University of Glasgow

Roderic Page

> Text mining for museum specimen identifiers
> [\#TDM](https://twitter.com/hashtag/TDM?src=hash)
> <http://t.co/BsFXSAZJpK> cc [@rdmpage](https://twitter.com/rdmpage)
> [@robgural](https://twitter.com/robgural) thoughts?
>
> --- Ross Mounce (@rmounce) [May 19,
> 2015](https://twitter.com/rmounce/status/600588364933419008)

![Class EMuMedia
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width="200" height="133" style="float:right;"}This post is a response to
Ross Mounce\'s post [Text mining for museum specimen
identifiers](http://rossmounce.co.uk/2015/05/19/text-mining-for-museum-specimen-identifiers/).
As Ross notes in that post, mining literature for specimen codes is
something I\'ve been interested in for a while (search for [specimen
codes](http://iphylo.blogspot.co.uk/search?q=specimen+codes) on iPhylo),
and [@Aime Rankin](https://twitter.com/aimerankin%22) (formerly an
undergraduate student at Glasgow) did some [work on this as
well](http://figshare.com/authors/Aime_Rankin/434982). It\'s great to
see progress in this area.

Here are some thoughts on Ross\'s post (I\'m posting here rather than as
a comment on Ross\'s blog because this is going to be long).

### What questions to ask?

Obviously there\'s a lot of scope for metrics, such as numbers of
citations for individual specimens, and league tables for collections
(see [GBIF specimens in BioStor: who are the top ten museums with
citable
specimens?](http://iphylo.blogspot.com/2012/02/gbif-specimens-in-biostor-who-are-top.html)).
As Ross notes, there\'s also scope for updating out of date museum
metadata with information from the literature (e.g., [Linking data from
the NHM portal with content in
BHL](http://iphylo.blogspot.com/2014/12/linking-data-from-nhm-portal-with.html)),
but even more interesting is the potential to cross-link databases in a
way that permits novel queries. For example, if we have a paper on a
disease that includes data we can link to a georeferenced specimen, then
we can enable spatial queries for diseases (e.g., [BHL and GBIF as
biomedical
databases](http://iphylo.blogspot.com/2012/03/bhl-and-gbif-as-biomedical-databases.html)).

### Materials for mining

From my perspective the obvious corpus to mine is the [Biodiversity
Heritage Library (BHL)](http://biodiverstylibrary.org). Ross repeats the
erroneous view that BHL is just \"legacy\" literature. Apart from the
obvious point that everything not published right not is, by definition,
legacy, BHL has a lot of modern content (including papers published in
the last couple of years).

Furthermore, there are journals that cite Natural History Museum
specimens, including \"in house\" journals (e.g., [*Bulletin of the
British Museum (Natural History)
Zoology*](http://biostor.org/issn/0007-1498) and [*Bulletin of the
Natural History Museum. Zoology
series*](http://biostor.org/issn/0968-0470)), as well as the [Bulletin
of the British Ornithologists\' Club](http://biostor.org/issn/0007-1595)
which has published lots of new bird names for which the type specimen
is often in the NHM.

I guess one issue is accessibility. Ross notes that:

> The PMC OA subset is fantastic & really facilitates this kind of
> research -- I wish ALL of the biodiversity literature was aggregated
> like (some) of the open access biomedical literature is. You can
> literally just download a million papers, click, and go do your
> research. It facilitates rigorous research by allowing full machine
> access to full texts.

So, how we can make BHL content as accessible? For each article I\'ve
extracted from BHL and stored in BioStor you can get full text by simply
appending \".text\" to the BioStor URL, but this isn\'t quite the same
as grabbing a big dump of text.

The other source of mining is GenBank, which has a lot of sequences that
have NHM vouchers, but also a weird and wonderful array of ways of
recording those specimens. This is one reason I\'m building [\"Material
examined\"](http://bionames.org/~rpage/material-examined/), to cope with
these codes. For example sequence
[KF281084](http://www.ncbi.nlm.nih.gov/nuccore/KF281084) has voucher
\"TRING 1877111743\" which more traditionally would be written as \"BMNH
1877.11.17.43\", which is \"NHMUK 1877.11.17.43\" in the NHM database.
This is just one example of the horrors of matching specimen codes (for
more see the code for [Material
examined](https://github.com/rdmpage/material-examined)).

One reason GenBank is useful is that the sequences are often linked to
the literature, which means you get to make the link between specimen
and literature without actually needing to mine the text itself (handy
if access is problematic).

### Bonus question: How should I publish this annotation data?

> But if I wanted to publish something a little better & a little more
> formal, what kind of RDF vocabulary can I use to describe "occurs in"
> or "is mentioned in". What would be the most useful format to publish
> this data in so that it can be re-used and extended to become part of
> the biodiversity knowledge graph and have lasting value?

Personally I\'d avoid RDF because that way lies madness (or at least
endless detours haggling about ontologies).

But making the output useful is an important question. Despite the fact
that it is a bit clunky, I suspect Darwin Core Archives are the way to
go. The core data is a CSV table, so it\'s easy to generate, and also
easy to use. Lets say you analysed a particular corpus (e.g., PLoS ONE),
you could then output the data in Darwin Core (making sure both specimen
and publication had stable identifiers), then package it up and upload
to Zenodo or Figshare and get a DOI. For bonus points, it would be great
to see this data on GBIF, but this would require (a) mapping NHM
specimen codes to GBIF ids (the NHM has this), and (b) GBIF being able
to recognise that the data you\'re adding is not new specimens but
rather annotations of existing specimens.

### Things to think about

Here are a couple of additional things to think about.

#### Specimen finding as a service

In the same way that we have taxonomic name-finding services, it would
be great if we had a specimen code-finding service. I have code that I
use in BioStor, but it would be great to have something that is robust,
stable, and generalisable across multiple specimen codes. My tool
[Material examined](http://bionames.org/~rpage/material-examined/)
focusses on parsing a single string rather than parsing a block of text,
but adding that functionality is an obvious thing to do.

#### Markup as output

One concern I have with work that involves mining text is that we hardly
ever store the intermediate step of text + located elements. Instead we
get to see sumamry output (e.g., this page has these three scientific
names, and these 10 specimen codes). As Terry Catapano
([@catapanoth](https://twitter.com/catapanoth)) once wisely pointed out
\"indexing is markup\", in that if you find a substring in some text,
you have in effect marked up the text. Can we preserved the marked up
text so that we go back and look at it and improve our text mining
methods, or make that markup available to others to build upon it? There
are all sorts of things which could be built upon this information, for
example, imaging if the results where given to BHL so that people could
search by specimen code.


This post is a response to Ross Mounce's post Text mining for museum specimen identifiers. As Ross notes in that post, mining literature for specimen codes is something I've been interested in for a while (search for specimen codes on iPhylo), and @Aime Rankin (formerly an undergraduate student at Glasgow) did some work on this as well. It's great to see progress in this area.

Rogue Scholar Beiträge

Text mining for museum specimen identifiers