataset with a simpel visualisation tool, such as VESpeR (see doi:10.1016/j.ecoinf.2014.08.004). Users interested in the data could then play with the data without the overhead of installing specialist software. In a sense, the data becomes an app.

Friday, August 12, 2016

Spatial search in BioStor

I've been experimenting with simple spatial search in BioStor, as shown in the demo below. If you go to the map on BioStor you can use the tools on the left to draw a box or a polygon on the map, and BioStor will search it's database for articles that mention localities that occur in that region. If you click on a marker you can see the title of the article, clicking on that title takes you to the article itself.

This is all rather crude (and a little slow), but it provides another way to dive into the content I've been extracting from the BHL. One thing I've been doing is looking at protected areas (often marked on Open Street Map), drawing a simple polygon around that area, then seeing if BioStor knows anything about that area.

For the technically minded, this tool is an extension of the Searching GBIF by drawing on a map demo, and uses the geospatial indexing offered by Cloudant.

Wednesday, August 10, 2016

On asking for access to data

In between complaining about the lack of open data in biodiversity (especially taxonomy), and scraping data from various web sites to build stuff I'm interested in, I occasionally end up having interesting conversations with the people whose data I've been scraping, cleaning, cross-linking, and otherwise messing with.

Yesterday I had one of those conversations at Kew Gardens. Kew is a large institution that is adjusting to a reduced budget, a changing ditigal landscape, and a rethinking of it's science priorities. Much of Kew's data has not been easily accessible to the outside world, but this is changing. Part of the reason for this is that Defra, which part-funds Kew, is itself opening up (see Ellen Broad's fascinating post Lasers, hedgehogs and the rise of the Age of Yoghurt: reflections on #OpenDefra).

During this conversation I was asked "Why didn't you just ask for the data instead of scraping it? We would most likely have given it to you." My response to this was "well, you might have said no". In my experience saying "no" is easy because it is almost always the less risky approach. And I want a world where we don't have to ask for data, in the same way that we don't ask to get source code for open source software, and we don't ask to download genomic data from GenBank. We just do it and, hopefully, do cool things with it. Just as importantly, if things don't work out and we fail to make cool things, we haven't wasted time negotiating access for something that ultimately didn't work out. The time I lose is simply the time I've spent playing with the data, not any time negotiating access. The more obstacles you put in front of people playing with your data, the fewer innovative uses of that data you're likely to get.

But it was pointed out to me that a consequence of just going ahead and getting the data anyway is that it doesn't necessarily help people within an organisation make the case for being open. The more requests for access to data that are made, the easier it might be to say "people want this data, lets work to make it open". Put another way, by getting the data I want regardless, I sidestep the challenge of convincing people to open up their data. It solves my problem (I want the data now) but doesn't solve it for the wider community (enabling everyone to have access).

I think this is a fair point, but I'm going to try and wiggle away from it. From a purely selfish perspective, my time is limited, there are only so many things I can do, and making the political case for opening up specific data sets is not something I really want to be doing. In a sense, I'm more interested in what happens when the data is open. In other words, let's assume the battle for open has been won, what do we then? So, I'm essentially operating as if the data is already open because I'm betting that it will be at some point in time.

Without wishing to be too self-serving, I think there are ways that treating closed data as effectively open can help make the case that the data should (genuinely) open. For example, one argument for being open is that people will come along and do cool things with the data. In my case, "cool" means cross linking taxonomic names with the primary literature, eventually to original decsriptions and fundamental data about the organisms tagged with the taxonomic names (you may feel that this stretches the definitoon of "cool" somewhat). But adding value to data is hard work, and takes time (in some cases I've invested years in cleaning and linking the data). The benefits from being open may take time, especially if the data is messy, or relatively niche so that few people are prepared to invest the time necessary to do the work.

Some data, such as the examples given in Lasers, hedgehogs and the rise of the Age of Yoghurt: reflections on #OpenDefra will likely be snapped up and give rise to nice visualisations, but a lot of data won't. So, imagine that you're making the case for data to be open, and one of your arguments is "people will do cool things with it", eventually you win that argument, the data is opened up... and nothing happens. Wouldn't it be better if once the data is open, those of us who have been beavering away with "illicit" copies of the data can come out of the woodwork and say "by the way, here are some cool things we've been doing with that data"? OK, this is a fairly self-serving argument, but my point is that while internal arguments about being open are going on I have three choices:

Wait until you open the data (which stops me doing the work I want to do)
Help make the case for being open (which means I engage in politics, an area in which I have zero aptitude)
Assume you will be open eventually, and do the work I want to do so that when you're open I can share that work with you, and everyone else

Call me selfish, but I choose option 3.

