BNCOD 2008 Workshop

The proceedings of the BNCOD 2008 Workshop on "Biodiversity Informatics: challenges in modelling and managing biodiversity knowledge" are online. This workshop was held in conjunction with the 25th British National Conference on Databases (BNCOD 2008) at Cardiff, Wales. The papers make interesting reading.

Exploring International Plant Names Index (IPNI) Data using Visualisation by Nicola Nicolson [PDF]

This paper describes visualisation as a means to explore data from the International Plant Names Index (IPNI). Several visualisations are used to display large volumes of data and to help data standardisation efforts. These have potential uses in data mining and in the exploration of taxon concepts.

Nicky explores some visualisations of the IPNI plant name database. Unfortunately only one of these (arguably the east exciting one) is shown in the PDF. The visualisations of citation history using Timeline, and social networks using prefuse are mentioned, but not shown.

Scratchpads: getting biodiversity online, redefining publication by Vince Smith et al. [PDF]

Taxonomists have been slow to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of taxonomic research. Here we describe a social networking application (Scratchpads) that enables communities of biodiversity researchers to manage and publish their data online. In the first year of operation 466 registered users comprising 53 separate communities have collectively generated 110,000 pages within their Scratchpads. Our approach challenges the traditional model of scholarly communication and may serve as a model to other research disciplines beyond biodiversity science.

This is a short note describing Scratchpads, which are built using the Drupal content management system (CMS). Scratchpads provide a simple way for taxonomists to get their content online. Based in large measure on the success of scratchpads, EOL will use Drupal as the basis of their "Lifedesks". There are numerous scratchpads online, although the amount and quality of content is, um, variable.

Managing Biodiversity Knowledge in the Encyclopedia of Life by Jen Schopf et al. [PDF]

The Encyclopedia of Life is currently working with hundreds of Content Providers to create 1.8 million aggregated species pages, consisting of tens of millions of data objects, in the next ten years. This article gives an overview of our current data management and Content Provider interactions.

This is a short note on EOL itself. I've given my views on EOL's progress (or, rather, lack thereof) elsewhere (here, here and here). The first author on this paper has left the project, and at least one of the other authors is leaving. It seems EOL has yet to find its feet (it certainly has no idea of how to use blogs).


Distributed Systems and Automated Biodiversity Informatics: Genomic Analysis and Geographic Visualization of Disease Evolution by Andrew Hill and Robert Guralnick [doi:10.1007/978-3-540-70504-8_28]

A core mission in biodiversity informatics is to build a computing infrastructure for rapid, real-time analysis of biodiversity information. We have created the information technology to mine, analyze, interpret and visualize how diseases are evolving across the globe. The system rapidly collects the newest and most complete data on dangerous strains of viruses that are able to infect human and animal populations. Following completion, the system will also test whether positions in the genome are under positive selection or purifying selection, a useful feature to monitor functional genomic charac-teristics such as, drug resistance, host specificity, and transmissibility. Our system’s persistent monitoring and reporting of the distribution of dangerous and novel viral strains will allow for better threat forecasting. This information system allows for greatly increased efficiency in tracking the evolution of disease threats.

This paper is was one of two contributions chosen to be proceedings BNCOD 2008 ("Sharing Data, Information and Knowledge", doi:10.1007/978-3-540-70504-8, ISBN 978-3-540-70503-1). Rob Guralnick has put a free version online (see his comment below). It describes the very cool system being developed to provide near real time visualisation of disease spread and evolution, and builds on some earlier work published in Systematic Biology (doi:10.1080/10635150701266848).

LSID Deployment in the Catalogue of Life by Ewen Orme et al. [PDF]

In this paper we describe a GBIF/TDWG-funded project in which LSIDs have been deployed in the Catalogue of Life’s Annual and Dynamic Checklist products as a means of identifying species and higher taxa in these large species catalogues. We look at the technical infras- tructure requirements and topology for the LSID resolution process and characteristics of the RDF (Resource Description Framework) metadata returned by the resolver. Such characteristics include the use of concepts and relationships taken from the TDWG (Taxonomic Database Working Group) ontology and how a given taxon LSID relates to others includ- ing those issued by database providers and those above and below it in the taxonomic tree. Finally we evaluate the pro ject and LSID usage in general. We also look to the future when the CoL LSID infrastructure will have to deal changing taxonomic information, annually in the case of the Annual Checklist and possibly much more frequently in the case of the Dynamic Checklist.

Although I was an early adopter of LSIDs (in my now defunct Taxonomic Search Engine doi:10.1186/1471-2105-6-48 and the very-much alive LSID Tester, doi:10.1186/1751-0473-3-2), I have some reservations about them. The Catalogue of Life uses UUIDs to generate the LSID identifier, which makes for rather ugly looking LSIDs, as David Shorthouse has complained. For example, the LSID for Pinnotheres pisum urn:lsid:catalogueoflife.org:taxon:ef0ae064-29c1-102b-9a4a-00304854f820:ac2008 (gack). Why these ugly UUIDs? Well, one advantage is that they can be generated in a distributed fashion and remain unique. This would make sense for a project like the Catalogue of Life, which aggregates names from a range of contributors, but in actual fact all the LSIDs at present are of the form "xxxxxxxx-29c1-102b-9a4a-00304854f820", indicating that they are being generated centrally (by MySQL's UUID function, in this case).

Ironically, when I was talking to Frank Bisby earlier this year, he implied that LSIDs would change with each release if the information about a name changed, thus failing to solve the existing, fundamental design flaw in the Catalogue of Life, namely the lack of stable identifiers! So, at first glance we are stuck with hideous-looking identifiers that may be unstable. Hmmm...

Workflow Systems for Biodiversity Researchers: Existing Problems and Potential Solutions by Russel McIver et al. [PDF]

In this paper we discuss the potential that scientific work- flow systems have to support biodiversity researchers in achieving their goals. This potential comes through their ability to harness distributed resources and set up complex, multi-stage experiments. However, there remain concerns over the usability of existing workflow systems and re- search still needs to be done to help match the functionality of the soft- ware to the needs of its users. We discuss some of the existing concerns regarding workflow systems and propose three potential interfaces in- tended to improve workflow usability. We also outline the software ar- chitecture that we have adopted, which is designed to make our proposed workflow interface software interoperable across key workflow systems.

Not sure what to make of this paper. Workflows seem to generate an awful lot of publications, and few tools that people actually use.


