University of Glasgow

Roderic Page

![Screen_shot_2010-08-30_at_22.37.31.png](http://lh4.ggpht.com/_Gct8lVAxKqQ/TH0CspAEenI/AAAAAAAAAv0/Ydc-15rt4u4/Screen_shot_2010-08-30_at_22.37.31.png?imgmax=800){border="0"
width="132" height="132" style="float:right;"}[Dario
Taraborelli](http://nitens.org/taraborelli) has released
[ReaderMeter](http://readermeter.org/), an elegant app built on top of
the Mendeley API. You enter an author\'s name and it summarises that
authorship\'s readership in Mendeley. The app provides some summary
statistics ([mine are shown
below](http://readermeter.org/Page.Roderic%20D%20M)), and if you click
on the horizontal bar corresponding to a paper, you can see a
visualisation of who is reading your paper, including a nice map.  
  

::: {style="text-align:center"}
![meter.png](http://lh4.ggpht.com/_Gct8lVAxKqQ/TH0CtUAFklI/AAAAAAAAAv4/oxJ8pCYQoEE/meter.png?imgmax=800){border="0"
width="400"}
:::

  
As ever with author names, there are issues of people\'s name having
more than one spelling. In Mendeley I\'m known as Roderic D. M. Page, R.
D. M. Page, Rod Page, Roderic Page, Roderic D. M. Page, and doubtless
some others. Searching ReaderMeter using different spellings of my name
gives different results. There are various approaches to tackling this
problem, I\'ve touched on one approach
[earlier](http://iphylo.blogspot.com/2009/01/equivalent-author-names.html).  
  
However, there\'s a different way to tackle this problem in the context
of apps like ReaderMeter, because if you\'re a Mendeley user you can
assert that you are the author of a paper (these papers live in your
\"My Publications\" collection). Using Mendeley\'s API, an app could
retrieve this list of publications (providing the user gave it access),
and we could compute readership statistics from the set of articles
\"known\" to be authored (leaving aside the issue of people gaming the
system by spuriously claiming authorship). In this way the app relies on
the default behaviour of Mendeley users - uploading and self-identifying
the articles they\'ve written.  
  
Implementing a feature like this posses two problems. The first is
access to a user\'s data. Mendeley\'s API supports OAuth, so it could be
done in such a way that only the account\'s user could authorise the app
to access this list. The app could store the fact that the user has
verified that the list of publications. Think of it as a bit like
Amazon\'s [Real
Name™](http://www.amazon.com/gp/help/customer/display.html?ie=UTF8&nodeId=14279641)
feature.  
  
The other obstacle is Mendeley\'s API, which returns readership
statistics for public documents (i.e., those in the central
aggregation). At present, using the API there is no way to link the
global id for a Mendeley reference (e.g.,
ae7dd6a0-6d09-11df-936c-0026b95e484c) with the local id (e.g.,
3582682802) that reference has in a user\'s collection, unless we resort
to trying to match articles by searching by identifiers or article
titles. If the API exposed these links, apps like
[ReaderMeter](http://readermeter.org/) could become even more powerful
(and personalised).  
  


Dario Taraborelli has released ReaderMeter, an elegant app built on top of the Mendeley API. You enter an author's name and it summarises that authorship's readership in Mendeley. The app provides some summary statistics (mine are shown below), and if you click on the horizontal bar corresponding to a paper, you can see a visualisation of who is reading your paper, including a nice map.

ReaderMeter: what's in a name?

As part of my Quixotic attempt to construct a [wiki of taxonomic
names](http://iphylo.blogspot.com/2009/02/wiki-demo.html), I\'m building
a database of names and links. My current plan is to seed this with the
NCBI taxonomy. What I want to do is flesh out the NCBI taxonomy with
authorities and links to the original literature. At the moment the NCBI
taxonomy is almost \"nude\", lacking links to the literature behind the
names. As the magnificently bearded Geoffrey Bilder notes in an
[interview with Martin
Fenner](http://network.nature.com/people/mfenner/blog/2009/02/17/interview-with-geoffrey-bilder):  

> One way in which researchers assess the trustworthiness of content is
> by determining how it sits within the scholarly record. Does it
> provide evidence for its assertions in citations? Do other people cite
> it?

  
Given how important the NCBI taxonomy is, I think it would be a great
improvement if each name could be linked to the original taxonomic
publication. A first step to this is to find the taxonomic authority,
the name of the author (or authors) of the name.  
  
One potential source is [uBio](http://www.ubio.org), which provides web
services for retrieving information on names. Hence, an obvious approach
is to map NCBI names to uBio names. However, if I use uBio\'s SOAP
service typically I get multiple records for the same name. Some of
these are due to homomyms (e.g., the same name used for a plant and an
animal), but many are the same name with variations on the taxonomic
authority. Much of this variation arises because uBio aggregates
information from a wide range of databases, and each database differs in
who it records the taxonomic authority.  
  