Thursday, June 30, 2016

Aggregating annotations on the scientific literature: a followup on the ReCon16 hackday

In the previous post I sketched out a workflow to annotate articles using hypothes.is and aggregate those annotations. I threw this together for the hackday at ReCon 16 in Edinburgh, and the hack day gave me a chance to (a) put together a crude visualisation of the aggregated annotations, and (b) recruit CrossRef's Rachael Lammey (@rachaellammey) into doing some annotations as well so I could test how easy it was to follow my garbled instructions and contribute to the project.

We annotated the paper A new species of shrew (Soricomorpha: Crocidura) from West Java, Indonesia (doi:10.1644/13-MAMM-A-215). If you have the hypothes.is extension installed you will see our annotations on that page, if not, you can see them using the hypothes.is proxy: https://via.hypothes.is/http://dx.doi.org/10.1644/13-MAMM-A-215.

Rachael and I both used the IFTTT tool to send our annotations to a central store. I then created a very crude summary page for those annotations: http://bionames.org/~rpage/recon16-annotation/www/index.html?id=10.1644/13-MAMM-A-215. When this page loads it queries the central store for annotations on the paper with DOI 10.1644/13-MAMM-A-215, then creates some simple summaries.

For example, here is a list of the annotations. The listed is "typed" by tags, that is, you can tell the central store what kind of annotation is being made using the "tag" feature in hypothes.is. On this example, we've picked out taxonomic names, citations, geographical coordinates, specimen codes, grants, etc.

Given that we have latitude and longitude pairs, we can generate a map: Screenshot 2016 06 30 12 31 15

The names of taxa can be enhanced by adding pictures, so we have a sense of what organisms the paper is about:

The metadata on the web page for this article is quite rich, and hypothes.is does a nice job of extracting it, so that we have a list of DOIs for many of the articles this paper cites. I've chosen to add annotations for articles that lack DOIs but which may be online elsewhere (e.g., BioStor).

What's next

This demo shows that it's quite straightforward to annotate an article and pull those annotations together to create a central database that can generate new insights about a paper. For example, we can generate a map even if the original paper doesn't provide one. Conversely, we could use the annotations to link entities such as museum specimens to the literature that discusses those specimens. Given a specimen code in a paper we could look up that code in GBIF (using GBIF's API, or a tool like "Material Examined", see Linking specimen codes to GBIF). Hence we could go from code in paper to GBIF, or potentially from GBIF to the paper that cites the specimen. Having a central annotation store potentially becomes a way to build a knowledge graph linking different entities that we care about.

Of course, a couple of people manually annotating a few papers isn't scalable, but because hypothes.is has an API we can scale this approach (for another experiment see Hypothes.is revisited: annotating articles in BioStor). For example, we have automated tools to locate taxonomic names in text. Imagine that we use those tools to create annotations across the accessible biodiversity literature. We can then aggregate those into a central store and we have an index to the literature based on taxonomic name, but we can also click on any annotation and see that name in context as an annotation on a page. We could manually augment those annotations, if needed, for example by correcting OCR errors.

I think there's scope here for unifying the goals of indexing, annotation, and knowledge graph building with a fairly small set of tools.

Thursday, June 23, 2016

Aggregating annotations on the scientific literature: a hack for ReCon 16

7iUlfzBp I will be at ReCon 16 in Edinburgh (hashtag #ReCon_16), the second ReCon event I've attended (see Thoughts on ReCon 15: DOIs, GitHub, ORCID, altmetric, and transitive credit). For the hack day that follows I've put together some instructions for a way to glue together annotations made by multiple people using hypothes.is. It works by using IFTTT to read a user's annotation stream (i.e., the annotations they've made) and then post those to a CouchDB database hosted by Cloudant.

Why, you might ask? Well, I'm interested in using hypothes.is to make machine-readable annotations on papers. For example, we could select a pair of geographic co-ordinates (latitude and longitude) in a paper, tag it "geo", then have a tool that takes that annotation, converts it to a pair of decimal numbers and renders it on a map.

Or we could be reading a paper and the literature cited lacks links to the cited literature (i.e., there are no DOIs). We could add those by selecting the reference, pasted in the DOI as the annotation, and tagging it "cites". If we aggregate all those annotations then we could write a query that lists all the DOIs of the cited literature (i.e., it builds a small part of the citation graph).