Visualisation to Aid Biodiversity Studies through Accurate Taxonomic Reconciliation by Martin Graham et al. [doi:10.1007/978-3-540-70504-8_29]

All aspects of organismal biology rely on the accurate identification of specimens described and observed. This is particularly important for ecological surveys of biodiversity, where organisms must be identified and labelled, both for the purposes of the original research, but also to allow reinterpretation or reuse of collected data by subsequent research projects. Yet it is now clear that biological names in isolation are unsuitable as unique identifiers for organisms. Much modern research in ecology is based on the integration (and re-use) of multiple datasets which are inherently complex, reflecting any of the many spatial and temporal environmental factors and organismal interactions that contribute to a given ecosystem. We describe visualization tools that aid in the process of building concept relations between related classifications and then in understanding the effects of using these relations to match across sets of classifications.

The second contribution published in the conference proceedings, but there is also free version available here from the project's blog. The paper describes TaxVis, a project developing visualisation techniques for comparing multiple taxonomic hierarchies.

The paper discusses taxonomic concepts and the difficulty of establishing what a taxonomist meant when they used a particular name. As much as I understand the argument, I can't shake the feeling that obsessing about taxonomic concepts is ultimately a dead end. It won't scale, and in an age of DNA barcoding, it becomes less and less relevant.

Releasing the content of taxonomic papers: solutions to access and data mining by Chris Lyal and Anna Weitzman [PDF]

Taxonomic information is key to all studies of biodiversity. Taxonomic literature contains vast quantities of that information, but it is under-utilised because it is difficult to access, especially by those in biodiverse countries and non-taxonomists. A number of initiatives are making this literature available on the Web as images or even as unstructured text, but while that improves accessibility, there is more that needs to be done to assist users in locating the publication; locating the relevant part of the publication (article, chapter etc) and locating the text or data required within the relevant part of the publication. Taxonomic information is highly structured and automated scripts can be used to mark-up or parse data from it into atomised pieces that may be searched and repurposed as needed. We have developed a schema, taXMLit that allows for mark-up of taxonomic literature in this way. We have also developed a prototype system, INOTAXA that uses literature marked up in taXMLit for sophisticated data discovery.

This is a nice overview of the challenge of extracting information from legacy literature. There are numerous challenges facing this work, including taks that are trivial for people, such as determining when an article starts and ends, but which are challenging for computers (see Lu et al. doi:10.1145/1378889.1378918, free copy here -- there is a job related to this question available now). Related efforts are the TaxonX markup being used by Plazi. My own view is that for legacy literature heavy markup is probably overkill, decent text mining will be enough. The real challenge is to stop the rot at source, and enable new taxonomic publications to be marked up as part of the authoring and publishing process.

An architecture to approach distributed biodiversity pollinators relational information into centralized portals based on biodiversity protocols by Pablo Salvanha et a. [PDF]

The present biodiversity distributed solution using DiGIR / TAPIR protocols and the Darwincore2 schema has been very valuable in the centralized portals, which that can provide distributed information in a very quickly way. Using the same concept this paper presents an architecture based on the case study of pollinators to bring the centralization of the relational information to those portals. This architecture is based on a technological structure to facilitate the implementation and extraction from the providers of that relational information, and proposes a model to make this information reliable to be used with the present specimens information on the portal database.

This is a short note on extending DarwinCore to include information about pollination relationships. The wisdom of doing this has been question (see Roger Hyam's comment on the proposal).

A Pan-European Species-directories Infrastructure (PESI) by Charles Hussey and Yde de Jong [PDF]

This communication introduces the rationale and aims of a new Europe-wide biodiversity informatics project. PESI defines and coordinates strategies to enhance the quality and reliability of European biodiversity information by integrating the infrastructural components of four major community networks on taxonomic indexing, namely those of marine life, terrestrial plants, fungi and animals, into a joint work programme. This will include functional knowledge networks of both taxonomic experts and regional focal points, which will collaborate on the establishment of standardised and authoritative taxonomic (meta-) data. In addition PESI will coordinate the integration and synchronisation of the European taxonomic information systems into a joint e-infrastructure and the creation of a common user-interface disseminating the pan- European checklists and associated user-services results.

This paper describes PESI, yet another mega-science project in biodiversity, complete with acronyms, work packages, and vacuous, buzzword-compliant statements. Just what the discipline needs...

Dinosaurs and the Cretaceous Terrestrial Revolution

Shameless plug. One of my former PhD students, Katie Davis, is second author on "Dinosaurs and the Cretaceous Terrestrial Revolution" (doi:10.1098/rspb.2008.0715), which came out recently in Proceedings of the Royal Society. The abstract:

The observed diversity of dinosaurs reached its highest peak during the mid- and Late Cretaceous, the 50 Myr that preceded their extinction, and yet this explosion of dinosaur diversity may be explained largely by sampling bias. It has long been debated whether dinosaurs were part of the Cretaceous Terrestrial Revolution (KTR), from 125–80 Myr ago, when flowering plants, herbivorous and social insects, squamates, birds and mammals all underwent a rapid expansion. Although an apparent explosion of dinosaur diversity occurred in the mid-Cretaceous, coinciding with the emergence of new groups (e.g. neoceratopsians, ankylosaurid ankylosaurs, hadrosaurids and pachycephalosaurs), results from the first quantitative study of diversification applied to a new super tree of dinosaurs show that this apparent burst in dinosaurian diversity in the last 18 Myr of the Cretaceous is a sampling artefact. Indeed, major diversification shifts occurred largely in the first one-third of the group’s history. Despite the appearance of new clades of medium to large herbivores and carnivores later in dinosaur history, these new originations do not correspond to significant diversification shifts. Instead, the overall geometry of the Cretaceous part of the dinosaur tree does not depart from the null hypothesis of an equal rates model of lineage branching. Furthermore, we conclude that dinosaurs did not experience a progressive decline at the end of the Cretaceous, nor was their evolution driven directly by the KTR.

Now, if we could just get the bird supertree paper out the door...

Spida of Love

Systematics makes The Colbert Report.



The paper describing Aptostichus stephencolbertio by Jason Bond and Amy Stockman has been published in Systematic Biology doi:10.1080/10635150802302443. Jason described also described Aptostichus angelinajolieae in the same paper, but I guess she is otherwise engaged.

iSpecies gets automated tagging

Given that the clones are hot on my heels, I feel the need to add more bells and whistles to iSpecies. The first new feature is automated tagging, and uses Yahoo's Term Extraction API. I send the titles of any papers found, and the Wikipedia snippet, and Yahoo returns keywords ("tags").


