From little acorns . . . A retrospective on OpenCitations

The initial vision

Now that OpenCitations is hosting over one billion freely available scholarly bibliographic citations, this is perhaps an opportune moment to look back to the start of this initiative. A little over eleven years ago, on 24 April 2010, I spoke at the Open Knowledge Foundation Conference, OKCon2010, in London, on the topic

OpenCitations: Publishing Bibliographic Citations as Linked Open Data

I reported that, earlier that same week, I had applied to Jisc for a one-year grant to fund the OpenCitations Project (opencitations.net). Jisc (at that time ‘The JISC’, the Joint Information Systems Committee) was tasked by the UK government, among other things, to support research and development in information technology for the benefit of the academic community.

The purpose of that original OpenCitations R&D project was to develop a prototype in which we:

  • harvested citations from the open access biomedical literature in PubMed Central;
  • described and linked them using CiTO, the Citation Typing Ontology [1];
  • encoded and organized them in an RDF triplestore; and
  • published them as Linked Open Data in the OpenCitations Corpus (OCC).

I told those at the conference that in this demonstration project, with limited JISC funding, we could not hope to “boil the whole ocean”, but that nevertheless there would be substantial benefits from even partial coverage of citation data from the scholarly literature:

  • We could show the way and establish best practice.
  • Despite partial coverage, all key papers would most likely be cited several times.
  • The overall topological structure of the citation network would be revealed.
  • We would create a ‘benchmark’ corpus of high-quality RDF citation data that could be used to develop analytical and visualization tools.
  • We could show the value of open citation data in helping scholars to discover full text articles of all types, and thus encourage subscription-access publishers to release their reference metadata.

The important thing, I said, was to make a start!

The Jisc OpenCitations Project

That JISC grant application was funded, and the project, to last for a year with modest funding of £100K, started in my lab in the Department of Zoology at Oxford University on 1st June 2010, and was subsequently extended for a further six months.

Using data from the Open Access subset of PubMed Central, we created the first prototype release of the OpenCitations Corpus of linked bibliographic citation data, containing 6,529,815 independent bibliographic records of both citing and cited entities, comprising references to ~20% of all post-1980 articles recorded in PubMed, including those to all the most important highly cited papers in every field of biomedical endeavour.

This achievement was almost entirely the result of the excellent work by our chief data wrangler Alex Dutton, whose skill and natural feel for linked data did wonders for this project. Ben O’Steen, Graham Klyne and Alistair Miles made important contributions.

The project also resulted in many other development, described here, most which were developed or at least initiated during a short but wonderfully productive collaboration with Silvio Peroni, who spent six months with me in 2010 as a doctoral student intern from the University of Bologna, to which he subsequently returned to complete his thesis and develop his academic career.

These included:

  • the deconstruction and re-development of the original version of CiTO into a suite of orthogonal and complementary ontologies covering the whole domain of scholarly publishing – the SPAR (Semantic Publishing and Referencing) Ontologies [2, 3];
  • the mapping of various existing metadata schemas into RDF using SPAR, including the DataCite Metadata Schema, and subsequently JATS, now the default NISO standard for XML markup of scholarly documents) [4]; and
  • the initiation of the Semantic Publishing Blog and this OpenCitations Blog.

Life after Jisc – the flowering of OpenCitations

After the Jisc funding ended and I, after a long career in biological teaching and research, formally retired from the Department of Zoology at the Oxford University, members of the initial OpenCitations team moved on to other things. Like so many grant-funded academic project whose initial financial support had dried up, OpenCitations could have foundered at that stage, as an interesting prototype but with too little content to be useful. However, the concept of providing an open alternative to proprietary citation indexes was too important to abandon. But how could it be transitioned into something enduring and useful, particularly when as a matter of principle one had decided that the citation data should be made freely available, thus precluding income generation by charging for ‘premium’ services or the formation of a commercial spin-off?