By aggregating across multiple users we effectively crowd source the annotation problem, but in a way that we can still collect those annotations. For this hack I'm going to automate this collection by enabling each user to create an IFTTT recipe that feeds their annotations into the database (they can switch this feature off at any time by switching off the recipe).

Manual annotation is not scalable, but it does enable us to explore different ways to annotate the literature, and what sort of things people may be interested in. For example, we could flag scientific names, great numbers, localities, specimens, concepts, people, etc. We could explore what degree of post-processing would be needed to make the annotations computable (e.g., converting 8°07′45.73″S, 63°42′09.64″W' into decimal latitude and longitude).

If this project works I hope to learn something about people want to extract from the literature, and to what extent having a database of annotations can provide useful information. This will also help inform my thinking about automated annotation, which I've explored in Hypothes.is revisited: annotating articles in BioStor.

Wednesday, June 22, 2016

What happens when open access wins?

The last few days I've been re-reading articles about Ted Nelson's work (including ill-fated Project Xanadu), reading articles celebrating his work (brought together in the open access book "Intertwingled"), playing with Hypothes.is, and thinking about annotation and linking. One of the things which distinguishes Nelson's view of hypertext from the current web is that for Nelson links are first class citizens, they are persistent, they are bidirectional, and can be links not just documents but between parts of documents. In the web we have links that are unidirectional, when I link to something, the page I link to has no idea that I've made that link. Knowing who links to you turns out to be both hard to work out, and very valuable. In the academic world, links between articles (citations) form the basis of commercial databases such as the Web of Science. And of course, the distribution of links between web pages forms the basis of Google's search engine. Just as attempts to build free and open citation databases have come to nothing, there is no free and open search engine to compete with Google.

The chapters in "Intertwingled" make clear that hypertext had a long and varied history before being subsumed by the web. One project which caught my eye was Microcosm, which lead me to the paper "Dynamic link inclusion in online PDF journals" (doi:10.1007/BFb0053299, there's a free preprint here). This article tackles the problem of adding links to published papers. These links could be to other papers (citations), to data sets, to records in online databases (e.g., DNA sequences), names of organisms, etc. The authors outline four different scenarios for adding these links to an article.

In first scenario the reader obtains a paper from a publisher (either open access from behind a paywall), then using a "linkbase" that they have access too they add link to the paper.

This is very much what Hypothes.is offers, you use their tools to add annotations to a paper, and those annotations remain under your control.

In the second scenario, the publisher owns the linkbase and provides the reader with an annotated version of the paper.

This is essentially what tools like ReadCube offer. The two remaining scenarios cover the case where the reader doesn't get the paper from the publisher but instead gets the links. In one of these scenarios (shown below) the reader sends the paper to the publisher and gets the linked paper back in return, in the other (not shown) the reader gets the links but uses their own tools to embed them in the paper.

If you're still with me at this point you may be wondering how all of this relates to the title of this essay ("What happens when open access wins?"). Well, imagine that academic publishing eventually becomes overwhelmingly open access, so that publishers are making content available for free. Is this a sustainable business model? Might a publisher, seeing the writing on the wall, start to think about what they can charge for, if not articles (I'm deliberately ignoring the "author pays" model of open access as I'm not convinced this has a long term future).

In the diagrams above the "linkbase" is on the publisher's side in two of the three scenarios. If I was a publisher, I'd be looking to assembling proprietary databases and linking tools to create value that I could then charge for. I'm sure this is happening already. I suspect that the growing trend to open access for publications is not going to be enough to keep access to scientific knowledge itself open. In many ways publications themselves aren't terribly useful, it's the knowledge they contain that matters. Extracting, cross linking, and interpreting that knowledge is going to require sophisticated tools. The next challenge is going to be ensuring that the "linkbases" generated by those tools remain free and open, or an "open access" victory may turn out to be hollow.

Thursday, May 26, 2016

Thoughts on Wikipedia, Wikidata, and the Biodiversity Heritage Library

Given that Wikipedia, Wikidata, and the Biodiversity Heritage Library (BHL) all share the goal of making information free, open, and accessible, there seems to be a lot of potential for useful collaboration. Below I sketch out some ideas.