As an example, here are the tags for one of my favourite animals, Helice crassa.

mud crabs mangrove estuary muddy sediments mud crab sea coasts mud flats sex ratios habitat preferences activity patterns laboratory conditions estuarine gills burrows endemic respiration original article morphology ventilation dana biology

I think these give a nice sense of what we know about this crab.

I'm storing the tags for future analysis. I think there are some interesting ideas to explore, such as clustering the tags into meaningful groups. I'm also interested in how much we can learn about an organism based on these keywords. Can we automatically infer something about the ecology of the organism?

There is also scope for adding some semantics. Some of these tags are taxon names, and some refer to geographic places. Some are concepts, which could be linked to the relevant page in Wikipedia (Faviki is an example of this approach). At present the tags aren't clickable (i.e., you can't query by tag), but that would be a useful feature. One could get taxa that were tagged with a given term, such as "estuarine". For now, it's a quick way to get a sense of what we know about a taxon.

iPhone, barcodes, and natural history museums

One of my pet peeves is how backward natural history museums are in grasping the possibilities the Internet raises. Most electronic displays in museums have low information content, and are doomed to obsolescence. Traditional media (plaques, labels) have limited space, and also date quickly. For example, the Natural History Museum in London has a skeleton of Diplodocus carnegiei (see photo below by EmLah). This is one of many replicas distributed around the world.


The plaque describing this fossil has fairly minimal information. Wikipedia, however, has a nice article on Diplodocus, which includes a public domain image of the replica skeleton being presented to the trustees of the British Museum of Natural History in 1905.

Given the limitations of physical media, museum labels and plaques will always be small, and will often be out of date. Wikipedia, of course, can be kept current, and anybody can contribute.

So, the trick is to link the physical object to the Internet. This is now trivial thanks to mobile tagging. By pointing a mobile phone with a camera at a 2D barcode, one can go from physical object to web site.


Here is a 2D barcode for the URL of the Wikipedia article on Diplodicus. Imagine taking your iPhone, pointing it at this barcode, and being taken to the Wikipedia page. If museums were clever, they could set out their own Wiki, and mobilise the combined skills of the museum staff, volunteers, and visitors to populate it.

Now that the iPhone has applications, imagine creating an application that read these barcodes. Kevin Chiu at Columbia has a made one, and there are others out there. Museums could build on this, brand it with their logo, and greatly enhance visitor experience.

Wonder if anyone is doing this...?

Zitgist

Stumbled across Zitgist (via UMBEL), and thought the diagram above was so cool I'd have to blog about it. Zitgist is one of a growing number of Semantic Web companies, specialising in Linked Data. This topic is dear to my heart, so I'll need to keep an eye on what Zitgist and others are up to.

Why isn't EOL using Wikipedia?

Interesting paper by Huss et al. in PLoS Biology entitled "A Gene Wiki for Community Annotation of Gene Function" (doi:10.1371/journal.pbio.0060175). Essentially, the paper describes using Wikipedia to create a comprehensive gene wiki:

In principle, a comprehensive gene wiki could have naturally evolved out of the existing Wikipedia framework, and as described above, the beginnings of this process were already underway. However, we hypothesized that growth could be greatly accelerated by systematic creation of gene page stubs, each of which would contain a basal level of gene annotation harvested from authoritative sources. Here we describe an effort to automatically create such a foundation for a comprehensive gene wiki. Moreover, we demonstrate that this effort has begun the positive-feedback loop between readers, contributors, and page utility, which will promote its long-term success.

Given that the EOL project seems stalled (i.e., the current content hasn't changed), and the existing Wikipedia content is often much richer than EOL's, one has to ask why EOL doesn't give up it's current model and make use of Wikipedia? In other words, create all its taxon pages in Wikipedia.

OpenDOI

Brian de Alwis has written a cool Apple Script called OpenDOI that adds support for resolving doi: and hdl: URLs using Safari on a Mac. With it installed, links such as hdl:10101/npre.2008.1760.1 and doi:10.1093/bib/bbn022 become clickable, without having to stick a HTTP proxy in front of them.

Seems that an obvious extension to this would be to add support for LSIDs. Firefox can support LSIDs through the LSID Browser for Firefox, but this won't work with Safari. Something for the to do list.

It pays to put things on the Web

Seems obvious in retrospect, but on of the great things about putting stuff online is that it may be useful to other people. What seems like ages ago I developed the Glasgow Taxonomic Name Server to experiment with searching for and display taxonomic names and classifications. As part of that work I developed a SOAP web service, and wrote a tutorial on how to use SOAP from within Microsoft Excel. I did this mainly for my own benefit, so that I wouldn't forget how to do it (much Googling was required). This tutorial has been reproduced, updated and credited, by the World Register of Marine Species (WoMRS). I only realised this after browsing the WoMRS site after following a recent conversation on TAXACOM about the proper name of the sperm whale. The take home message is that you never know who will make use of something you've done, and the chances are that if you've solved a problem, somebody else may well benefit from your solution.

dechronization

Rich Glor brought dechronization to my attention. This is a very active blog "by junior academic scientists whose research focuses on evolution, reconstruction of phylogenetic trees, and comparative methods." There's some nice stuff there, including software reviews, paper appraisals, conference reports, and *cough* porn.

Library Git

Just a quick not to make a link between David Shorthouse's post about taxonomic consensus and distributed version control (Taxonomic Consensus as Software Creation), and Galen Charlton's article in The Code4Lib Journal (Distributed Version Control and Library Metadata). Some interesting food for thought here. Both mention Git. If you want to know more, watch Linus Torvald's wonderfully direct talk at Google:

Agenames

Stumbled across the cool AgeNames service, described on the stratigraphy.net blog. Agenames takes some text and extracts stratigraphic terms from text. For example, it will extract geological time periods from text. It's a geological equivalent of uBio's taxonomic name extraction services. It would be fun to play with this as part of the iPhylo project.

Charting taxonomic knowledge

Nice paper by Robert Huber and Jens Klump has appeared in Computers & Geosciences entitled "Charting taxonomic knowledge through ontologies and ranking algorithms" (doi:10.1016/j.cageo.2008.02.016). The paper is not open access, but you can get some background from the post How TaxonRank works. Here's the abstract.

Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research.

The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria.

The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute to the preservation our scientific heritage.

How to succeed in evolutionary biology, without really trying

Lab Times has an interesting article by Ralf Neumann that analyses Europe's publications in evolutionary biology for the period 1996-2006. On page 36 there is a table of the 30 most cited authors in Europe, and the top five most cited papers. To my astonishment, I'm there at number 10 (accompanied by a photo taken in New York). What is interesting is that although the top 30 are varied in their interests, and include some well known names in the field, the top five papers in terms of citations are all about phylogenetic methods:

1. Page, RDM
   TreeView: An application to display phylogenetic trees on personal computers.
   COMPUTER APPLICATIONS IN THE BIOSCIENCES, 12 (4): 357-358 AUG 1996 (doi:10.1093/bioinformatics/12.4.357)


2. Strimmer, K; von Haeseler, A
   Quartet puzzling: A quartet maximum-likelihood method for reconstructing tree topologies.
   MOLECULAR BIOLOGY AND EVOLUTION, 13 (7): 964-969 SEP 1996


3. Ronquist, F; Huelsenbeck, JP
   MrBayes 3: Bayesian phylogenetic inference under mixed models.
   BIOINFORMATICS, 19 (12): 1572-1574 AUG 12 2003 (doi:10.1093/bioinformatics/btg180)


4. Yang, ZH
   PAML: a program package for phylogenetic analysis by maximum likelihood.
   COMPUTER APPLICATIONS IN THE BIOSCIENCES, 13 (5): 555-556 OCT 1997 (doi:10.1093/bioinformatics/13.5.555)


5. Guindon, S; Gascuel, O
   A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.
   SYSTEMATIC BIOLOGY, 52 (5): 696-704 OCT 2003 (doi:10.1080/10635150390235520)

Note also that most of these papers are short application notes. Of course, the number of pages in the publication bears no relation to the effort involved in writing the actual software. The other thing that's interesting is that of the 30 most cited authors, I have published the second smallest number of papers (40). A quick plot of the number of citations against number of papers suggests published suggests that while there is a correlation between effort (papers) and impact (citations), it's not perfect (ρ = 0.44, R²= 0.19). You can have a reasonable impact without generating lots of papers.

So, what can we learn from this? Well, it would be tempting to offer advice along the lines of "if you want to succeed in this field, write a piece of software that a lot of people find useful, and make sure you have a publication that they can cite." Oh, and getting in early helps. Of course, this advice should be taken with a pinch of salt. Beware the 100th idiot.

iSpecies clones, and taxonomic intelligence

Mauro Cavalcanti has released e-Species, "a taxonomically intelligent biodiversity search engine" written in Python that mimics much of the functionality of iSpecies. The project is open source, with a SourceForge page, although no files seem to be available yet. This is the second iSpecies clone I've seen, David Shorthouse having written a clone that uses only JSON.

One thing which distinguishes e-Species is the use of Catalogue of Life web services to provide some information on the name. However, it doesn't look like e-Species makes use of synonyms in its searches (i.e., what many refer to as "taxonomic intelligence"). Searching on two alternative names for the sperm whale (Physeter catodon and P. macrocephalus) yields different results (unless the underlying source knows that these names are synonyms, such as NCBI). Presumably, a taxonomically intelligent search would be able to merge results from searches using different names, and present those together.

Merging results requires some thought as to how to merge lists from different sources (e.g., merging lists of publications and images). This has been the subject of much study in the context of merging results from different search engines. Some starting points are:

• Rank Aggregation Methods for the Web
• Aggregation of partial rankings, p-ratings and top-m lists
• Tadpole: A Meta search engine

The last link is a student project and is a Microsoft Word document, which I've uploaded to Scribd and embedded below.

Tadpole: A Meta search engine - Upload a Document to Scribd

Read this document on Scribd: Tadpole: A Meta search engine

The end of science, and the end of taxonomy

Mauro Cavalcanti brought Chris Anderson's The End of Theory article in Wired to my attention, part of the July issue on "The End of Science".

Of course, the end of science is hyperbole of the highest order (as, indeed, is the "end of theory"). It is also ironic that in the same issue Wired confess to having gotten 5 predictions of the death of something hopelessly wrong (including web browsers and online music swapping, no less). However, I guess the reason Mauro sent me the link is this section:

The best practical example of this is the shotgun gene sequencing by J. Craig Venter. Enabled by high-speed sequencers and supercomputers that statistically analyze the data they produce, Venter went from sequencing individual organisms to sequencing entire ecosystems. In 2003, he started sequencing much of the ocean, retracing the voyage of Captain Cook. And in 2005 he started sequencing the air. In the process, he discovered thousands of previously unknown species of bacteria and other life-forms.

If the words "discover a new species" call to mind Darwin and drawings of finches, you may be stuck in the old way of doing science. Venter can tell you almost nothing about the species he found. He doesn't know what they look like, how they live, or much of anything else about their morphology. He doesn't even have their entire genome. All he has is a statistical blip — a unique sequence that, being unlike any other sequence in the database, must represent a new species.

This sequence may correlate with other sequences that resemble those of species we do know more about. In that case, Venter can make some guesses about the animals — that they convert sunlight into energy in a particular way, or that they descended from a common ancestor. But besides that, he has no better model of this species than Google has of your MySpace page. It's just data. By analyzing it with Google-quality computing resources, though, Venter has advanced biology more than anyone else of his generation.

Leaving aside whether Venter has indeed "advanced biology more than anyone else of his generation" (how, exactly, can one measure that?), it started me thinking about the yawning chasm between efforts such as the Encyclopedia of Life and the Catalogue of Life on one hand, and, say metagenomics on the other. EoL and CoL have a view of life that is taxon, indeed, species-centric, that appeals to our sense of what matters (basically those organisms we can see comfortably with the naked eye, and interact with). But if you browse the NCBI taxonomy, not only do you see an attempt to classify organisms phylogenetically, you will also encounter "taxa" that are metagenomes (e.g., NCBI Taxonomy ID 408169). These metagenomes are the result of shotgun sequencing environmental samples, they comprise multiple taxa. In this way, they resemble large-scale sampling events such as plankton netting, or tree fogging, which results in masses of material, much of it unidentified. One difference is that the metagenomes are digitised (i.e., sequenced), and hence can be analysed further (as opposed to a mass of specimens in jars). Indeed, this is one motivation behind DNA barcoding -- the ability to digitise massive samples of organisms.