Finally, I realized that something radical needed to be done to move OpenCitations forward. I had maintained a lively collaboration with Silvio Peroni at the University of Bologna, resulting between 2011 and 2014 in the publication of 18 articles and conference papers concerning the SPAR ontologies, ontology development, documentation and visualization, and related topics, and in 2015 I invited him to start working with me directly on OpenCitations. It was the best decision I could have made. We decided to take the initial concept and re-implement it from the bottom up. OpenCitations gave Silvio a major computer science project to which he could apply his considerable talent, and soon resulted in the development of a revised RDF data model for describing citation data, the OpenCitations Data Model (OCDM) [5] and a suite of new software tools to harvest, organise and publish citations at linked open data [6]. The credit for almost all the subsequent conceptual and technical developments within OpenCitations, which have incrementally led to our present situation, is due to Silvio Peroni, and the scholarly community is indebted to him for the intelligence, skill and diligent application he has given to OpenCitations over the past six years. I am truly honoured to have Silvio as co-Director of OpenCitations, and wish to take this opportunity to acknowledge his contributions and to thank him publicly.

Our work on OpenCitations at that stage, summarized in [7], would not have been possible without the enthusiastic support of Silvio’s senior colleague Fabio Vitali and of the Department of Computer Science and Engineering at the University of Bologna, which not only provided a stimulating environment for Silvio’s post-doctoral work, but also supplied computing services and infrastructure at no charge to OpenCitations. It was also greatly helped by Professor David De Roure of Oxford University, who gave me an academic home and a formal affiliation within the Oxford e-Research Centre after my retirement from the Department of Zoology, which enabled me to continue to hold research grants.

As has been documented in earlier posts in this blog, we greatly benefitted in 2017 from a grant from the Alfred P. Sloan Foundation which enabled us to purchase a new and more powerful computing infrastructure for the sole use of OpenCitations and to extend and improve our software, and subsequently in 2019 by a project grant from the Wellcome Trust to develop the Open Biomedical Citations in Context Corpus, that permitted the extension of OCDM and SPAR for the characterization of in-text references and their textual contexts.

A significant breakthrough came in January 2018 with our decision to treat citations as first-class data entities, each with its own persistent identifier (PID), the Open Citations Identifier (OCI) [8]. This gave Silvio the freedom to envision a new kind of database, a citation index in which each citation had its own metadata, including citation timespan, citation categorization (e.g. self-citation), and of course the DOIs of the citing and cited publications. The creation of this new index was possible only with the incredible effort by Ivan Heibi, who served as a Research Fellow in the project funded by the Alfred P. Sloan Foundation at that time, and who was entirely responsible for developing the first version of the code necessary for creating such a database. Having harvested all the open references from Crossref metadata dumps, Silvio and Ivan created COCI, the OpenCitations Index of Crossref DOI-to-DOI Citations, which immediately became our principal source of open citations, the original OpenCitations Corpus being retained as a ‘sandbox’ in which to experiment with new data representations, for example those required for the Open Biomedical Citations in Context Corpus. Access to COCI was facilitated by Silvio’s development of a REST API, using his software tool RAMOSE (Restful API Manager Over SPARQL Endpoints), which enables the easily configurable deployment of a REST API over any SPARQL endpoint to an RDF triplestore [9]. We were able to organize our all data, both ‘traditional’ and new, and to encode it in RDF, thanks to the comprehensive OpenCitations Data Model [5], itself based on our SPAR Ontologies [3], which we evolved as necessary to accommodate new data representation requirements.

During this period we published a number of definitions, conference papers and journal articles documenting these advances, details of which can be found here. Of these, the most recent canonical publication describing OpenCitations as an infrastructure for open scholarship, and its datasets, tools, services and activities, is Peroni and Shotton (2020) [10]. We also established the Research Centre for Open Scholarly Metadata at the University of Bologna, primarily to handle administrative, financial and academic aspects of OpenCitations activities.