BHL as a source of references for Wikipedia

Wikipedia likes to have sources cited to support claims in its articles. BHL has a lot of articles that could be cited by Wikipedia articles. By adding these links, Wikipedia users get access to further details on the topic of interest. BHL also benefits from greater visibility resulting from visits from Wikipedia readers.

In the short term BHL could search Wikipedia for articles that could benefit from links to BHL (see below). In the long term as more and more BHL articles get DOIs this will become redundant as Wikipedia authors will discover articles via CrossRef.

There are various ways to search Wikipedia to get a sense of what links could be added. For example, you can search the Wikipedia API for pages that link to a particular web domain (see https://www.mediawiki.org/wiki/API:Lists/All#Exturlusage). Here's a search for articles linking to biostor.org https://en.wikipedia.org/w/api.php?action=query&list=exturlusage&euquery=biostor.org&eulimit=20.

A quick inspection suggests that many of these links could be improved (for example, some have outdated links to PDFs and not to the article), so we can locate Wikipedia articles that could be edited. It is likely that Wikipedia articles that have one link to BHL or BioStor may have other citations that could be linked.

Wikipedia as a source of content

One of the big challenges facing BHL is extracting articles from its content. My own BioStor is one approach to tackling this problem. BioStor takes citation details for articles and attempts to locate them in BHL - the limiting factor is access to good-quality citation data. Wikipedia is potentially an untapped source of citation data. Each page that uses the "Cite" template could be mined for citations, which in turn could be used to locate articles. Wikipedia pages using the Cite template can be found via the API, e.g. https://en.wikipedia.org/w/api.php?action=query&list=embeddedin&eititle=Template:Cite&eilimit=20&format=json. Alternatively, we could mine particular types of pages (e.g., those on taxa or taxonomists), or mine Wikispecies (which doesn't use the same citation formatting as Wikipedia).

Wikidata as a data store

If Wikidata aims to be a repository of all structured data relevant to Wikipedia, then this includes bibliographic citations (see WikiCite 2016 ), hence many articles in BHL will end up in Wikidata. This has some interesting implications, because Wikidata can model data with more fidelity than many other sources of bibliographic information. For example, it supports multiple languages as well as multiple representations of the sample language - the journal Acta Herpetologica Sinica https://www.wikidata.org/wiki/Q24159308 in Wikidata has not only the Chinese title (兩棲爬行動物學報) but the pinyin transliteration "Liangqi baxing dongwu yanjiu". Rather than attempt to replicate a community-editable database, Wikidata could be the place to manage article and journal-related metadata.

Disambiguating people

As we move from "strings to things" we need to associate names for things with identifiers for those things. I've touched on this already in Possible project: mapping authors to Wikipedia entries using lists of published works. Ideally each author in BHL would be associated with a globally unique identifier, such as ORCID or ISNI. Contributors to Wikipedia and Wikidata have been collecting these for individuals with Wikipedia articles. If those Wikipedia pages have links to BHL content then we can semi-automate the process of linking people to identifiers.

Caveats

There are a couple of potential "gotchas" concerning Wikipedia and BHL. The licenses used for content are different, BHL is typically CC-BY-NC whereas Wikipedia is CC-BY. The "non commercial" restriction used by BHL is a deal-breaker for sharing content such as page images with Wikicommons.

Wikipedia and Wikidata are communities, and I've often found this makes it challenging to find out how to get things done. Who do you contact to make a decsioon about some new feature you'd like to add? It's not at all obvious (unless you're a part of that community). Existing communities with accepted practices can be resistant to change, or may not be convinced that what you'd like to do is a benefit. For example, I think it would be great to have a Wikipedia page for each journal. Not everyone agrees with this, and one can expend a lot of energy debating the pros and cons. The last time I got seriously engaged with Wikipedia I ended up getting so frustrated I went off in a huff and built my own wiki. This is where a "Wikipedian in residence" might be helpful.

Notes on current and future projects

I'll be taking a break shortly, so I thought I'd try to gather some thoughts on a few projects/ideas that I'm working on. These are essentially extended notes to myself to jog my memory when I return to these topics.

BOLD data into GBIF

Following on from work on getting mosquito data into GBIF I've been looking at DNA barcoding data. BOLD data is mostly absent from GBIF. The publicly available data can be downloaded, and is in a form that could be easily ingested by GBIF. One problem is that the data is incomplete, and sometimes out of date. BOLD's data dumps and BOLD's API use different formats (sigh), and the API returns additional data such as image soft voucher specimens. Most data in the data dumps are not identified to species, so they will have limited utility for most GBIF users.