So, perhaps if we overlook the "end of theory" bit (although this is appealing given that some critiques of DNA barcoding have made overblown claims for taxonomy as hypothesis-driven science), the key here is that much of what in an earlier age might have been provisional knowledge unfit for public consumption (e.g., a bunch of unidentified samples) is now very public. In the past, taxonomists wouldn't describe new taxa without sufficient information for a decent description, now the most actively growing taxonomic database (NCBI) has "taxa" that are aggregates of unidentified, unknown (and possibly, unknowable) organisms.

PhyQL

Hasan Jamil has released PhyQL, a visual system for querying
phylogenetic information. To quote from the web site:

Popular phylogenetic databases such as TreeBASE, PhyloFinder, TreeFAM offer complex text-based web forms for structure queries. Still there seems a great need for intelligent visual query formation based on a phylogenetic query language for content exploration. PhyQL offers a visual query design interface where the user can create simple to complex queries based visual query operators. The query language is translated to a list of datalog queries, then executed in XSB, an extension of Prolog. Separating the application layer from the data layer by a logic layer reduces query tools development time. Moreover, PhyQL offers interactive tree visualization which is very convenient for viewing very large trees.

There is also a YouTube screencast:


I haven't had a chance to play with it yet. PhyQL was originally described by Jamil et al. "Querying phylogenies visually", BIBE 2001 (doi:10.1109/BIBE.2001.974405).

tvwidget released

I've put the first version of "tvwidget" into Google Code. This is a HTML-only widget to display large evolutionary trees (you can see how my thoughts on how to do this unfolded by following my earlier posts starting with Visualising very big trees, Part V). tvwidget itself is a C++ program that takes a tree and generates the image tiles and Javascript for the viewer. It's poorly documented, I'll deal with tis once I get some time.

You can see a live demo of tvwidget displaying Bininda-Emonds et al.'s mammal supertree published in Nature (doi:10.1038/nature05634). The tree is the first one in Supplementary Figure 1.

From PDFs to Google Earth

I've added a service to bioGUID that takes a PDF and attempts to extract latitude and longitude data from the PDF, returning those co-ordinates in either a Google Earth KML file, or in JSON format. This is one of a bunch of services that I'm adding to bioGUID to support some of the data mining that I'm doing.

To see what it can do, try this URL to get a list of localities in the paper Description of eight new species of shrub frogs (Ranidae: Rhacophorinae: Philautus) from Sri Lanka.

Then try this one to get the KML file, and open it in Google Earth. The service uses a bunch of regular expressions to try and extract latitude and longitude pairs from the text (needless to say, there are nearly as many different ways to write a latitude and longitude as there are authors).

The ultimate aim is to assemble a bunch of Open Access PDFs (say, from Zootaxa), run them through this service, then display the result on Google Earth. Think of it as a geography of taxonomy.

Oh, and the irony of me criticising GBIF for displaying poor quality data, then adding to this by providing a service to extract yet more co-ordinates of possibly doubtful validity has not entirely escaped me...

More GBIF errors, courtesy of FishBase

Resurrecting iSpecies after moving it to a new folder on one of my servers, and browsing popular searches, I keep coming across clearly erroneous distributions. FishBase seems a major culprit. For example, the common pandora Pagellus erythrinus is a marine fish, yet GBIF displays numerous occurrences in mainland Africa (dots with black centre on map below).

What gives? Well, after struggling with the somewhat non-intuitive GBIF web site I found that the erroneous records are from FishBase. As for the frog example I blogged about earlier, the actual records have locality information indicating most of the records come from the Mediterranean, but the latitude and longitudes are reversed. Swapping these, the records show a more believable distribution (white dots on SVG map below). If you don't see the map, use a decent web browser such as Safari 3 or Firefox 2. If you must use Internet Explorer, grab the RENESIS player.





I know I've harped on about this before, but surely the time is ripe for some clever data cleaning? Especially if users start to loose their trust in GBIF.

Catalogue of Life as a treemap

I have an "on again/off again" relationship with treemaps. Lately, I've been taking another look, partly inspired by Björn Engdahl's MSc thesis Ordered and Unordered Treemap Algorithms and Their Applications on Handheld Devices. He describes a simple treemap algorithm which he calls Split Layout. It has the nice properties of having a good aspect ratio (most cells in the treemap are approximately square) and it keeps the cells in roughly the original order. This later property is important as one thing I find distracting with tree diagrams is if the order of the objects in the tree keep changing.

I also have an "on again/off again" relationship with the Catalogue of Life, which is potentially very useful, but seems determined to undermine this with some poor design decisions. But, I finally bit the bullet and extracted a complete classification from the 2008 edition of the Catalogue of Life. I downloaded an ISO image, burnt a CD, installed it on a Windows box (gack), grabbed the MySQL database files, and put those on my MacBook Air. Using some tools I developed for working with the NCBI taxonomy, I wanted to extract the tree from the taxa table, only to discover that this table isn't a tree. Not all the taxa in the table are flagged is_accepted_name, and if you remove those, then the remaining taxa don't form a tree. It's clear that some taxa have been orphaned when the table was created. For example, Enteromorpha flexuosa is not an accepted name, and is flagged as such in the taxa table, yet it is has four child taxa that are accepted (Enteromorpha flexuosa subsp. linziformis, Enteromorpha flexuosa subsp. biflagellata, Enteromorpha flexuosa subsp. pilifera, and Enteromorpha flexuosa forma submarina). These taxa are orphaned in the tree. Eventually I gave up trying to extract the tree using SQL, and had to traverse the entire structure starting at the root node. This extracts a tree, at the cost of the orphans. It appears that Catalogue of Life haven't checked whether there classification is, in fact, a tree (OK, technically it is a forest as it is a set of disjoint trees comprising the eight kingdoms CoL recognises, but I make it a tree by rooting it on a node called "life").

After much anguish, I have a tree. I then coded up Engdahl's algorithm, based on the pseudocode he provides on p. 31 of his thesis (I think there's a bug in his code as he doesn't deal with the case when the cell being partitioned is narrower than it is wide, but this was easy to fix). One thing I was keen to do is just use HTML, no SVG or Flash. Here's an example of the treemap, showing the eight kingdoms. Each taxon is drawn proportional to log₁₀(n + 1), where n is the number of terminal taxa (i.e., species or below) in that taxon (the number of terminals is shown in each cell). The log scale was chosen to avoid mega-diverse groups crowding out the smaller taxa.