OpenCitations’ future

The problem remained: how to sustain the OpenCitations infrastructure financially. We were greatly helped by Bilder, Lin and Neylon’s formulation of the Principles of Open Scholarly Infrastructures (POSI) [11], in which they clearly pointing out that reliance solely on grant funding for specific projects was not the answer. OpenCitations compliance with POSI is described here. We were thus immensely grateful that SPARC Europe and other institutions had the wisdom to establish SCOSS (The Global Sustainability Coalition for Open Science Services) to facilitate the crowd-sourced financial support of useful open infrastructures by the scholarly community, including academic libraries, government agencies and other stakeholders. OpenCitations applied for SCOSS support in 2019, which led to the selection of OpenCitations for support in the SCOSS second round.

The donations we are now starting to receive from such stakeholders, and the new staff that this funding has recently allowed us to hire, signal the start of our transition from a financially vulnerable academic project to a sustainable open scholarly infrastructure of real value to the community.

The work of opening more of the global citation graph now requires two things:

  • that each publisher takes responsibility for ensuring that the references from all of its journal articles and books are submitted, together with all other bibliographic metadata, to open scholarly bibliographic metadata aggregators such as Crossref and DataCite, from which they can be indexed into open citation indexes of sufficient quality, depth of detail and breadth of coverage that these offer genuine alternatives to the expensive proprietary citation indexing services upon which the academic community presently relies; and
  • that the entire scholarly stakeholder community re-directs a fraction of the enormous sums currently spent on its subscriptions to proprietary bibliographic services in order to support Open Science infrastructures such as OpenCitations that making citations and other forms of scholarly metadata and objects freely available.

References

[1] David Shotton (2010). CiTO, the Citation Typing Ontology. J. Biomedical Semantics 1 (Suppl. 1): S6. http://dx.doi.org/10.1186/2041-1480-1-S1-S6

[2] Silvio Peroni, David Shotton (2012). FaBiO and CiTO: ontologies for describing bibliographic resources and citations. Web Semantics, 17: 33-34. https://doi.org/10.1016/j.websem.2012.08.001, OA at http://speroni.web.cs.unibo.it/publications/peroni-2012-fabio-cito-ontologies.pdf

[3] Silvio Peroni, David Shotton (2018). The SPAR Ontologies. In Proceedings of the 17th International Semantic Web Conference (ISWC 2018): 119-136. https://doi.org/10.1007/978-3-030-00668-6_8

[4] Peroni S, Lapeyre DA and Shotton D (2012) From Markup to Linked Data: Mapping NISO JATS v1.0 to RDF using the SPAR (Semantic Publishing and Referencing) Ontologies. Proc. 2012 JATS Conference, National Library of Medicine, Bethesda, Maryland, USA (October 2012): 16-17. http://www.ncbi.nlm.nih.gov/books/NBK100491/

[5] Marilena Daquino, Silvio Peroni , David Shotton (2020). The OpenCitations Data Model. Figshare. https://doi.org/10.6084/m9.figshare.3443876.v7

[6] Silvio Peroni, David Shotton, Fabio Vitali (2017). One Year of the OpenCitations Corpus: Releasing RDF-based scholarly citation data into the Public Domain. In The Semantic Web – ISWC 2017 (Lecture Notes in Computer Science Vol. 10588, pp. 184–192). Springer, Cham. https://doi.org/10.1007/978-3-319-68204-4_19

[7] Silvio Peroni, Alexander Dutton, Tanya Gray, David Shotton (2015). Setting our bibliographic references free: towards open citation data. Journal of Documentation, 71 (2): 253-277. http://dx.doi.org/10.1108/JD-12-2013-0166, OA at http://speroni.web.cs.unibo.it/publications/peroni-2015-setting-bibliographic-references.pdf

[8] Silvio Peroni, David Shotton (2019). Open Citation Identifier: Definition. Figshare. https://doi.org/10.6084/m9.figshare.7127816

[9] Daquino, M., Heibi, I., Peroni, S., & Shotton, D. (2021). Creating Restful APIs over SPARQL endpoints with RAMOSE. Semantic Web. http://arxiv.org/abs/2007.16079

[10] Silvio Peroni, David Shotton (2020). OpenCitations, an infrastructure organization for open scholarship. Quantitative Science Studies, 1(1): 428-444. https://doi.org/10.1162/qss_a_00023

[11] Geoffrey Bilder, Jenny Lin, Cameron Neylon (2015). Principles for Open Scholarly Infrastructure. http://dx.doi.org/10.6084/m9.figshare.1314859

OpenCitations described

OpenCitations is an infrastructure organization for open scholarship dedicated to the publication of open bibliographic and citation data. We at OpenCitations are proud to announce the publication, in the first issue of Quantitative Science Studies, of a canonical paper in which we introduce and describe OpenCitations and outline its achievements and goals [1].

