GBIF is running its Ebbe Nielsen Challenge for the third successive year. This year the title is Liberating species records from open data repositories for scientific discovery and reuse. To quote from the Challenge background on Devpost: In essence, the 2017 Challenge is to develop tools to discover these biodiversity-relevant datasets, and make them available to GBIF.

Yes, this post is indeed an attempt to fit as many buzzwords that I don't really understand into the title. I've been playing around with Glitch, which is a delightful project from Fog Creek (makers of Trello and co-creators of Stack Overflow). On first glance Glitch looks weirdly retro, and it took a little while for me to get the hang of things. Bit it's fun and very powerful.

For my own use more than anything else I've started creating a list of Wikidata SPARQL queries here. I personally don't find Wikidata's data model particularly easy to grasp, so one way to learn is to take the example queries on the Wikidata Query site and mess about with them. For those interested in taxonomic data Wikidata is quite rich in content.

Last week I was at WikiCite 2017, a fascinating three day event in Vienna. Wikicite is "a proposal to build a bibliographic database in Wikidata to serve all Wikimedia projects", and is attracting increasing attention from academics, librarians, publishers, data geeks, and others. You can get a sense of the project by following @WikiCite on Twitter.

Following on from earlier posts exploring how to map DNA barcodes and putting barcodes into GBIF it's time to think about taking advantage of what makes barcodes different from typical occurrence data. At present GBIF displays data as dots on a map (as do I in http://iphylo.org/~rpage/bold-map/). But barcodes come with a lot more information than that.

In preparation for WikiCite 2017 I'm looking more closely at extracting bibliographic information from Wikispecies. The WikiCite project "is a proposal to build a bibliographic database in Wikidata to serve all Wikimedia projects". One reason for doing this is so that each factual statement in WikiData can be linked to evidence for that statement.

At present BioStor provides a simple display of an article extracted from BHL. You get the page images, and sometimes a map and an altmetric "donut". But we can do better than this. For example, I'm starting to experiment with displaying a list of literature cited by the article.

Following on from previous posts The Semantic Web made fun: d3sparql and The Biodiversity Heritage Library meets Wikidata via Wikispecies: adding author identifiers to BioStor I've put together an example query that can be used to extract a taxonomic classification from Wikidata.

I've added an experimental feature to BioStor that uses data from Wikidata and Wikispecies to augment what information BioStor displays on authors.

Given a big corpus of literature one of the fun things to do is look at how the use of a term has changed over time. When did people first use a particular word? When did one word start to replace another, etc.? Google's Ngram Viewer is perhaps the best known tool for exploring these questions.

Following on from adding DNA barcodes to GBIF I've now uploaded a taxonomic classification of DNA barcode BINs (Barcode Index Numbers). Each BIN is a cluster of similar DNA barcodes that is essentially equivalent to a species.