Animalia 892,966

Archaea 281

Bacteria 9,588

Chromista 6,855

Fungi 33,017

Plantae 206,843

Protozoa 6,435

Viruses 1,906

The live version is here. It's a bit crude (to go back up the tree just use your browser back button), but it's simple, and it's HTML. The underlying code is PHP, but it would be quite easy to convert this to Javascript to make a simple drop in widget. In addition to Björn Engdahl's algorithm, and the Catalogue of Life data, I should acknowledge Samson's code for generating colour gradients.

There are all sorts of things that could be done to improve this. One approach would be to include exemplar pictures of the taxa in each cell, to help navigate in unfamiliar taxa. Denise Green and Rebecca Shapley's Teaching with a visual tree of life report has some examples of this idea (see their p. 86), and Marcos Weskamp (author of the very cool newsmap) has done a mockup for EOL using Flash.

As to the treemap idea itself, there are some fun things which could be done with it. I'm not convinced that it is great for navigation. However, it is probably very useful for showing changes over time. For example, imagine making the State of Observed Species report dynamic. Take the uBio RSS feed for new names, classify the new names, then colour the treemap cells by the number of new names (in a sense, this is a taxonomic version of newsmap).

Stained Glass

Something a little different, my dad's work features in the Winter 2008 issue of Art News New Zealand by Rob Garrett, who has a copy of the article on his web site. Dad designed eight stained glass windows for Westlake Boys High School in Auckland, New Zealand.
Rob Garrett describes them thus:

The challenge when designing stained glass windows as a commemoration of 50 years of a high school is tough, no matter how open the brief. There is no unifying faith; no character-driven narrative; and no beginning, middle and end in the dramatic sense. There is only bewildering complexity; layer upon layer of possibility. [Dugald] Page has tackled this complexity head on by establishing unifying strands that weave through all eight panels: prismatic colour, seasonal change and the metaphor of metamorphosis. Stitched into these strands is a palimpsest of iconic symbols of science and technology, sport, the Pacific, discovery, historic events, literature and the arts.

They are gorgeous to look at (the picture below shows them before they were mounted in the school hall).

When DOIs collide and then disappear: when is a unique, resolvable identifier a bad idea?

As much as I like the idea of a globally unique, resolvable identifier, my recent experience with JSTOR is making me wonder.

JSTOR has three identifiers for articles it archives, DOIs, SICIs, and stable URLs (the later being introduced with the new platform released April 4, 2008). Previously JSTOR would publish DOIs for many of its articles. However, not all of these work, and many are now embedded in the HTML (say, in Dublin Core meta elements) but not publicly displayed.

I suspect the issue is the moving wall:

Journals in JSTOR have "moving walls" that define the time lag between the most current issue published and the content available in JSTOR. The majority of journals in the archive have moving walls of between 3 and 5 years, but publishers may elect walls anywhere from zero to 10 years.

Now, imagine that a publisher has an article on its web site, complete with a DOI, and that article is then add to JSTOR, but is still displayed on the publisher's site.


To make this concrete, consider the article by Baum et al. . On the InformaWorld site this is displayed with doi:10.1080/106351598260879. The same article is also in JSTOR, with the URL http://www.jstor.org/pss/2585367. No DOI is displayed on the page, but if you look at the HTML source, we find:
<meta name="dc.Identifier" scheme="doi" content="10.2307/2585367">. The DOI prefix 10.2307 is used for all JSTOR DOIs, and some for Systematic Biology still work, e.g. 10.2307/2413524.

Now, what happens when the JSTOR moving wall overlaps with publisher's material? What happens if a publisher digitises back issues, then assigns them DOIs? Do the JSOR DOIs then die (as some of them seem to have already done)? And what happens to the poor sap like me, who has been linking to JSTOR DOIs in the naive belief that DOIs don't die?

Suddenly separating identity from resolution is starting to look very attractive...

QOTD

Setting all these reservations and biases aside, the total number of living organisms that have received Latin binomial names is currently around 1.5 million or so. Amazingly, there is as yet no centralized computer index of these recorded species. It says a lot about intellectual fashions, and about our values, that we have a computerized catalog entry, along with many details, for each of several million books in the Library of Congress but no such catalog for the living species we share our world with. Such a catalog, with appropriately coded information about the habitat, geographical distribution, and characteristic abundance of the species in question (no matter how rough or impressionistic), would cost orders of magnitude less money than sequencing the human genome; I do not believe such a project is orders of magnitude less important. Without such a factual catalog, it is hard to unravel the pattems and processes that determine the biotic diversity of our planet.

--Robert M. May, 1988, "How many species are there on Earth? doi:10.1126/science.241.4872.1441

Not much has changed in twenty years...

BioOne (and/or CrossRef) sucks

<rant>
BioOne sucks. Really, really, sucks. I have lost count of the number of times they break DOIs. These are supposed to be the gold standard globally unique identifier, and BioOne continually buggers them. For example, take this URL:

http://www.bioone.org/perlserv/?request=get-abstract&doi=10.1600/02-14.1.

Note the doi=10.1600/02-14.1 bit at the end. If we go to the web page, we see this DOI displayed at the bottom of the page. Yet, when we resolve the DOI, we get the dreaded DOI Not Found error.

This.should.not.happen.

What is BioOne doing!? Now, it is possible that there's a problem with CrossRef, because Googling this paper I found it also lives on Ingenta with, wait for it, another DOI (doi:10.1600/036364404772973960).

This.should.not.happen.

BioOne and Ingenta are hosting the same paper, with different DOIs, only one of which is working. Will somebody please bang some heads together and sort this out!
</rant>

iPhylo on Google Code

Partly inspired by Pedro Beltra's post Open Science project on domain family expansion about using Google Code as a project management system, I've started to populate the iPhylo project. At this stage I'm uploading some scripts for parsing and extracting bibliographic records, and adding wiki pages describing how this is done, discussing different bibliographic identifiers, etc. The aim is to slowly document the background to all the harvesting and linking that I'm working on. Hence, the Google Code project will have documentation and data, not just code. The code for the web site won't go in for a while yet, it needs massive cleaning and tidying up.

