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Tag: Open Citation Corpus

Like a kid with a new train set! Exploring citation networks

As part of the Open Citations Project, Alex Dutton recently completed a graphing plug-in for the Open Citations web site, that permits users to generate different kinds of graphs of citation networks by querying the Open Citation Corpus for a particular article, and either display the network of papers citing that article (input citations), papers cited by that article (output citations), or both.  These can be displayed on screen in the web browser in a variety of layouts, or conveniently downloaded in a number of useful formats.

THIS IS SOOOOO COOL!

Having survived the preparation and posting of the JISC Open Citations Project Final Blog Post last night, minutes before the midnight deadline, I’m now like a kid with a new train set, playing with this display tool and exploring the citation networks present in the Open Citation Corpus, something I have dreamed of doing for two years now.

Remember first that in the Open Citations Corpus we have some 200,000 citing articles – those within the Open Access Subset (OASS) of Pubmed Central – citing ~3.4 million papers out there in the big wide world, which are only recipients of citations.  The consequence of this limited corpus is that the majority of citation chains are of length one – from a paper in the OASS to a paper outside the OASS.  Not very interesting.  Add to this the fact that PubMed Central is new – over 90% of the papers in the Open Access Subset were published in the 21st Century, and 77% of them in the last 5 years.  Thus there are only a very few citation from articles within the OASS to other articles within the OASS.  That means that the maximum length of our citation chains, at present, to three or four on links the input side – a selected article may be cited by a chain of three or four other OASS articles, and three or four on the output side – the selected article may cite other OASS articles in addition to non-OASS articles, and these in turn will cite others.  However, in most cases, the citations chains are much shorter.

simple network
simple networkFigure 1. A simple citation network of input citation chain length of 2 links within the Open Citations Corpus, and an output chain length of 1 link – the selected article (red) receives citations from other OASS articles (green), and itself cites only articles outside the OASS (white).

Let’s start with something familiar – the article in PLoS Neglected Tropical Diseases by Reis et al. (2008) [1] that I used for our semantic publishing exemplar [2].  Its inward citation graph, limited to a citation chain length of two links, created by and copied from the Open Citations Project web site, looks like this:

input citations of Reis
Figure 2. The input citation network of Reis et al. (2008), limited to an citation chain length of 2 links.

I, of course, cited the Reis et al. (2008) paper [1] in our 2009 Adventures paper [3] that we based upon it, and also in my first paper on CiTO in 2010 [3], which also cites the Adventures paper.   Reis et al. (2008) is also cited by Fink et al. (2010) [4], who also cited our Adventures paper, and by Bourhy et al. (2010) [5], another PLoS Neglected Tropical Diseases paper in the OASS, which in turn is cited by Galloway and Levett (2010) [6], while our Adventures paper is also cited by Gerner and Nenadic (2010) [7].

The following image shows this graph as it was originally created within the Open Citations web page:

Input citations of Reis in web page
Figure 3. The same input citation network of Reis et al. (2008), as shown in the Open Citations web site.

Since Reis et al. (2008) has a reference list containing 52 references, its output citation graph is much more complex, even when limited to a citation chain length of 2, since several of its cited papers are also members of the Open Access Subset.  The following figure shows the whole output citation network a citation chain length of 2, which is too demagnified to be legible.

Citations by Reis
Figure 4. The outward citation network of Reis et al. (2008), limited to a citation chain length of 2 links.

The next figure shows a close-up of part of the previous diagram – the output citation network of Reis et al. (2008), again showing the Reis et al. (2008) paper in red, and one of the key papers it cites, Maciel et al. (2010) [8], a slightly earlier paper from the same research group, forming a second key node in the top right of the diagram.

Cited by Reis closeup
Figure 5. A close-up of a central portion of the outward citation network of Reis et al. (2008), limited to a citation chain length of 2 links.

Clearly, there is lots of information that can be extracted from these graphs, particularly when we display them in a tool like GraphViz that permits interactions with the data.  While the Open Citations web site simply displays such citation graphs created using one of several layout algorithms selected by the user, the raw data can also be downloaded in a variety of formats including GraphViz, GraphML and SVG, while the resulting network images can be downloaded in as PNG, JPEG and PDF images, and the underlying RDF metadata can be downloaded as RDF/XML. N-triples, Notation3 and Turtle.

