GBIF and impact: CrossRef, FundRef, and Altmetric

For anyone doing research or involved in scientific infrastructure, demonstrating the "impact" of those activities is becoming increasingly important. This has fostered a growth industry in "alt metrics", tools to track how research gathers attention outside academia (of course, we can argue whether attention is the same as impact).

For an organisation such as GBIF there's a clear need to show that it has impact on the field of biodiversity (and beyond), especially to its funders (which are ultimately national governments). To do this GBIF needs to track how its data is used by the research communities, both to do science and to inform policy. This is hard to do, especially if there's a limited culture of data citation. It occurs to me that another way to tackle this problem is to invert it by looking not at the impact of GBIF, but at GBIF as a source of impact.

For a moment let's replace GBIF with Wikipedia. We can ask "what is the impact of Wikipedia on the research community?" For example, Wikipedia is the 8th largest referrer of DOIs, which means that Wikipedia is a major source traffic to academic publishing sites. All those Wikipedia pages which cite the primary literature are driving traffic to those articles.

Conversely, if we regard Wikipedia as important we can use citations of articles in Wikipedia pages as a measure of a researcher's impact. For example, according to Impact story I am "Wikitastic" as 11 Wikipedia pages cite articles that I am an author of (authorship is discovered by using my ORCID 0000-0002-7101-9767).

Likewise, altmetric tracks citations on Wikipedia, so that a paper like the one below may have minimal social media impact but as the gray donut rings signifying that it's been cited on Wikipedia.

JENKINS, P. D., & ROBINSON, M. F. (2002, June). Another variation on the gymnure theme: description of a new species of Hylomys (Lipotyphla, Erinaceidae, Galericinae). Bulletin of The Natural History Museum. Zoology Series. Cambridge University Press (CUP) doi:10.1017/S0968047002000018

Hence, we can look at Wikipedia in two different ways. The first is to ask "what is the impact of Wikipedia?", the second is to assume that Wikipedia has impact, and then use that as one measure of the impact of researchers (how "Wikitastic" you are).

So, let's go back to GBIF. Imagine we leave aside the question of whether GBIF has impact and imagine that we can use GBIF as a measure of impact ("GBIFtastic", sorry, that was unforgivable).

Example 1: From DOI to FundRef to GBIF

In a previous post I discussed the lack of mosquito data in GBIF and how I plugged this gap by using open data cite by a paper in eLife. This paper has the DOI 10.7554/elife.08347 and if I plug that into CrossRef's search engine I can get back some information on the funders of that paper:

Research funded by Sir Richard Southwood Graduate Scholarship | Rhodes Scholarships | National Institutes of Health (RAPIDD program, R01-AI069341, R01-AI091980, R01-GM08322, N01-A1-25489) | Wellcome Trust (#095066, Vecnet, #099872) | National Aeronautics and Space Administration (#NNX15AF36G) | Biotechnology and Biological Sciences Research Council | Bill and Melinda Gates Foundation (#OPP1053338, #OPP52250) | Studienstiftung des Deutschen Volkes | Directorate-General for Research and Innovation (#21803) | European Centre for Disease Prevention and Control (ECDC/09/018)

Now, this gives me a connection between funding agencies, a paper they funded, and the data in GBIF. For example, the Bill and Melinda Gates Foundation (doi:10.13039/100000865) funded doi:10.7554/elife.08347 which generated data in GBIF doi:10.15468/7apj8n.

I suspect that the Bill and Melinda Gates Foundation don't know that they've funded data gathering that has ended up in GBIF, but I suspect they'd be interested. Especially if that could be quantified (een better if we can demonstrate reuse). The process of linking funders to data can be largely automated, especially as more and more papers are now automatically linked to funder information. The link between publications and data in GBIF can be harder to establish, but at least one publisher (Pensoft) has establish a direct feed from publication to GBIF.

So, what if GBIF could computationally discover the funders of the data it holds, and could then communicate that to the funders. I think there's scope here for funders to take an interest in GBIF and it's role in expanding the reuse (and hence impact) of data that funders have paid for. Demonstrating to governments that national funding agencies are supporting research that generates data that ends up in GBIF may help make the case that GBIF is worth supporting.

Example 2: GBIF as altmetric source

The little altmetric donuts that we see on papers require sources of data, such as Twitter, Wikipedia, blogs, etc. For example, the Plant List dataset I recently put into GBIF has a DOI (doi:10.15468/btkum2)and this has received some attention so it has a altimetric donut (wouldn't it be nice if GBIF showed these on dataset pages?):

What if GBIF itself became a source that altimetric scanned when measuring impact? What if having your papers mentioned in GBIF (for example, as a source of distributional data or a taxonomic name) contributed to the visible impact of that work. Wouldn't that encourage people to mobilise their data? Wouldn't that help people discover the wider conversation about the data and associated publications? Wouldn't that help generate more impact for papers that might otherwise gather less attention?

Summary

I realise that I've somewhat avoided the question of the impact of GBIF itself, which is something that also needs to be tackled (and this is one reason why GBIF assigns DOIs to datasets and downloads to support data citation), but I think that may be only a part of the bigger picture. If we assume GBIF is impactful to start with, then I think we can start to think how GBIF can help persuade researchers and funders that contributing to GBIF is a good thing.

Altmetrics, Disqus, GBIF, JSTOR, and annotating biodiversity data

Browsing JSTOR's Global Plants database I was struck by the number of comments people have made on individual plant specimens. For example, for the Holotype of Scorodoxylum hartwegianum Nees (K000534285) there is a comment from Håkan Wittzell that the "Collection number should read 1269 according to Plantae Hartwegianae". In JSTOR the collection number is 1209.

Now, many (if not all) of these specimens will also be in GBIF. Indeed, K000534285 is in GBIF as http://www.gbif.org/occurrence/912442645, also with collection number 1209. A GBIF user will have no idea that there is some doubt about one item of metadata about this specimen.

So, an obvious thing to do would be to make the link between the JSTOR and GBIF records. Implementing this would need so fussing because (sigh) unlike DOIs for articles we don't have agreed upon identifiers for specimens. So we'd need to do some mapping between the specimen barcode K000534285, the JSTOR URL http://plants.jstor.org/stable/10.5555/al.ap.specimen.k000534285, and the GBIF record http://www.gbif.org/occurrence/912442645.

In addition to providing users with more information, it might also be useful in kickstarting annotation on the GBIF site. At the moment GBIF has no mechanism for annotating data, and if it did, then it would have to start from scratch. Imagine that a person visiting occurrence 912442645 sees that it has already attracted attention elsewhere (e.g., JSTOR). They might be encouraged to take part in that conversation (because at least one person cared enough to comment already). Likewise, we could feed annotations on the GBIF site to JSTOR.

A variation on this idea is to think of annotations such as those in the JSTOR database as being analogous to the tweets, blog posts, and bookmarking that altmetric tracks for academic papers. Imagine if we applied the same logic to GBIF and had a way to show users that a specimen has been commented on in JSTOR Plants? Thinking further down the track, we could image adding other sorts of "attention", such as citations by papers, vouchers for DNA sequences, etc.

It would be a fun project to see whether the Disqus API enabled us to create a tool that could match JSTOR Global Plants comments to GBIF occurrences.