One approach would be to take the data dumps as the basic data, then use the API to enhance that data, such as adding image links. If the API returns a species-level identification for a barcode then that could be added as an identification using the corresponding Darwin Core extension. In this way we could treat the data as an evolving entity, which it is as our knowledge of it improves. For a related example see Leafcutter bee new to science with specimen data on Canadensys where Canadensys record two different identifications of some bee specimens as research showed that some specimens represented a new species.

This work reflects my concern that GBIF is missing a lot of data outside its normal sources. The mechanism for getting data into GBIF is pretty bureaucratic and could do with reforming (or, at least provision of other ways to add data).

BOLD by itself

I've touched on this before (Notes on next steps for the million DNA barcodes map), I'd really like to do something better with the way we display and interact with DNA barcode data. This will need some thought on calculating and visualising massive phylogenies, and spatial queries that return subtrees. I can't help thinking that there's scope for some very cool things in this area. If nothing else, we can do interesting things without getting involved in some of the pain of taxonomic names.

Big trees

Viewing big trees is still something of an obsession. I still think this hasn't been solved in a way that helps us learn about the tree and the entities in that tree. I currently think that a core problem to solve is how to cluster or "fold" a tree in a sensible way to highlight the major groups. I did something rather crude here, other approaches include "Constructing Overview + Detail Dendrogram-Matrix Views" (doi:10.1109/TVCG.2009.130, PDF here).

Graph databases and the biodiversity knowledge graph

I'm working on a project to build a "biodiversity knowledge graph" (see doi:10.3897/rio.2.e8767). In some ways this is recreating (my entry in Elsevier's Grand Challenge "Knowledge Enhancement in the Life Sciences", see also hdl:10101/npre.2009.3173.1 and doi:10.1016/j.websem.2010.03.004).

Currently I'm playing with Neo4J to build the graph from JSON documents stored in CouchDB. Learning Neo4J is taking a little time, especially as I'm creating nodes and edges on the fly and want to avoid creating more than one node for the same thing. In a world of multiple identifiers this gets tricky, but I think there's a reasonable way to do this (see the graph gist Handling multiple identifiers). Since I'm harvesting data I'm ending up building a web crawler, so I need to think about queues, and ways to ensure that data added at different times gets properly linked.

Wikipedia and wikidata

I occasionally play with Wikipedia and Wikidata, although this is often an exercise in frustration as editing Wikipedia tends to result in edit wars ("we don't do things that way"). Communities tend to be conservative. I'll write up some notes about ways Wikipedia and Wikidata can be useful, especially in the context of the Biodiversity Heritage Library (see also Possible project: mapping authors to Wikipedia entries using lists of published works).

All the names

The database of all taxonomic names remains as elusive as ever -- our field should be deeply embarrassed by this, it's just ridiculous.

My own efforts in this area involve (a) obtaining lists of names, by whatever means available, and (b) augmenting them to include links to the primary literature. I've made some this work publicly accessible (e.g., BioNames). I'd like all name databases to make their data open, but most are resistant to the idea (some aggressively so).

One approach to this is to simply ignore the whimpering and make the data available. Another is to consider recreating the data. We have name finding algorithms, and more of the literature is becoming available, either completely open (e.g., BHL) or accessible to mining (see Content Mine). At some point we will be able to recreate the taxonomic name databases from scratch, making the obstinate data providers not longer relevant.

First descriptions

Names, by themselves, are not terribly useful. But the information that hangs off them is. it occurs to me that projects like BioNames (and other things I've been working on such as IPNI names) aren't directly tackling this. Yes, it's nice to have a bibliographic citation/identifier for the original description of a name (or subsequent name changes), but what we'd really like is to be able to (a) see that description and (b) have it accessible to machines. So one thing I plan to add to BioNames automate going from name to the page with the actual description, and display this information. For many names BioNames knows the page number of the description, and hence it's location within the publication. So we need to simply pull out that page (allowing for edge cases where the mapping between digital and physical pages might not be straight forward) and display it (together with text). If we have XML we can also try and locate the descriptions within the text (for some experiments using XSLT see https://github.com/rdmpage/ipni-names/tree/master/pmc ).There's lots of scope for simple text mining here, such as specimen codes (such as type specimens) and associated taxonomic names (synonyms, ecologically associated organisms, etc.).

Dockerize all the things!