Having used our new Open Citations web site and its network display interface for a short while, I am already aware of many shortcomings and limitations that we will attempt to improve upon in the next few days.  However, we would very much like to hear from you – as a user of the Open Citations web site – both to learn what you like about what we have done and to hear what you find to be shortcomings of the functionality and new features that you would like to see implemented, which we will record as user stories to input into our next round of development.  These can either be recorded as comments on this blog post, or can be e-mailed with the subject line “Open Citations web site” either to me <david.shotton@zoo.ox.ac.uk> or to Alex Dutton <Alexander.dutton@zoo.ox.ac.uk>, who is the person who deserves all the credit for the present system.  We look forward to hearing from you.

[1]  Reis RB, Ribeiro GS, Felzemburgh RDM, Santana FS, Mohr S, Melendez SXTO, Queiroz A, Santos AC, Ravines RR, Tassinari WS, Carvalho MS, Reis MG, Ko AI (2008). Impact of environment and social gradient on Leptospira infection in urban slums. PLoS Negl Trop Dis 2(4): e228. doi:10.1371/journal.pntd.0000228.

[2] Shotton D, Portwin K, Klyne G, Miles A (2009). Adventures in semantic publishing: exemplar semantic enhancements of a research article. PLoS Comput Biol 5:e1000361. doi:10.1371/journal.pcbi.1000361.

[3] Shotton D (2010). CiTO, the Citation Typing Ontology. Journal of Biomedical Semantics  1 (Suppl. 1): S6. doi:10.1186/2041-1480-1-S1-S6.

[4]  Fink JL, Fernicola P, Chandran R, Parastatidis S, Wade A, Naim O, Quinn GB, Bourne PE (2010). Word add-in for ontology recognition: semantic enrichment of scientific literature.  BMC Bioinformatics 11:103. doi:10.1186/1471-2105-11-103.

[5]  Bourhy P, Collet L, Clément S, Huerre M, Ave P, Giry C, Pettinelli F, Picardeau M (2010). Isolation and Characterization of New Leptospira Genotypes from Patients in Mayotte (Indian Ocean). PLoS Negl Trop Dis 4(6): e724. doi:10.1371/journal.pntd.0000724.

[6]  Galloway RL, Levett PN (2010) Application and Validation of PFGE for Serovar Identification of Leptospira Clinical Isolates. PLoS Negl Trop Dis 4(9): e824. doi:10.1371/journal.pntd.0000824.

[7]  Gerner M, Nenadic G (2010). LINNAEUS: A species name identification system for biomedical literature. BMC Bioinformatics 11:85. doi:10.1186/1471-2105-11-85.

[8]  Maciel EAP, Carvalho ALF, Nascimento SF, Matos RB, Gouveia EL, Reis MG, Ko AI (2008). Household transmission of Leptospira infection in urban slum communities. PLoS Negl Trop Dis 2: e154. doi:10.1371/journal.pntd.0000154.

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JISC Open Citations Project – Final Project Blog Post

Executive summary

Introduction

To general readers of this blog, this post will appear different from normal posts. Rather than being about a particular topic, it pulls together a summary of the work undertaken over the past year within the Open Citations Project supported by the JISC, and is primarily intended to assist JISC evaluation of the project and its outputs. Details of the work undertaken and the outputs from this project have mostly been described in previous blog posts, to which this post will frequently refer.

Project scope and purpose

The Open Citations Project is global in scope, designed to change the face of scientific publishing and scholarly communication. Specifically, it aims to make it possible to publish bibliographic information in RDF and to make citation links as easy to traverse as Web links.

Project aims

To achieve this goal, we have had four primary aims:

  • To create a semantic infrastructure that makes possible the description of citations, references and bibliographic entities in RDF, since we found existing ontologies inadequate for our purpose.
  • To extend that semantic infrastructure to handle data citations and data entities, as well as bibliographic citations and bibliographic entities, mindful of Philip Bourne’s prediction that soon there will be no meaningful difference between a journal article and a database entry.
  • To provide exemplars of how these ontologies can be applied to real-world data, by creating mappings from existing encodings to RDF, and by creating
    RDF metadata relating to bibliographic and data entities and their citations.
  • To convert the reference lists within all the PMC Open Access subset articles to RDF, and their publication as open linked data that third parties can use in novel ways.