Here, I outline the contents of our paper, and provide definitive links on the topics described. Many of these topics have been the subjects of earlier blog posts.

This paper appears in the first Special Issue of QSS, dedicated to the description of the bibliometric data sources that lie at the heart of scientometric research, which aims to characterize the most important data sources currently available and to show how they differ in various dimensions, for instance in the data they provide, their level of openness, and their support for making research reproducible. The first three papers in this special issue cover the most important commercial bibliographic data sources: Web of Science (Clarivate Analytics), Scopus (Elsevier), and Dimensions (Digital Science), while the remaining three articles describe open data sources: Microsoft Academic, Crossref and OpenCitations.

In the introduction to our own paper, we describe the origins of OpenCitations, discuss the growth and benefits of open science, and introduce the Semantic Web techniques used at OpenCitations for recording and publishing our data. We then go on to describe OpenCitations’ services and data, namely Open Citation Identifiers, the OpenCitations Data Model, the SPAR (Semantic Publishing and Referencing) Ontologies, the OpenCitations Corpus, and the OpenCitations Indexes of citation data, of which the first and largest is COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations, that currently holds information on over 624 million citations. We conclude our survey of OpenCitations’ services and data by outlining the generic open source software developed at OpenCitations, including OSCAR, the OpenCitations RDF Search Application for searching over RDF datasets, LUCINDA, OSCAR’s associated OpenCitations RDF Resource Browser, and RAMOSE, OpenCitations’ application for creating REST APIs over SPARQL endpoints, thus opening Semantic Web datasets to those not familiar with SPARQL, the RDF query language.

In the second half of the paper, we describe OpenCitations as an organization in terms of its compliance with the principles for the sustainability of open infrastructures proposed by Bilder, Lin and Neylon (2015) [2], and report the selection of OpenCitations by the Global Sustainability Coalition for Open Science Services (SCOSS) as an open infrastructure organization worthy of crowd-funding support by the stakeholder community. We then provide usage statistics for our datasets and web site, and describe the adoption of OpenCitations data and services by the community, before concluding with a forward look at our proposed developments of OpenCitations activities.

References

[1] Silvio Peroni and David Shotton (2020). OpenCitations, an infrastructure organization for open scholarship. Quantitative Science Studies 1 (1): 428-444. https://doi.org/10.1162/qss_a_00023

[2] Geoffrey Bilder, Jennifer Lin and Cameron Neylon (2015). Principles for open scholarly infrastructures. Figshare. https://doi.org/10.6084/m9.figshare.1314859

‘Likes’ joins the semantic web: cito:likes

A ‘like’ button is a well-known feature in communication software such as social networking services, Internet forums, news websites and blogs that permits a user to indicate that he/she likes, enjoys or supports certain content.  Internet services that feature ‘like’ buttons usually also display the number of users who have expressed that they ‘like’ a particular item of content, providing a quantitative estimate of the strength of support for it.

In particular, the ‘Like’ button is one of Facebook’s social plug-ins, which can be use on websites outside Facebook as part of Facebook’s Open Graph.  It is valued by advertisers who wish to attract ‘likes’ for their products (and who pay Facebook for the privilege), but its use has aroused privacy concerns because it permits Facebook to track visitors to participating sites, even if they not Facebook users, giving Facebook a vast amount of information about who visits which sites.

Like it or not, however, this form of social communication has now become an integral feature of online social interactions.  For this reason, we thought it would be worthwhile to enable encoding of such ‘likes’ as open linked data, in the form of a new object property in CiTO, the Citation Typing Ontology.

