University of Glasgow

Roderic Page

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhBaMrDj0KRPFPHmjSBYzffLbJZhA711GGekWPbiRqzSpSYLvBdef7OLwDrPaarFrxMHrBEQP5iiM_u3hF_AdNODs5whiO0i5cJmoQx3NWDcWUroU9OGF9o99BMcOIkIoCTETHH/s200/Rf7UoXTw_400x400.jpg){border="0"
width="128" original-height="240"
original-width="240"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhBaMrDj0KRPFPHmjSBYzffLbJZhA711GGekWPbiRqzSpSYLvBdef7OLwDrPaarFrxMHrBEQP5iiM_u3hF_AdNODs5whiO0i5cJmoQx3NWDcWUroU9OGF9o99BMcOIkIoCTETHH/s240/Rf7UoXTw_400x400.jpg){style="display: block; padding: 1em 0; text-align: center; clear: right; float: right;"}
:::

The [Plazi](http://plazi.org) project has become one of the major
contributors to GBIF with some 36,000 datasets yielding some 500,000
occurrences (see [Plazi\'s GBIF
page](https://www.gbif.org/publisher/7ce8aef0-9e92-11dc-8738-b8a03c50a862)
for details). These occurrences are extracted from taxonomic publication
using automated methods. New data is published almost daily (see [latest
treatments](https://tb.plazi.org/GgServer/static/newToday.html)). The
map below shows the geographic distribution of material citations
provided to GBIF by Plazi, which gives you a sense of the size of the
dataset.

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbzyO3NVCA0r2-2bkxUBCZdA9iuZZATf_mlqYDy6CCZjO4NTSEQMC8txdCLGGo_Ynz7ISTEGVLuPJDX3Rx8ZOh1vDZVzseKKa6OsvPsc2qoirL_tGwF4i0JJEWR5Uhyphenhyphen8b1R4Ey/s400/Screenshot+2021-10-24+at+20.43.23.png){border="0"
width="400" original-height="514"
original-width="1030"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbzyO3NVCA0r2-2bkxUBCZdA9iuZZATf_mlqYDy6CCZjO4NTSEQMC8txdCLGGo_Ynz7ISTEGVLuPJDX3Rx8ZOh1vDZVzseKKa6OsvPsc2qoirL_tGwF4i0JJEWR5Uhyphenhyphen8b1R4Ey/s1030/Screenshot+2021-10-24+at+20.43.23.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

By any metric Plazi represents a considerable achievement. But often
when I browse individual records on Plazi I find records that seem
clearly incorrect. Text mining the literature is a challenging problem,
but at the moment Plazi seems something of a \"black box\". PDFs go in,
the content is mined, and data comes up to be displayed on the Plazi web
site and uploaded to GBIF. Nowhere does there seem to be an evaluation
of how accurate this text mining actually is. Anecdotally it seems to
work well in some cases, but in others it produces what can only be
described as bogus records.

## Finding errors

A treatment in Plazi is a block of text (and sometimes illustrations)
that refers to a single taxon. Often that text will include a
description of the taxon, and list one or more specimens that have been
examined. These lists of specimens (\"material citations\") are one of
the key bits of information that Plaza extracts from a treatment as
these citations get fed into GBIF as occurrences.

To help explore treatments I\'ve constructed a simple web site that
takes the Plazi identifier for a treatment and displays that treatment
with the material citations highlighted. For example, for the Plazi
treatment
[03B5A943FFBB6F02FE27EC94FABEEAE7](https://tb.plazi.org/GgServer/html/03B5A943FFBB6F02FE27EC94FABEEAE7)
you can view the marked up version at
<https://plazi-tester.herokuapp.com/?uri=622F7788-F0A4-449D-814A-5B49CD20B228>.
Below is an example of a material citation with its component parts
tagged:

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjinptnav7_CNmsrnCzCArizBz19_srW3AyQ8LL5b5PHqFw-m3zjXDDqxd4PMCacnTQ2xyJh61Wo_0omEbwQ5AGJRsHteeqa7-btTty4QGcVsdTVp0CpOxZrw7hFkpwBGWN_lea/s400/Screenshot+2021-10-24+at+20.59.56.png){border="0"
width="400" original-height="94"
original-width="693"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjinptnav7_CNmsrnCzCArizBz19_srW3AyQ8LL5b5PHqFw-m3zjXDDqxd4PMCacnTQ2xyJh61Wo_0omEbwQ5AGJRsHteeqa7-btTty4QGcVsdTVp0CpOxZrw7hFkpwBGWN_lea/s693/Screenshot+2021-10-24+at+20.59.56.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

This is an example where Plazi has successfully parsed the specimen. But
I keep coming across cases where specimens have not been parsed
correctly, resulting in issues such as single specimens being split into
multiple records (e.g.,
<https://plazi-tester.herokuapp.com/?uri=5244B05EFFC8E20F7BC32056C178F496>),
geographical coordinates being misinterpreted (e.g.,
<https://plazi-tester.herokuapp.com/?uri=0D228E6AFFC2FFEFFF4DE8118C4EE6B9>),
or collector\'s initials being confused with codes for natural history
collections (e.g.,
<https://plazi-tester.herokuapp.com/?uri=252C87918B362C05FF20F8C5BFCB3D4E>).

Parsing specimens is a hard problem so it\'s not unexpected to find
errors. But they do seem common enough to be easily found, which raises
the question of just what percentage of these material citations are
correct? How much of the data Plazi feeds to GBIF is correct? How would
we know?

## Systemic problems

Some of the errors I\'ve found concern the interpretation of the parsed
data. For example, it is striking that despite including marine taxa
**no** Plazi record has a value for depth below sea level (see [GBIF
search on depth range 0-9999 for
Plazi](https://www.gbif.org/occurrence/map?depth=0,9999&publishing_org=7ce8aef0-9e92-11dc-8738-b8a03c50a862&advanced=1)).
But [many records do have an
elevation](https://www.gbif.org/occurrence/map?elevation=0,9999&publishing_org=7ce8aef0-9e92-11dc-8738-b8a03c50a862&advanced=1),
including records from marine environments. Any record that has a depth
value is interpreted by Plazi as being elevation, so we have aerial
crustacea and fish.

### Map of Plazi records with depth 0-9999m

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnYHyMsNeElQaa-WjfVe6PHQfPx5O4sbAt6Spxn2Cp8FPPK50JbuKCg0o188uAg8ryVM_aZtYvBSl1tpAdAn25yIvmSh97wf1fxa6nb4C9ijNy_hOTtvK3k1aA3HbWJ6xpSma2/s320/Screenshot+2021-10-25+at+12.03.51.png){border="0"
width="400" original-height="258"
original-width="673"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnYHyMsNeElQaa-WjfVe6PHQfPx5O4sbAt6Spxn2Cp8FPPK50JbuKCg0o188uAg8ryVM_aZtYvBSl1tpAdAn25yIvmSh97wf1fxa6nb4C9ijNy_hOTtvK3k1aA3HbWJ6xpSma2/s673/Screenshot+2021-10-25+at+12.03.51.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

### Map of Plazi records with elevation 0-9999m

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4kucSwi2YxsVsjDboeeZM6Nyy9W0REaqnXEsqgdk2tn_oqzMflKMzqpWnXJCwXvpKD1EOhhtN4CA9B20dJFcMycFpQQJGSlRD-BaWQMv6hApysjFWHkReaaeqYnvwrG0-yjQi/s320/Screenshot+2021-10-25+at+12.04.06.png){border="0"
width="400" original-height="256"
original-width="675"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4kucSwi2YxsVsjDboeeZM6Nyy9W0REaqnXEsqgdk2tn_oqzMflKMzqpWnXJCwXvpKD1EOhhtN4CA9B20dJFcMycFpQQJGSlRD-BaWQMv6hApysjFWHkReaaeqYnvwrG0-yjQi/s675/Screenshot+2021-10-25+at+12.04.06.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

Anecdotally I\'ve also noticed that Plazi seems to do well on zoological
data, especially journals like *Zootaxa*, but it often struggles with
botanical specimens. Botanists tend to cite specimens rather differently
to zoologists (botanists emphasise collector numbers rather than
specimen codes). Hence data quality in Plazi is likely to taxonomic
biased.