Principle deliverables and outputs

  • The SPAR (Semantic Publishing and Referencing) Ontologies.
  • Graffoo and LODE, two novel tools for ontology visualization and documentation.
  • Mappings of various existing metadata schemes to RDF using SPAR.
  • Development of data citation methods and protocols
  • The Open Citations Blog in which activities and outputs are described.
  • The Open Citations Corpus of bibliographic citation data encoded in RDF and published as Open Linked Data.
  • The OpenCitations.net web site, to provide user access to the Open Citations Corpus.
  •     The Open Citations Project softwareused for processing the Pubmed Central Open Access corpus into Open Linked Data.The net result is open citation data from life science journal articles available on the web, for utilization by academics, for citation network analysis applications, and for tracking the impact of research grant funding.

Primary beneficiaries

  • Scholars worldwide, particularly in the biomedical sciences, by providing better access to bibliographic and citation data.
  • Academic publishers and repository managers, by providing a semantic infrastructure and tools to enable their outputs and holdings to join the semantic web of open linked data.

Background

In 2008, Katie Portwin and I had an enjoyable summer ‘souping up’ a PLoS Neglected Tropical Diseases article by Reis et al. (2008) [1] that I had downloaded as an XML file from the journal web site in late April, one week after it had been published. The resulting enhanced publication, available here, became an exemplar of what is possible in the realm of semantic publishing, while undertaking that work was very influential in shaping the course of my more recent activities.

One of the things we undertook was to mark up the reference list with annotations that clarified the nature of the cited entity (e.g. book, journal article, medical report) and the reason the authors had cited those entities (used data from, obtained background from, extended, etc.) – annotation that we took care to verify with the authors themselves before publishing them!

While we undertook that work manually, it quickly became apparent that what we needed was an ontology from which a controlled vocabulary of such terms could be used to create both human- and machine-readable metadata describing the citations and the cited entities. We therefore developed a draft ontology that we subsequently split to form the basis of the first two ontologies of the suite of SPAR (Semantic Publishing and Referencing) Ontologies described elsewhere on this blog, namely CiTO, the Citation Typing Ontology to describe the relationships between the citing and cited entities, and FaBiO, the FRBR-aligned Bibliographic Ontology, to describe the cited entities themselves.

Using these tools, we were able to mark up the reference list from Reis et al., and publish it as RDF.

From there it was but a small step to dream of the day when the references from all biomedical research articles would be published as open linked data, and to think what we could do to make that dream a reality.

And it was obvious where to start – with the Open Access subset of journal articles available in PubMed Central (PMC), all nicely marked up in XML using the National Library of Medicine DTD.

Table of contents

The various aspects of the Open Citations Project and its outputs are described in the following blog posts, complete with diagrams, data tables, and screen shots where appropriate. These are organized into the following set of distinct topics:

  • Standards
  • The SPAR ontologies for bibliographic and data entities and their citations
  • Graffoo and LODE – tools for ontology visualization and documentation
  • Third-party applications of our ontologies
  • Mappings to the SPAR ontologies, and exemplar RDF encodings
  • Development of data citation methods and protocols
  • The creation of the Open Citation Corpus of linked bibliographic citation data

1 Standards

Advantages of Ontological Standards in Scholarly Publishing

Nomenclature for citations and references

2 The SPAR ontologies for categorizing bibliographic and data entities and their citations

The SPAR ontologies described in the following blog posts were developed jointly with Silvio Peroni, a brilliant graduate student from the University of Bologna, who spent the last six months of 2010 working with me as an intern in Oxford, where he became an honorary member of the Open Citations Project, contributing very significantly to our achievements. His supervisor Fabio Vitali and the Department of Information Science at the University of Bologna are to be congratulated and thanked for their enlightened requirement that all their graduate students spend an internship overseas, since without his collaboration and great skill, much of this development would not have been possible within the available time, if at all.

Introducing the Semantic Publishing and Referencing (SPAR) Ontologies

New web site for the SPAR ontologies

Functional clustering of CiTO properties

Extending FRBR within FaBiO

Categorising bibliographic resources with FaBiO and SKOS

CiTO4Data – a new data-centric citation typing ontology

Using FaBiO to describe data entities

3 Graffoo and LODE – tools for ontology visualization and documentation

These tools have been developed by Silvio Peroni, an honorary member of the Open Citations Project, as explained above.

Graffoo, a Graphical Framework for OWL Ontologies

Using LODE for ontology visualization

4  Third-party applications of our ontologies

Our work to develop a standard semantic infrastructure for bibliographic and data entities and their citation is new. Nevertheless, we have received encouraging responses when we have presented our work at international publishing venues such as the 2010 ALPSP Conference and the 2010 STM Innovation Conference.