This new property, cito:likes, has the following definition:

“A property that permits you to express appreciation of or interest in something, or to express that it is worth thinking about even if you do not agree with its content, enabling social media ‘likes’ statements to be encoded in RDF.  Use of this property does NOT imply the existence of a formal citation of the entity that is ‘liked’.”

An exemplar usage of cito:likes (in Turtle format) is:

sioc: <http://rdfs.org/sioc/ns#> .
foaf: <http://xmlns.com/foaf/0.1/> .
today: <http://opencitation.wordpress.com/2012/07/13/> .

today:cito-likes a sioc:Post ;
	sioc:has_creator [ 
		a sioc:UserAccount ; 
		sioc:account_of [ 
			a foaf:Person ;
			foaf:givenName "David" ;
			foaf:familyName "Shotton" ] ] .

<https://www.facebook.com/silvioperoni> a sioc:UserAccount ;
	sioc:account_of <http://www.essepuntato.it/me>;
	cito:likes today:cito-likes .

To our surprise, we found that existing ontologies did not include such a property – a search in the excellent new LOV (Linked Open Vocabularies) service revealed that no other open ontology contains the same concept as is now represented by cito:likes.

The Trait Ontology has trait:likes, but this object property has a gender-related domain, and its definition indicates that its usage is designed for expressing sexual fetish preferences.

Schema.org at first sight appears to have something resembling cito:likes, but inspection of schema:UserLike reveals this use to be specific for events.

Even the SIOC ontology, a product of the SIOC initiative (Semantically-Interlinked Online Communities) aimed at enabling the integration of online community information, which is described in an award-winning paper from DERI [1], lacks the concept ‘likes’.

So here we offer cito:likes, a property (like all other cito properties) without domain or range constraints, permitting it to be used in a wide variety of situations.

Like it? Click the Like button below!

David Shotton
Silvio Peroni

Reference

[1]     John G. Breslin, Andreas Harth, Uldis Bojars, and Stefan Decker (2005). Towards Semantically-Interlinked Online Communities.  In Proc. ESWC 2005 (A. Gómez-Pérez and J. Euzenat, Eds.); Lecture Notes in Computer Science 3532, pp. 500–514.  doi:10.1007/11431053_34.  Available from http://bit.ly/KQ2iK4.

Open Citations and Semantic Publishing

Given the renewed interest among publishers in the Open Citations Corpus, following the decisions by Nature Publishing Group, publisher of Nature, and by the American Association for the Advancement of Science, publisher of Science, to open their citation data for inclusion in the corpus, I thought it would be helpful to provide links to videos of two conference presentations I gave that describe the Open Citations Corpus in the context of our other work in the area of semantic publishing.

The first of these was an invited contribution with the title Enriching Scientific Citations to Facilitate Knowledge Discovery, given to publishers at the Scientific, Technical and Medical Publishers Innovations Seminar 2010 entitled “Flows in Flux: how publishing technologies change the researcher’s life”, held in London, UK, on 3rd December 2010:

lecture: http://river-valley.tv/media/conferences/stm-innovation-2010/0202-David-Shotton/

slides: http://imageweb.zoo.ox.ac.uk/pub/2010/Presentations/SHOTTON_Citations_STM-Innovations-Seminar-03Dec2010.pdf

abstract: http://imageweb.zoo.ox.ac.uk/pub/2010/Presentations/STM_Innovations_Seminar_2010_ABSTRACTS.pdf

The second presentation, given almost a year later, was an invited contribution with the title The SPAR (Semantic Publishing and Referencing) Ontologies and the Open Citation Corpus, given to librarians at SWIB11 (Semantic Web in Bibliotheken; Semantic Web in Libraries Conference 2011) “Scholarly Communication in the Web of Data”, held in Hambrug, Germany on 30th November 2011:

lecture: http://www.scivee.tv/node/39208

slides: http://imageweb.zoo.ox.ac.uk/pub/2011/presentations/Shotton_SWIB11_SPARandOpenCitationCorpus_30Nov2011.pptx.pdf

abstract: http://imageweb.zoo.ox.ac.uk/pub/2011/presentations/Shotton_Abstract_for_Presentation_at_SWIB11.pdf