Plazi is [using GitHub to track issues with
treatments](https://github.com/plazi/community/issues) so feedback on
erroneous records is possible, but this seems inadequate to the task.
There are tens of thousands of data sets, with more being released
daily, and hundreds of thousands of occurrences, and relying on GitHub
issues devolves the responsibility for error checking onto the data
users. I don\'t have a measure of how many records in Plazi have
problems, but because I suspect it is a significant fraction because for
any given day\'s output I can typically find errors.

## What to do?

Faced with a process that generates noisy data there are several of
things we could do:

1.  Have tools to detect and flag errors made in generating the data.
2.  Have the data generator give estimates the confidence of its
    results.
3.  Improve the data generator.

I think a comparison with the problem of parsing bibliographic
references might be instructive here. There is a long history of people
developing tools to parse references ([I\'ve even had a
go](https://iphylo.blogspot.com/2021/05/finding-citations-of-specimens.html)).
State-of-the art tools such as [AnyStyle](https://anystyle.io) feature
machine learning, and are tested against [human curated
datasets](https://github.com/inukshuk/anystyle/blob/master/res/parser/core.xml)
of tagged bibliographic records. This means we can evaluate the
performance of a method (how well does it retrieve the same results as
human experts?) and also improve the method by expanding the corpus of
training data. Some of these tools can provide a measures of how
confident they are when classifying a string as, say, a person\'s name,
which means we could flag potential issues for anyone wanting to use
that record.

We don\'t have equivalent tools for parsing specimens in the literature,
and hence have no easy way to quantify how good existing methods are,
nor do we have a public corpus of material citations that we can use as
training data. I [blogged about
this](https://iphylo.blogspot.com/2021/05/finding-citations-of-specimens.html)
a few months ago and was considering using Plazi as a source of marked
up specimen data to use for training. However based on what I\'ve looked
at so far Plazi\'s data would need to be carefully scrutinised before it
could be used as training data.

Going forward, I think it would be desirable to have a set of records
that can be used to benchmark specimen parsers, and ideally have the
parsers themselves available as web services so that anyone can evaluate
them. Even better would be a way to contribute to the training data so
that these tools improve over time.

Plazi\'s data extraction tools are mostly desktop-based, that is, you
need to download software to use their methods. However, there are
experimental web services available as well. I\'ve created a simple
wrapper around the material citation parser, you can try it at
<https://plazi-tester.herokuapp.com/parser.php>. It takes a single
material citation and returns a version with elements such as specimen
code and collector name tagged in different colours.

## Summary

Text mining the taxonomic literature is clearly a gold mine of data, but
at the same time it is potentially fraught as we try and extract
structured data from semi-structured text. Plazi has demonstrated that
it is possible to extract a lot of data from the literature, but at the
same time the quality of that data seems highly variable. Even minor
issues in parsing text can have big implications for data quality (e.g.,
marine organisms apparently living above sea level). Historically in
biodiversity informatics we have favoured data quantity over data
quality. Quantity has an obvious metric, and has milestones we can
celebrate (e.g., [one billion
specimens](GBIF%20at%201%20billion%20-%20what's%20next?)). There aren\'t
really any equivalent metrics for data quality.

Adding new types of data can sometimes initially result in a new set of
quality issues (e.g., [GBIF metagenomics and
metacrap](https://iphylo.blogspot.com/2019/12/gbif-metagenomics-and-metacrap.html))
that take time to resolve. In the case of Plazi, I think it would be
worthwhile to quantify just how many records have errors, and develop
benchmarks that we can use to test methods for extracting specimen data
from text. If we don\'t do this then there will remain uncertainty as to
how much trust we can place in data mined from the taxonomic literature.

## Update

Plazi has responded, see [Liberating material citations as a first step
to more better
data](http://plazi.org/posts/2021/10/liberation-first-step-toward-quality/).
My reading of their repsonse is that it essentially just reiterates
Plazi\'s approach and doesn\'t tackle the underlying issue: their method
for extracting material citations is error prone, and many of those
errors end up in GBIF.


The Plazi project has become one of the major contributors to GBIF with some 36,000 datasets yielding some 500,000 occurrences (see Plazi's GBIF page for details). These occurrences are extracted from taxonomic publication using automated methods.