Lots of scope to explore using container to provide services. Docker Hub provides Elastic Search and Neo4J, and Bitnami can run Elastic Search and CouchDB on Google's cloud. Hence we can play with various tools without having to install them. The other side is creating containers to package various tools (Global Names is doing this), or using containers to package up particular datasets and the tools needed to explore them. So much to learn in this area.

Wednesday, May 11, 2016

Scott Federhen

Images Awoke this morning to the sad news (via Scott Miller) that Scott Federhen of the NCBI had died. Anyone using the NCBI taxonomy is a beneficiary of Scott's work on bring together taxonomy and genomic data.

Scott contributed both directly and indirectly to this blog. I reported on some of his work linking taxa in NCBI to sequences from type material (NCBI taxonomy database now shows type material), Scott commented on "dark taxa" and DNA barcoding (e.g., Dark taxa even darker: NCBI pulls (some) DNA barcodes from GenBank (updated)), and was an author on a guest post on "Putting GenBank Data on the Map" (in response to http://dx.doi.org/10.1126/science.341.6152.1341-a). He was also very helpful when I wanted to make links between the NCBI taxonomy and Wikipedia in my iPhylo Linkout project (see http://dx.doi.org/10.1371/currents.RRN1228).

I didn't know Scott well, but always enjoyed chatting to him at meetings (most recently the 6th International Barcode of Life Conference at Guelph). He wasn't shy about putting forth his views, or sharing his enthusiasm for ideas. Indeed, last time we met he was handing out paper copies of his preprint "Replication is Recursion; or, Lambda: the Biological Imperative" (available on bioRχiv http://dx.doi.org/10.1101/018804). He then followed up by sending me a t-shirt with the "replication is recursion" logo printed on one side and some penguins on the other (if I remember correctly this was designed by a member of his family). I delight in baffling students by wearing it sometimes when I lecture.

A number of people in the bioinformatics and biodiversity informatics communities are in shock this morning, this is obviously as nothing compared to what his family must be going through.

Tuesday, May 10, 2016

Notes on next steps for the million DNA barcodes map

Some notes to self about future directions for the "million DNA barcodes map" http://iphylo.org/~rpage/bold-map/.

At the moment we have an interactive map that we can pan and zoom, and click on a marker to get a list of one or more barcodes at the location. We can also filter by major taxonomic group. Here are some ideas on what could be next.

Search

At the moment search is simply browsing the map. It would be handy to be able to enter a taxon or a barcode identifier and go to the corresponding markers on the map.

What is this?

If we have a single DNA barcode I immediately want to know "what is this?" A picture may help, and I may look up the scientific name in BioNames, but perhaps the most obvious thing to do is get a phylogeny for that barcode and similar sequences. These could then be displayed on the map using the technique I described in Visualising Geophylogenies in Web Maps Using GeoJSON (see also http://dx.doi.org/10.1371/currents.tol.8f3c6526c49b136b98ec28e00b570a1e).

So, ideally we would:

Display information about that barcode (e.g., taxonomic identification where known).
Display the local phylogeny of barcodes that contains this barcode.
Display that phylogeny on the map

Hence we need to be able to generate a local phylogeny of barcodes, either on the fly (retrieve similar sequences then build tree) or using a precompute global barcode phylogeny from which we pull out the local subtree.

What is there?

A question that the map doesn't really answer is "what is the diversity of a given area?". Yes there are lots of dots, and you can click on them, but what would be nice is the ability to draw a polygon on the map (like this) and get a summary of the phylogenetic diversity of barcodes within that area.

100144 drummond For example, imagine drawing a polygon around Little Barrier Island in New Zealand. Can we effectively retrieve the data published by Drummond et al. ( Evaluating a multigene environmental DNA approach for biodiversity assessment DOI:10.1186/s13742-015-0086-1)?.

To support "what is there?" queries we need to be able to:

Draw an arbitrary spatial region region on the map and retrieve a set of sequences found within that region
Retrieve the phylogeny for that set of sequences

Once agin, we either need to be able to build a phylogeny for an arbitrary set of sequences on the fly, or extract a subtree. If the a global tree is available, we could compute the length of the subtree, and also compute a visual layout fairly easily (essentially with time proportional to the number of sequences).

We'd also need to decide on the best way to visualise the phylogeny for the set of sequences. Perhaps something like Krona, or something more traditional.

Summary

There doesn't seme to be any way of getting away from the need for a global phylogeny of COI DNA barcodes if I want to extend the functionality of the map.