TAXACOM indexed by MarkMail

MarkMail is a great tool for searching mail archives. Although focussing on software development projects, they are open to requests, so last week I asked if they could index TAXACOM. My pitch was that TAXACOM is a long running list full of interesting conversations, has been the subject of scholarly study (Christine Hine's book I mentioned earlier), and is topical given interest in biodiversity and the Encyclopedia of Life.

They've done so, and the result is http://taxacom.markmail.org/ . It's just fabulous. For example, here are some things you can do. Being terribly egocentric, I looked at my own posts:
http://taxacom.markmail.org/search/?q=from:"Roderic+Page".

Realising that there are other people in the world, I queried for posts about GBIF:
http://taxacom.markmail.org/search/?q=gbif.

A broader theme might be databases, or the taxonomic impediment. Below is the chart of messages over time for the query "databases". You can "swipe" the mouse across the chart to select messages from a given time span.



I worry that I may end up spending more time playing with this than I should, but it's a neat tool. Hats off to Jason Hunter of MarkMail for adding TAXACOM so promptly.

JavaScript Information Visualization Toolkit

I've just discovered Nicolas Garcia Belmonte's JavaScript Information Visualization Toolkit (JIT). Wow! This is very cool stuff (and no Flash). To quote from the web site:

The JIT is an advanced JavaScript infovis toolkit based on 5 papers about different information visualization techniques.
The JIT implements advanced features of information visualization like Treemaps (with the slice and dice and squarified methods), an adapted visualization of trees based on the Spacetree, a focus+context technique to plot Hyperbolic Trees, and a radial layout of trees with advanced animations (RGraph).

Nicolas also links to a talk by Tamara Munzner, which I've embedded below to remind myself to watch it.

Open Access logo - help

Trivial as this may seem, I'm trying to find out who designed this "Open Access" logo, and whether there are some original files for it. I've seen this logo (or variations on it) on the PLoS web site, the open access publisher Hindawi Publishing, and the Mac OS X program Papers uses it.

It's driving me nuts that I can't find the original. Other widely used logos typically have a site where a designer or organisation provides a bunch of versions in different formats, such as the Creative Commons symbols, the ubiquitous RSS feed icon, and other projects such as the Geotag icon. It's sometimes desirable to have different formats of an icon, and ideally have a vector-based version (e.g., in EPS or SVG) format that can be used to create images at different resolutions, and these projects provide these files.

Apart from the interesting fact that there doesn't seem to be a standard logo or symbol for Open Access, does anybody know where this logo came from?

Fixing GBIF

The more I play with GBIF the more I come across some spectacular errors. Here's one small example of what can go wrong, and how easy it would be to fix at least some of the errors in GBIF. This is topical given that the recent review of EOL highlighted the importance of vetting and cleaning data.

The frog Boophis periegetes features in a recent study of DNA barcoding (doi:10.1186/1742-9994-2-5). The sequences from this study (AY848605-9) aren't georeferenced in GenBank, but in iPhylo they are courtesy of Metacarta's web services. The sequences are located in Madagascar.

Finding errors

Curious about the frog I did a search in iSpecies and got the following map:


Oops, the frog is found in the middle of the South Atlantic(!), and in Brazil(!?).
These specimen records are provided by the MCZ, Harvard. Looking at the latitude and longitude co-ordinates, it's clear that there has been a comedy of errors. In the case of MCZ A-119852 the longitude is west instead of east, for MCZ A-119850 and MCZ A-119851 the latitude and longitudes have been swapped, and the longitude is west instead of east (again). If we make these changes, the specimens go back to Madagascar (the rectangle on the SVG map below). If you don't see the map, use a decent web browser such as Safari 3 or Firefox 2. If you must use Internet Explorer, grab the RENESIS player.





Interestingly the DiGIR records all list the country as Madagascar, so for any specimen in GBIF it would be trivial to test whether:

1. do the co-ordinates for the specimen fall inside the bounding box for the country?
2. if not, will they if we change sign (i.e., hemispheres) and/or swap latitude and longitude?

These would be trivial things to do, and would probably catch a lot of the more egregious errors in GBIF.

Fixing errors
What will be interesting is whether these records will be fixed. I have sent feedback via GBIF's web site, as well as sending an email to the MCZ. I'll let readers know what happens.

Ground truth

Lastly, those interested in the frog itself may find the iSpecies search frustrating as the link returned by Google Scholar leads to a page in Ingenta saying:

This title is now published by Blackwell Publishing and can be found here www.ingentaconnect.com/content/bsc/zoj

Nope, the paper in question is actually at ScienceDirect (doi:10.1006/zjls.1995.0040). This paper describes the species, and gives the latitude and longitude of the collection localities (correctly).

iPhylo Demo

I started this blog with the goal of documenting my own efforts to make a database of evolutionary trees, based on ideas sketched in hdl:10.1038/npre.2007.1028.1. I've felt that the major task is link phylogenies to other information, such as taxon names, specimens, localities, images, publications, etc. That is, to embed trees in a broader context. Discovering how to engage with that broader context led to a bunch of experiments, toys, and diversions:

1. iSpecies, a toy to aggregate information on a species.
2. Semant, experiments with RDF and triple stores (AKA the Semantic Web).
3. bioGUID, an attempt to make identifiers resolvable, with an increasing focus on developing an OpenURL resolver for biodiversity literature.

iSpecies and bioGUID are still operational, but the ant work fell victim to server crashes, and a growing frustration with the limitations of triple stores. Blogs for all three projects document their histories: iSpecies, Semant, and bioGUID. In a sense, these blogs document the steps along the way to iPhylo.

Based on this experience, I started again with what I've previously referred to as a database of everything. The first public demo is online at iphylo.org/~rpage/demo1. It's very crude, but may give a sense of what I'm trying to do.

The goal of iPhylo is to treat biodiversity objects as equal citizens. Each object has a unique identifier, associated metadata, and is linked to other objects (for example, a specimen is linked to sequences, sequences are linked to publications, etc.). By following the links it is possible to generate new views on existing information, such as a map for study that doesn't have any maps. For example, below is a map generated for Brady et al. (doi:10.1073/pnas.0605858103), based on links between sequences and specimens (if you can't see the map you need a SVG-capable web browser, such as Safari 3 or Firefox 2).

Ironically there are no phylogenies yet. At this stage I'm trying to link the bits together.