Further details of the Open Citations Corpus and the SPAR ontologies, and their applications are, of course, given in this Open Citations and Semantic Publishing blog, for which the following two posts provide the best introduction for those coming here for the first time:

JISC Open Citations Project – Final Project Blog Post

Introducing the Semantic Publishing and Referencing (SPAR) Ontologies

Five Stars Ontology

To accompany today’s publication in D-Lib Magazine of the article The Five Stars of Online Journal Articles – a framework for article evaluation highlighted in the previous post, I have today also published The Five Stars Ontology, a simple ontology written in OWL 2 DL that forms part of SPAR, a suite of Semantic Publishing and Referencing Ontologies. It is intended for use by publishers and others wishing to encode Five Stars ratings, such as those exemplified in the D-Lib article, in machine-readable form, so they can accompany other machine-readable metadata for the article.  To exemplify this, the following RDF graph, shown in turtle notation, gives the Five Stars ratings for the D-Lib article itself:

<http://dx.doi.org/10.1045/january2012-shotton>
     fivestars:hasPeerReviewRating “3”^^xsd:nonNegativeInteger ;
     fivestars:peerReviewRatingComment “Post-publication responsive
          peer review of the preprint.” ;
     fivestars:hasOpenAccessRating “4”^^xsd:nonNegativeInteger ;
     fivestars:openAccessRatingComment “Gold/libre open access
          without author fee!” ;
     fivestars:hasEnhancedContentRating “1”^^xsd:nonNegativeInteger ;
     fivestars:enhancedContentRatingComment “Plentiful Web links in
          text and to all references. No additional semantic
          enhancement of text.” ;
     fivestars:hasAvailableDatasetsRating “0”^^xsd:nonNegativeInteger ;
     fivestars:availableDatasetsRatingComment “Not applicable.” ;
     fivestars:hasMachine-readableMetadataRating “1”^^xsd:nonNegativeInteger ;
     fivestars:machine-readableMetadataRatingComment “Structural
          markup in HTML only.” ;
     fivestars:hasOverallFiveStarsRating “9”^^xsd:nonNegativeInteger ;
     fivestars:overallFiveStarsRatingComment “The nature of this
          article, being a position paper rather than a research
          paper with primary research data, has influenced the
          overall rating obtained.” .

Comments on the paper Ceci n’est pas un hamburger

Very VERY occasionally I read a paper that is so well written, and which addressed the points so accurately and so eloquently, that I rejoice.  The paper by Pettifer et al. entitled Ceci n’est pas un hamburger: modelling and representing the scholarly article that appeared in Learned Publishing last October [1], is one of this special handful. 

It is beautifully written, and the scope of its coverage is highly pertinent to the recent discussions on the future of research communication detailed in the previous post.  It also has the benefit of being published as an Open Access paper in what is otherwise a subscription access journal. 

I particularly liked the authors’ evaluation of FRBR‘s classification into works, expressions and manifestations to describe the relative benefits and drawbacks of PDF, XML, and RDF as representations of a journal article, since that is exactly what Silvio Peroni and I modelled in FaBiO, the FRBR-aligned Bibliographic Ontology.

The paper is also an excellent introduction to Utopia Documents, the ‘smart’ PDF reader that the authors have developed, which is used to create the Semantic Biochemical Journal, and which is to be highly recommended for personal use to enrich the experience of reading articles in PDF format on-line.  The Utopia Documents software is freely available, and can be downloaded from http://www.utopiadocs.com.

[1] Pettifer S, McDermott P, Marsh J, Thorne D, Villeger A and Attwood TK (2011).  Ceci n’est pas un hamburger: modelling and representing the scholarly article.  Learned Publishing, 24 (3): 207-220.  http://dx.doi.org/10.1087/20110309.

 

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.

Enhanced by Zemanta

How to cite data

As an approach towards developing best practice for data citation, I recently wrote a Data Citation Best Practice Discussion Document that is available on Google Docs, and that I have now slightly revised to Version 2 [1].