Problems with Plazi parsing: how reliable are automated methods for extracting specimens from the literature?

If you compare the impact that BHL and Plazi have on GBIF, then it\'s
clear that BHL is almost invisible. Plazi has successfully in carved out
a niche where they generate [tens of thousands of
datasets](https://www.gbif.org/participant/369) from text mining the
taxonomic literature, whereas BHL is a [participant in name
only](https://www.gbif.org/participant/366). It\'s not as if BHL lacks
geographic data. I recently added back a [map display in
BioStor](https://biostor.org/map.php) where each dot is a pair of
latitude and longitude coordinates mentioned in an article derived from
BHL\'s scans.

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilUuMsEej0kWdyvORIKwZsROOM_QsV3rIDukixea4kNfz56rQtVpE-gytw3c5DtujGWH8dQ751X9XnKDzV-KoZIN_KaiQ3AhKwfukLMX0p-XgBlOCKAELw2P8tEwrhe1MH8DHP/s320/Screenshot+2021-06-04+at+12.48.15.png){border="0"
width="320" original-height="591"
original-width="622"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilUuMsEej0kWdyvORIKwZsROOM_QsV3rIDukixea4kNfz56rQtVpE-gytw3c5DtujGWH8dQ751X9XnKDzV-KoZIN_KaiQ3AhKwfukLMX0p-XgBlOCKAELw2P8tEwrhe1MH8DHP/s622/Screenshot+2021-06-04+at+12.48.15.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

This data has the potential to fill in gaps in our knowledge of species
distributions. For example, the Atlas of Living Australia (ALA) shows
the following map for the cladoceran (water flea)
[*Simocephalus*](https://bie.ala.org.au/species/urn:lsid:biodiversity.org.au:afd.taxon:7e12338f-57f0-4648-8338-59d766da4b7b):

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYDEEThyphenhyphenl3lwkXk5q7P7Ax6mhyphenhyphen-7qOCjOs_DYA3PnetwdHCA011Nwz10u0TpSSGyxHUL_IKwQRCoXzN_POaF7gjEmLjbmQ4Mc3a3GeXZG_AHABBD99gIud-eyyKiN6Pfs3VEYM/s320/Screenshot+2021-06-04+at+12.47.06.png){border="0"
height="320" original-height="591"
original-width="556"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYDEEThyphenhyphenl3lwkXk5q7P7Ax6mhyphenhyphen-7qOCjOs_DYA3PnetwdHCA011Nwz10u0TpSSGyxHUL_IKwQRCoXzN_POaF7gjEmLjbmQ4Mc3a3GeXZG_AHABBD99gIud-eyyKiN6Pfs3VEYM/s591/Screenshot+2021-06-04+at+12.47.06.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

Compare this to the localities mentioned in just one paper on this
genus:

> Timms, B. V. (1989). Simocephalus Schoedler (Cladocera: Daphniidae) in
> tropical Australia. The Beagle, 6, 89--96. Retrieved from
> <https://biostor.org/reference/241776>

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEigxNa6wJs5DdK_F9omOzLfBXVg2fpzKoFzV2yVaFURPrPoDSxlKeTTLtPEup5El_FvBnORgRK7WZaWsGHwravqOqN89pdkqaJGSgi8O6T17yvDwX5iH6g62Rqlc5BS0oyeUkjq/s320/Screenshot+2021-06-04+at+12.47.24.png){border="0"
width="320" original-height="584"
original-width="735"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEigxNa6wJs5DdK_F9omOzLfBXVg2fpzKoFzV2yVaFURPrPoDSxlKeTTLtPEup5El_FvBnORgRK7WZaWsGHwravqOqN89pdkqaJGSgi8O6T17yvDwX5iH6g62Rqlc5BS0oyeUkjq/s735/Screenshot+2021-06-04+at+12.47.24.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

There are records in this paper for species that currently have no
records at all in ALA (e.g., [*Simocephalus
serrulatus*](https://bie.ala.org.au/species/urn:lsid:biodiversity.org.au:afd.taxon:1b919df7-20aa-4a9b-8e97-e193074b9884#classification)):