Apart from local applications at the University of Oxford, the University of Bologna, and the University of Manchester (for the Utopia Project), and adoption of the SPAR ontologies by the University of Harvard both to complement SWAN (Semantic Web Applications in Neuromedicine) and to mark up astrophysics data (Accomazzi and Dave (2011) Semantic Interlinking of Resources in the Virtual Observatory Era. arXiv:1103.5958), we have expressions of interest from PLoS, Nature and Il Mulino, a major academic publisher in Italy, who are looking to improve their metadata encoding as RDF. We are also interacting with the British Library in mapping the DataCite Metadata Kernel to RDF (see below), and with the Dryad Data Repository in creating RDF mappings of Dryad metadata to RDF and, as part of the JISC Dryad-UK Project, in developing MIIDI and MIIDI-structured RDF metadata for infectious disease papers and datasets, using SPAR ontologies where appropriate, with the aim of permitting authors to submit rich metadata to Dryad.

The following blog posts describe uptake and use of CiTO in CiteULike and WordPress.

Use of CiTO in CiteULike

How to employ CiTO in CiteULike

Using CiTO in WordPress

5 Mappings to the SPAR ontologies, and exemplar RDF encodings

Comparison of BIBO and FaBiO

BIBO2SPAR, an RDF Mapping of BIBO to the SPAR Ontologies

DataCite2RDF – Mapping DataCite Metadata Scheme Terms to ontologies

6 Development of data citation methods and protocols

Nomenclature for data publications and citations

Questions of granularity – Dryad’s use of DataCite DOIs for data citation

How to cite data

Pensoft Journals policy and author guidelines on data publication and citation

7 The creation of the Open Citation Corpus of linked bibliographic citation data

This achievement is almost entirely as the result of the excellent work of our chief data wrangler Alex Dutton, whose skill and natural feel for linked data has done wonders for this project.

The following set of blog posts describe the starting corpus from PubMed central, our transformation of it to RDF, the problems we encountered along the way, the resulting Open Citations Corpus, and the potential uses to which the resulting open citation data can now be put.

Input data for Open Citations – the PMC Open Access Subset

Garbage in, garbage out – problems with bibliographic references

Who wrote this paper? Author list problems in PubMed Central references

Citation correction methods

The citation processing pipeline and the Open Citations Corpus

JISC Open Citations Project web site

Like a kid with a new train set! Exploring citation networks


JISC Administrative Data for Open Citations Project

This information, extracted from the JISC Expo DOAP (Description of a Project) spreadsheet,  is to be found in a separate blog post, here.

The Future

While this is the formal Final Blog Post for the JISC-funded Open Citations Project, that was funded for a year from 1st July 2010, our work is not yet finished. We cherish grand ideas for the liberation of the reference lists from all scholarly journal articles, using the Open Citations Corpus as an exemplar, in collaboration with publishers and organizations such as CrossRef who handle such citation data on behalf of publishers on a daily basis.

This work will only be finished when it is longer up to an individual academic research group to take on the task of citation liberation, but when each publisher publishes the citation data from each of their journal articles as open linked data on their own web sites, marked up using agreed ontological standards that we have proposed, freely available for scholar around the world, from Bangladesh to Zimbabwe, and from Holland to New Zealand, to use and explore, independent of their ability to afford subscription access to the journal articles from which the citations are made.

JISC Open Citations Project web site

The JISC Open Citations Project website at http://opencitations.net exists for several purposes:

and, most importantly,

The JISC Open Citations Project Home Page

For the purposes of this demonstration, we are running an instance of Fuseki, that provides access to the Open Citation Corpus in an underlying TDB quad store, with a local patch to enable query timeouts, as was done for the SPARQL endpoint of CLAROS, a related project in which we have been intimately involved.

The web site and the underlying RDF citation data follow key linked data principles:

  • We don’t use blank nodes
  • All URIs are dereferenceable and content-negotiable.
  • Where possible we use standard identifiers based on DOIs, ISSNs and ISBNs.

For users wishing to jump into the data, we provide tabs to access data about journals and articles, each giving greater detail about the contents as one clicks in.

The Journals page

Each Journal page displays metadata about the journal, and links to useful information and the ability to download the journal metadata in a variety of formats.


Details of one journal

The articles tab displays a subset of about 10% of the entire corpus, for speed of loading the demonstration.

The Articles Page

Each ‘article’ page displays details about the selected article and its citation network, using graphviz, along with a user input form to customise the display of the network, namely for input or output citations, and for different forms of display. The article metadata and the citation diagrams can be downloaded in various formats.