For example, for the name \"Diplura\" (which I\'ve [discussed
earlier](http://iphylo.blogspot.com/2006/11/homonyms-and-ubios-data-model-yet-more.html))
we get these names and authorities:  

- *Diplura* (Greene MS.) Allman 1864
- Diplura Borner, 1904
- *Diplura* C. L. Koch 1850
- *Diplura* G. J. Hollenberg, 1969
- *Diplura* Hollenb.
- *Diplura* Jerdon 1864
- *Diplura* Koch 1850
- *Diplura* Koch 1851
- *Diplura* Rambur 1866
- *Diplura* Simon 1892

Before asking which of these names corresponds to \"Diplura\" in NCBI,
I\'d like to cluster these names into sets by merging names that are
\"the same.\" This resembles the problem of [equivalent author
names](http://iphylo.blogspot.com/2009/01/equivalent-author-names.html).
The approach I\'m using is to build a graph linking taxonomic
authorities that are more similar than some threshold, then finding the
components of that graph. For example, here is the graph for
\"Diplura\":  
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh36C3qRxKaKzAmg5u0COZWAxhk9_lAHm3dAjVNYK_N39bX-X1euHSfTBIW0F2UCKQF4jRZ0C8zbvBDhh9Ao8ow9lK418-KGsicNX8gVYUtadBOneeY1t5B6inRiqpGeGd9lYaL/s320/Diplura.jpg){#BLOGGER_PHOTO_ID_5306364119800896882
style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 320px; height: 275px;"
border="0"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh36C3qRxKaKzAmg5u0COZWAxhk9_lAHm3dAjVNYK_N39bX-X1euHSfTBIW0F2UCKQF4jRZ0C8zbvBDhh9Ao8ow9lK418-KGsicNX8gVYUtadBOneeY1t5B6inRiqpGeGd9lYaL/s1600-h/Diplura.jpg){onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}"}  
The nodes in the graph are the taxonomic authorities, \"cleaned\" by
making all the text lower case, and stripping any punctuation. The edges
are labelled by the length of the [longest common
substring](http://en.wikipedia.org/wiki/Longest_common_substring_problem)
shared by the nodes that edge links (I ignore substrings less than four
characters long). This graph groups the variations on *Diplura* Koch (a
spider), and *Diplura* Hollenberg (a brown alga, see
[doi:10.1111/j.1529-8817.1969.tb02617.x](http://dx.doi.org/10.1111/j.1529-8817.1969.tb02617.x)).  
  
Not surprisingly, perhaps, the linkouts from the NCBI taxonomy for
Diplura are a mess, with the algal genus
([taxon:371965](http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&id=371965&lvl=3&lin=f&keep=1&srchmode=1&unlock)
linking to both plant and animal databases, and the insect class
([taxon:29997](http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&id=29997&lvl=3&lin=f&keep=1&srchmode=1&unlock))
linking to a mix of plants and animals, not all of the animals are
insects.  
  
I\'m still playing with the underlying code, but I might try and build a
web service that returns name clusters (and perhaps the graph as well).


As part of my Quixotic attempt to construct a wiki of taxonomic names, I'm building a database of names and links. My current plan is to seed this with the NCBI taxonomy. What I want to do is flesh out the NCBI taxonomy with authorities and links to the original literature. At the moment the NCBI taxonomy is almost "nude", lacking links to the literature behind the names.

Clustering taxonomic names

One problem I\'ve encountered in building a bibliographic database is
the different ways author names are written. For example, for papers
I\'ve authored my name may be written as \"Roderic D. M. Page\" or \"R.
D. M. Page\". Googling about this problem I came across Dror
Feitelson\'s paper [On identifying name equivalences in digital
libraries](http://informationr.net/ir/9-4/paper192.html). Feitelson
addresses the issue of matching first names:  

> The services provided by digital libraries can be much improved by
> correctly identifying variants of the same name. For example, this
> will allow for better retrieval of all the works by a certain author.
> We focus on variants caused by abbreviations of first names, and show
> that significant achievements are possible by simple lexical analysis
> and comparison of names. This is done in two steps: first a pairwise
> matching of names is performed, and then these are used to find
> cliques of equivalent names. However, these steps can each be
> performed in a variety of ways. We therefore conduct an experimental
> analysis using two real datasets to find which approaches actually
> work well in practice. Interestingly, this depends on the size of the
> repository, as larger repositories may have many more similar names.

Feitelson\'s solution is to construct a graph of similarity between
first names, then find weighted cliques grouping equivalent names. For
example, given the first names \"Ace D. E.\", \"A. D.\", \"Abe F. G.\",
\"Abe Bob C.\", \"A. B. C.\", and \"Abe B\", we create the graph below
where the edges are weighted by similarity between the names:  
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQRoSeNlVSxDf-uJexfZXXlcZl53YGAU7wvTtdtbm3Ejf1tKnk2H5UeYW14Sgb9zDYOiI2-A4JF5kGwGD1esaPmgq72_CeP3HDiUrSqS-QBWFjFwjNmT1XNE7KdX3UbI0X1WMS/s320/match.png){#BLOGGER_PHOTO_ID_5292761636571149074
style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 169px; height: 320px;"
border="0"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQRoSeNlVSxDf-uJexfZXXlcZl53YGAU7wvTtdtbm3Ejf1tKnk2H5UeYW14Sgb9zDYOiI2-A4JF5kGwGD1esaPmgq72_CeP3HDiUrSqS-QBWFjFwjNmT1XNE7KdX3UbI0X1WMS/s1600-h/match.png){onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}"}  
In this example, the names \"Abe Bob C\", \"A B C\", and \"Abe B\" are
equivalent, as are \"Ace D E\" and \"A D\", leaving \"Abe F G\" by
itself.  
  
I\'ve implemented Feitelson\'s weighted clique algorithm in a PHP script
that calls a C++ program that does the clique analysis. Results can be
returned in HTML or JSON. You can try the service at
<http://bioguid.info/services/>. You can also call the service directly
by a HTTP POST request to the URL
<http://bioguid.info/services/equivalent.php> with these parameters:

  

Parameter

Value

Description

  

names

string

List of first names, separated by end of line (\n) character

  

format

*html* or *json*

Format of the results

  


One problem I've encountered in building a bibliographic database is the different ways author names are written. For example, for papers I've authored my name may be written as "Roderic D. M. Page" or "R. D. M. Page". Googling about this problem I came across Dror Feitelson's paper On identifying name equivalences in digital libraries.

Messaggi di Rogue Scholar

ReaderMeter: what's in a name?

Clustering taxonomic names

Equivalent author names