::: {.separator style="clear: both;"}
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxRnTxS7Zo4ZKsZcDLPnRtc3HNZNC4IgG3wZLZjOpUKOgiYkgg-esVPFzQfxmjzM-2ITMTsDwDurWXrI7CVBoq4HXua2XjAL3js4VT_BW2gJo8HPvuBQPTy4TIK9mCnSjCJsSQ/s320/Screenshot+2021-06-04+at+12.47.44.png){border="0"
height="320" original-height="714"
original-width="481"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxRnTxS7Zo4ZKsZcDLPnRtc3HNZNC4IgG3wZLZjOpUKOgiYkgg-esVPFzQfxmjzM-2ITMTsDwDurWXrI7CVBoq4HXua2XjAL3js4VT_BW2gJo8HPvuBQPTy4TIK9mCnSjCJsSQ/s714/Screenshot+2021-06-04+at+12.47.44.png){style="display: block; padding: 1em 0; text-align: center; "}
:::

As it stands BioStor simply extracts localities, it doesn\'t extract the
full \"material citation\" from the text (that is, the specimen code,
date collected, locality, etc. for each occurrence). If it did, it would
then be in a position to contribute a large amount of data to ALA and
GBIF (and elsewhere). Not only that, if it followed the Plazi model this
contribution would be measurable (for example, in terms of numbers of
records added, and numbers of data citations). Plazi makes some of its
parsing tools available as web services (e.g.,
<http://tb.plazi.org/GgWS/wss/test> and
<https://github.com/gsautter/goldengate-webservices>), so in principle
we could parse BHL content and extract data in a form usable by ALA and
GBIF.

## Notes on Plazi web service

The endpoint is http://tb.plazi.org/GgWS/wss/invokeFunction and it
accepts POST requests, e.g.
data=Namibia%3A%2058%20km%20W%20of%20Kamanjab%20Rest%20Camp%20on%20road%20to%20Grootberg%20Pass%20%2819%C2%B038%2757%22S%2C%2014%C2%B024%2733%22E%29&functionName=GeoCoordinateTaggerNormalizing.webService&dataUrl=&dataFormat=TXT
and returns XML.


If you compare the impact that BHL and Plazi have on GBIF, then it's clear that BHL is almost invisible. Plazi has successfully in carved out a niche where they generate tens of thousands of datasets from text mining the taxonomic literature, whereas BHL is a participant in name only. It's not as if BHL lacks geographic data.

Thoughts on BHL, ALA, GBIF, and Plazi

On Friday I discovered that [BHL](http://biodiversitylibrary.org) has
started issuing CrossRef DOIs for articles, starting with the journal
*Revue Suisse de Zoologie*. The metadata for these articles comes from
[BioStor](http://biostor.org/issn/0035-418X). After a WTF and WWIC
moment, I tweeted about this, and something of a Twitter storm (and
email storm) ensued:

> .[@BioDivLibrary](https://twitter.com/BioDivLibrary) WTF?! When did
> [\#bhlib](https://twitter.com/hashtag/bhlib?src=hash) start minting
> DOIs for articles (\"parts\") e.g. <http://t.co/xm9xYS62cr> +1, but a
> little heads up maybe
>
> --- Roderic Page (@rdmpage) [September 11,
> 2015](https://twitter.com/rdmpage/status/642382857332256768)

To be clear, I\'m very happy that BHL is finally assigning article-level
DOIs, and that it is doing this via CrossRef. Readers of this blog may
recall an [earlier
discussion](http://iphylo.blogspot.com/2014/05/dois-are-not-enough.html)
about the relative merits of different types of DOIs, especially in the
context of identifiers for articles. The bulk of the academic literature
has DOIs issued by [CrossRef](http://www.crossref.org), and these come
with lots of nice services that make them a joy to use if you are a data
aggregator, like me. There are other DOI registration agencies minting
DOIs for articles, such as [Airiti
Library](http://www.airitilibrary.com/) in Taiwan (e.g.,
[doi:10.6165/tai.1998.43(2).150](http://dx.doi.org/10.6165/tai.1998.43(2).150))
and [ISTIC (中文DOI)](http://www.doi.org.cn/) in China (e.g.,
[doi:10.3969/j.issn.1000-7083.2014.05.020](http://dx.doi.org/10.3969/j.issn.1000-7083.2014.05.020))
(pro tip, if you want to find out the registration agency for a DOI,
simply append it to http://doi.crossref.org/doiRA/, e.g.
[http://doi.crossref.org/doiRA/10.6165/tai.1998.43(2).150](http://doi.crossref.org/doiRA/10.6165/tai.1998.43(2).150){target="_new"}).
These provide stable identifiers, but not the services needed to match
existing bibliographic data to the corresponding DOI (as I discovered to
my cost while [working with
IPNI](https://github.com/rdmpage/ipni-names)).

