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iPhylo

Rants, raves (and occasionally considered opinions) on phyloinformatics, taxonomy, and biodiversity informatics. For more ranty and less considered opinions, see my Twitter feed.ISSN 2051-8188. Written content on this site is licensed under a Creative Commons Attribution 4.0 International license.
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These are simply notes to myself about taxonomic classifications in Wikidata. Classifications in Wikidata can be complex and are often not trees. For example, if we trace the parents of the frog family Leptodactylidae back we get a graph like this: Each oval represents a taxon in Wikidata, and each arrow connects a taxon to its parent(s) in Wikidata.

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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.

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A quick note to myself to document a problem with the GBIF classification of liverworts (I've created issue POR-1879 for this).While building a new tool to browse GBIF data I ran into a problem that the taxon "Jungermanniales" popped up in two different places in the GBIF classification, which broke a graphical display widget I was using.If you search GBIF for Jungermanniales you get two results, both listed as "accepted":Based on Wikipedia

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Continuing the theme of the failings of the GBIF classification I've been playing further with cluster maps to visualise the problem (see this earlier post for an introduction).Browsing through bats in GBIF I keep finding the same species appearing more than once, albeit in different genera.

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Wikipedia is wonderful, but parts of it are horribly broken. Take, for example, taxonomic classifications. A classification is a rooted tree, which means that each node in the tree has a single parent. We can store trees in databases in a variety of ways. For example, for each node we could store a list of its children, or we could store the single unique parent of each node. Ideally we'd choose to store one or other, but not both.

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Following on from my previous post about visualising the mammalian classification in Wikipedia, I've extracted the largest component from the graph for all mammal taxa in Wikipedia, and it is a tree. This wasn't apparent in the previous diagram, where the component appeared as a big ball due to the layout algorithm used.