How does it work?
More on this later. Briefly, iPhylo uses a entity-attribute-value model database to store objects and their relationships. Like bioGUID, iPhylo relies on a suite of web services (most external, some I've developed locally) to locate and resolve identifiers. iPhylo resolves identifiers for PubMed records, GenBank sequences, museum specimens, publications, etc. and adds the associated metadata to a local database. Wherever possible it resolves any links in the metadata (e.g., if a GenBank record mentions a specimen, iPhylo will try and retrieve information on that specimen). When you view an object in iPhylo, these links are displayed. iPhylo will also try and convert bibliographic records to identifiers (such as DOIs) if no identifiers are provided, and also extracts georeferences for specimens and sequences, either from original records or by using a georeferencing service. Taxonomic names are resolved using uBio, and are treated as "tags."

At present iPhylo is being populated by various scripts, there is no facility for users to add data. This is something I will add in the future.

Getting the data
One of the biggest challenges is getting data (or, to be more precise, figuring out how to harvest available data). iPhylo builds on code for bioGUID. I've also been exploring bulk harvesting data sources. Sometimes this is easy. Many sequences in Genbank are linked to records in PubMed, so if you know the Pubmed id for a paper, you can harvest the sequences. For example, even though the Bulletin of the American Museum of Natural History isn't indexed in PubMed, it is possible to retrieve all the sequences GenBank records as being from papers published in the Bulletin. You can retrieve this list in XML form by clicking here.


Why?

There are all sorts of things which could be done with this. For example, by linking objects together we can also track the provenance of data, and ultimately build "citation networks" of specimens, sequences, etc. For background see my paper on "Biodiversity informatics: the challenge of linking data and the role of shared identifiers" (doi:10.1093/bib/bbn022, preprint at hdl:10101/npre.2008.1760.1).

As mentioned above, we can generate maps even if the original study didn't include one (by following the links). Given that we can geotag studies, this opens up the possibility to query studies spatially. For example, this study on bats and this study on rodents deal with taxa with very similar distributions. A spatial query could find these easily. Imagine interested in, say, Madagascar, and being able to find phylogenetic studies , even if the title and abstract of the paper don't mention Madagascar by name.

There also potential to clean data. One of the first studies I uploaded is Grant et al.'s study of dart-poison frogs. The map for this study shows a outlying point in California:

This point is MVZ 199828, which is a specimen of the salamander Aneides flavipunctatus. In GenBank, MVZ 199828 is listed as the voucher for seven sequences from the frog Mannophryne trinitatis. Oops. A quick iSpecies search, and a click on the GBIF map reveals that there is a specimen MVZ 199838 of Mannophryne trinitatis. i suspect that this is the true voucher for these sequences, and the GenBank records contain a typo.

Future
This is all still very, very crude. The demo is slow, the queries aren't particularly clever, and I've probably gone overboard on using Javascript to populate the web pages. The real value isn't in the web pages, but the links between the data objects. This is my main focus -- extracting and adding links. For now the data is displayed but you can't edit it. However, this is coming. Very basic RDF and RSS feeds are available for each object, and fans of microformats will find some goodies, and sociologists of science may find some of the coauthorship graphs intriguing

Colossal squid

The dissection of the colossal squid (Mesonychoteuthis hamiltoni) specimen from Antarctica has been getting a lot of coverage. Pangs of homesickness, especially seeing Steve O'Shea enthusing about the beast. Steve was a contemporary at Auckland Uni when I was a student. I remember him being deeply disappointed in me because I moved away from doing alpha taxonomy of crustaceans (describing taxa such as Pinnotheres atrinicola, right) to fussing with cladistics and computers. Looking at Steve on YouTube, I think it's clear who's having more fun. Maybe I should have stuck to taxonomy after all...

EOL Review

Last month I was at the MBL in Woods Hole, taking part in the review of the Biodiversity Informatics Group. BIG is responsible for the EOL web site. I chair the Informatics Advisory Group, which provides advice to BIG, and it was our task to produce an evaluation of where things stood. I've written a post on the Encyclopaedia of Life blog about some of the big challenges facing EOL as it moves into its second year.

Paper published

Bit of a rarity these days. My paper on identifiers in biodiversity informatics, which I mentioned earlier when I deposited the preprint at Nature Precedings, has been published in Briefings in Bioinformatics (doi:10.1093/bib/bbn022).

Here's the abstract:

A major challenge facing biodiversity informatics is integrating data stored in widely distributed databases. Initial efforts have relied on taxonomic names as the shared identifier linking records in different databases. However, taxonomic names have limitations as identifiers, being neither stable nor globally unique, and the pace of molecular taxonomic and phylogenetic research means that a lot of information in public sequence databases is not linked to formal taxonomic names. This review explores the use of other identifiers, such as specimen codes and GenBank accession numbers, to link otherwise disconnected facts in different databases. The structure of these links can also be exploited using the PageRank algorithm to rank the results of searches on biodiversity databases. The key to rich integration is a commitment to deploy and reuse globally unique, shared identifiers [such as Digital Object Identifiers (DOIs) and Life Science Identifiers (LSIDs)], and the implementation of services that link those identifiers.

Google Code wiki using Subversion

For some time now Google Code has been displaying the message:

The web interface for wiki content is currently READ-ONLY for maintenance.
You may still add comments, and members may add, edit, or delete wiki pages via svn. Learn more.

This is a bit of a pain as I've recently put the code for my LSID tester into Google Code (the project is here). Since having a simple wiki is part of the attraction of Google Code, I decided to finally figure out how to add a wiki via Subversion. Turns out it is pretty straight forward. I created a folder called "wiki" and added a file with some wiki markup. I then added it to the repository

svn import -m "Trying to add wiki"
 wiki https://lsid-php.googlecode.com/svn/wiki/ 
--username USERNAME

(do this from the folder containing "wiki", not within the "wiki" folder itself). This adds the contents of the wiki folder to the Google Code repository. You can then check this out:

svn checkout
https://lsid-php.googlecode.com/svn/wiki/ 
lsid-php-wiki --username USERNAME

This probably seems obvious to many, but I'm used to CVS, having run a CVS repository since the late 1990's when Mike Charleston and I were working on TreeMap. I've been resisting moving to Subversion simply because of the hassle of learning stuff that doesn't actually make my life any easier. That said, Google Code is a nice way to host projects.

Biodiversity informatics: the challenge of linking data and the role of shared identifiers

The manuscript for Briefings in Bioinformatics that I alluded to earlier has been accepted for publication. I've put a preprint up at Nature Preceding (hdl:10101/npre.2008.1760.1). The final version will appear in print later this year.