In that document, I first compared what is recommended by DataCite [2] and by Altman and King [3] with what currently practised by the Dryad Data Repository and what presently occurs ‘in the wild’ in a handful of journal articles that reference Dryad datasets.  I then proposed some ‘internal’ recommendations for Dryad to adopt, and concluded with draft Data Citation Best Practice Recommendations.  As I say in the preface to the document:

“Since Dryad is pioneering data management in terms of data resources that are linked to journal articles, it is to be hoped that by first developing citation best practice in the Dryad context we can thereby catalyse its wider spread.  If we can thus agree what such best practice should be among the Dryad community and implement such best practice proposals, we can then promote such practices within the wider scholarly community.”

I realized that much of the confusion and disagreement concerning the best method of citing data resources within earlier e-mail threads resulted from a conflation of ideas about two entities which in the conventional citation of journal articles are quite distinct:

  • the in-text citation containing an in-text reference pointer, e.g. “this paper builds upon the work of Jones et al. [15].”     and
  • the actual reference to Jones et al. within the article’s reference list, e.g. “[15] Jones A, Bloggs B and Smith C (2008). Title. JournalName
    14:132-134. doi:*****.”

Thus, in an e-mail I wrote on 27 April, where I said

“Excellent, but what we really want is for the data citations to be included in the reference list along with the bibliographic citations, following the DataCite model: Creator (PublicationYear): Title. Version. Publisher. ResourceType. Identifier “

. . . I should also have stressed the need for explicit in-text citations that denote such references.

All that is explained within the Google Docs paper.  In that paper I also proposed having a separate Data Resources section within the body text of a journal article, in which data resource citations can be gathered.  That does not preclude these resources also being cited, where appropriate, within the Methods and Materials or Results sections of the paper, but is designed to put data resource citations “on the map”, so to speak, as important new publication performative acts.

It is not appropriate, in my mind, for data citations to be included in the Acknowledgements section of a paper, which is designed for acknowledging contributions to the work from people and funding agencies, even if Thomson Reuters has developed methods to parse such entries, since they also have well-established mechanisms for harvesting proper (data) references from the reference list.

All the ontological terms required to mark up in-text reference pointers and their textual contexts, references, reference lists, etc., to permit automated detection and harvesting of data citations and references, are available as RDF within the SPAR (Semantic Publishing and Referencing) Ontologies (http://purl.org/spar/), which were designed precisely to facilitate such work.

Since writing my Data Citation Best Practice Discussion Document, I was invited (on a purely voluntary non-commercial basis, I should add!) to work with Pensoft Journals, a publisher that specialises in publishing biodiversity and biological systematics papers, and that has taken the lead in promoting the publication of datasets with DOIs, to contribute to and help revise their now-published Data Publishing Policies and Guidelines for Biodiversity Data [4].  This 34-page paper has a three-page section on how to cite data in Pensoft Journals, which I discuss in the next blog post, and which I am pleased to say includes all the recommendations discussed above.

[1]     David Shotton (2011) Data Citation Best Practice Discussion Document. Google Docs. https://docs.google.com/document/d/1kF8-faB72l4dKTLEyx6Z5cIabk68GrJ9GraCtWnK0qQ/edit?hl=en_GB&authkey=CPPW46wL#.

[2]    The DataCite Metadata Kernel version 2.0 (2011). http://datacite.org/schema/DataCite-MetadataKernel_v2.0.pdf.

[3]    Micah Altman and Gary King (2007). A proposed standard for the scholarly citation of quantitative data. D-Lib Magazine. 13. http://www.dlib.org/dlib/march07/altman/03altman.html.

[4]     Penev L, Mietchen D, Chavan V, Hagedorn G, Remsen D, Smith V, Shotton D (2011). Pensoft Data Publishing Policies and Guidelines for Biodiversity Data. Pensoft Publishers, http://www.pensoft.net/J_FILES/Pensoft_Data_Publishing_Policies_and_Guidelines.pdf.

Search OpenEdition Search

You will be redirected to OpenEdition Search