Input citations for Codon, C. (2007). Maturation and degradation of RNA in bacteria. Current Opinion in Microbiology 10(3): 271-278. doi:10.1016/j.mib.2007.05.008.

We also display the RDF properties of each entity, allowing a ‘follow your nose’ style of data discovery. Each page lists the SPARQL queries that were run to generate it, enabling the user to see how the site works and to tweak the queries for their own ends.

Further work is planned to display citations along a time axis, and to develop other tools to permit users to exploit the data.

The citation processing pipeline and the Open Citations Corpus

The input PubMed Central Open Access subset XML reference data, our starting corpus, were transformed into Open Citations RDF in multiple stages:

  1. The original XML was first transformed into an intermediate form using XSLT. The multitudinous ways different publishers have developed of encoding the same information can be more easily handled in this way, by generating an intermediate XML output dataset in which things are described in a more consistent manner, and enabled the resulting information to be parsed more easily from within a non-XML-based programming environment. Our transform pulled out information about articles, people, organisations, in-text reference pointers, and the reference list, and the links between them.
  2. The intermediate XML dataset was then transformed into BibJSON using a Python script. BibJSON is a relatively standard method of encoding bibliographic information. Each of the ~200,000 generated BibJSON dataset contains the information extracted from one marked-up Open Access article. We extended the standard BibJSON records with additional attributes (named with an ‘x-‘ prefix) for other properties we wish later to encode as RDF. At this and later stages, the BibJSON datasets are packed into a single gzipped tarball. Since it would be unwise to unpack such a tarball into ~200,000 independent files would give data management problems, the contents are extracted from the tarball as required using the Python tarfile module.
  3. Another Python script was then used to extract all the PubMed IDs, and to use these as inputs to the Entrez API, in order to extract independent information about the cited entities from the PubMed database. The returned PubMed records were then added alongside the original BibJSON records. These additional data were extremely useful for comparison when attempting to spot erroneous citations, as previously described.
  4. Next we ran a ‘sanitization script’ over the data, which performed the following functions:
  1. URL normalization (e.g. adding URL schemes, undoing character substitutions (e.g. en-dashes for hyphens, quotation marks for apostrophes).
  2. Splitting issue information from journal attributes.
  3. Fixing malformed DOIs (e.g. those missing the ’10.’ prefix). Where DOIs could not be fixed they were removed.
  4. Pulling “doi:****” DOIs out of “http://dx.doi.org/**** URLs.
  5. Removing spurious publication dates (those before 1900 and after 2011).

These corrections are easily extensible if we discover other classes of error in the data.

  1. The records were next unified by taking the transitive closure on a number of identifiers. These identifiers included DOIs, PubMed IDs, PubMed Central IDs and URLs for articles and other cited works, and ISSNs, eISSNs and ISO title abbreviations for journals.
  2. The BibJSON data were then rearranged so that each dataset contains multiple records believed to reference the same bibliographic entity, if it had multiple citations.
  3. Owing to mis-citation (in this case, the use of incorrect or incomplete identifiers) there were a number of clearly different that had been mistakenly declared to refer to the same entity. For this reason we use a distance metric to recluster record groups based on similarity.
  4. Finally, a Python script transforms the BibJSON tarball into RDF. The input tarball contains datasets, each of which comprises records believed to refer to the same entity. The script takes each of these datasets and merges them into a single ‘best’ record using the majority vote procedure previously described. The resultant record is then transformed into a number of quads for inclusion in the final RDF N-Quads Open Citations Corpus, principally modelled using the suite of SPAR ontologies created for this purpose.

This Open Citations Corpus of rdf citation data extracted from the open access subset of PubMed Central, detailing every reference list in the OASS articles, holds each reference list as an individual named graph (hence the storage in N-Quads rather than triples), and comprises 236,499,781 quads occupying 2.1 gigabytes of storage in its compressed state. It includes references to ~20% of all post-1980 papers recorded in PubMed, including all the highly cited papers in every field of biomedical research, and is freely available under a CC0 waiver from http://opencitations.net/data/.

The Open Citations Corpus can be queried via a Web query form or via a SPARQL interface from the Open Citations Project web site at http://opencitations.net/, described in a subsequent blog post, where more information about the project is given.

All the scripts used to transform the OASS input data into the Open Citations Corpus, described above, are available under an MIT Open Source licence at https://github.com/opencitations/.