However, now things get a little messy. From 2015 PDFs for *Revue Suisse
de Zoologie* are being uploaded to [Zenodo](http://zenodo.org), and are
getting DataCite DOIs there (e.g.,
[doi:10.5281/zenodo.30012](http://dx.doi.org/10.5281/zenodo.30012)).
This means that the most recent articles for this journal will not have
CrossRef DOIs. From my perspective, this is a disappointing move. It
removes the journal from the CrossRef ecosystem at a time when the
uptake of CrossRef DOIs for taxonomic journals is at an all time high
(both *ZooKeys* and *Zootaxa* have CrossRef DOIs), and now BHL is
starting to issue CrossRef DOIs for the \"legacy\" literature (bear in
mind that \"legacy\" in this context can mean articles published last
year).

I\'ve rehearsed the reasons why I think [CrossRef DOIs are best
elsewhere](http://iphylo.blogspot.com/2014/05/dois-are-not-enough.html),
but the keys points are that articles are much easier to discover (e.g.,
using <http://search.crossref.org>), and are automatically first class
citizens of the academic literature. However, not everybody buys these
arguments.

Maybe a way forward is to treat the two types of DOI as identifying two
different things. The CrossRef DOI identifies the article, not a
particular representation. The Zenodo DOI (or any DataCite DOI) for a
PDF identifies that representation (i.e., the PDF), not the article.

![Having CrossRef and Zenodo DataCite DOIs
coexist](https://lh3.googleusercontent.com/--90fUYzvDAQ/VfqWQMkIwrI/AAAAAAAAECs/9HHdeUM-F9c/Having%252520CrossRef%252520and%252520Zenodo%252520%252528DataCite%252529%252520DOIs%252520coexist.png?imgmax=800 "Having CrossRef and Zenodo (DataCite) DOIs coexist.png"){style="display:block; margin-left:auto; margin-right:auto;"
border="0" width="460" height="345"}

This would enable CrossRef and Zenod DOIs to coexist, providing we can
(a) have some way of describing the relationship between the two kinds
of DOI (e.g., CrossRef DOI - hasRepresentation -\> Zenodo DOI).

This would give freedom to those who want the biodiversity literature to
be part of the wider CrossRef community to mint CrossRef DOIs to do so.
It gives those articles the benefits that come with CrossRef DOIs
(findability, being included in lists of literature cited, citation
statistics, customer support when DOIs break, altmetrics, etc.)

It would also enable those who want to ensure stable access to the
contents of the biodiversity literature to use archives such as Zenodo,
and have the benefits of those DOIs (stability, altmetrics, free file
storage and free DOIs).

Having multiple DOIs for the same thing is, I\'d argue, at the very
least, unhelpful. But if we tease apart the notion of what we are
identifying, maybe they can coexist. Otherwise I think we are in danger
of making choices that, while they seem locally optimal (e.g., free
storage and minting of DOIs), may in the long run cause problems and run
counter to the goal of making the taxonomic literature has findable as
the wider literature.


On Friday I discovered that BHL has started issuing CrossRef DOIs for articles, starting with the journal
<i>
 Revue Suisse de Zoologie
</i>
. The metadata for these articles comes from BioStor. After a WTF and WWIC moment, I tweeted about this, and something of a Twitter storm (and email storm) ensued:    To be clear, I'm very happy that BHL is finally assigning article-level DOIs, and that it is doing this via CrossRef.

Messages de Rogue Scholar

Problems with Plazi parsing: how reliable are automated methods for extracting specimens from the literature?

Thoughts on BHL, ALA, GBIF, and Plazi

On having multiple DOI registration agencies for the same journal