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Tag: citation data

COCI has surpassed 700M citations

We are excited to share that COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations, was on 12 May 2020 extended with more than 47 million additional citations, and has reached a total number of more than 702 million DOI-to-DOI citation links between more than 58 million bibliographic entities.

The citations added in this the fifth release of COCI came from the most recent Crossref dump downloaded on 22 April 2020, which includes the references of the articles deposited in Crossref between 4 October 2019 and 4 April 2020. Such updates to COCI will now occur regularly at bimonthly intervals.

As a consequence, COCI now contains 702,772,530 citations, and also includes publications about the COVID-19 pandemic. We will use this new release of COCI to update the Coronavirus Open Citations Dataset, the second release of which will include details about these additional references and publications.

COCI, which is fully described in our open-access article, was one of the subjects of a multidisciplinary comparison between the major citation indexes recently published on arXiv. In addition, it has been recently mentioned on the Scholix web site as one of the implementors of the Scholix citation data format.

Finally, we wish to remind you that all the bibliographic and citation data in COCI:

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

The first issue of Quantitative Science Studies

The memorable date 20/02/2020 saw the publication by MIT Press of the first issue of Volume One of a new journal, Quantitative Science Studies (QSS), the official open access journal of the International Society for Scientometrics and Informetrics (ISSI). QSS’s Editor in Chief is Ludo Waltman (CWTS, University of Leiden, Netherlands), Vincent Larivière (Université de Montréal, Montreal, Quebec, Canada) and Staša Milojević (Indiana University Bloomington, Bloomington, Indiana, USA) are its Associate Editors, and it has a large and distinguished editorial board.

What makes the launch of this new journal remarkable is the story of how it came into being. In 2019, the entire editorial team of the Journal of Informetrics (JOI), a leading journal in this field published by Elsevier, resigned en masse and decided to start an alternative journal, QSS, both because of Elsevier’s position on open citations, and because, in their opinion, the financial model used by Elsevier violates the scientific ethos.

Reproducibility in the field of scientometrics requires scientific metadata that are both of high-quality and open, particularly those relating to bibliographic citations. The JOI editorial board was deeply concerned by the refusal of Elsevier to join almost all other large scholarly publishers in supporting the Initiative for Open Citations (I4OC). As we have previously reported on this blog, Elsevier is the largest contributor of bibliographic references to Crossref, but insists that these data should be kept closed.

Elsevier’s position, driven by commercial interests (since it sells access to citation data through Scopus), flies in the face of the scientific community’s clear move towards open science, with hundreds of scientometricians having signed an ISSI open letter urging scholarly publishers to support I4OC.

Science is a self-governing system, and the editorial team held the view that the ultimate responsibility for a scholarly journal should fall with the scientific community, who serve as the gatekeepers, producers, and consumers of scientific content.

The editorial team also believed Elsevier’s subscription fees to be excessive, and its article processing charges (APCs) for open access publishing to be unfairly high, thus limiting both those who can afford to read Elsevier journals and those who can afford to publish in them, so that publishing with Elsevier inevitably places major limits on scholarship, harming both science and society. It was for all these reasons that they forsook JOI and started QSS.

We at OpenCitations congratulate the editorial team for their courage in deciding to make this journal flip, and wish them, together with the ISSI and MIT Press, every success for this important new journal. We also commend the Technische Informationsbibliothek (TIB) – Leibniz Information Centre for Science and Technology and the Communication, Information, Media Centre (KIM) of the University of Konstanz, who, in collaboration with the Fair Open Access Alliance (FOAA), have generously agreed to cover APCs for the first three years of the QSS journal.

Introducing InTRePIDs – In-Text Reference Pointer Identifiers

Rationale

Readers of this blog will be familiar with Open Citation Identifiers (OCIs), described in an earlier post and formally defined in [1]. OCIs enable bibliographic citations, treated as first class information entities, to be uniquely identified and referenced, and are used to identify the >624 million individual citations indexed in the latest release of COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations, as described in a recent post.

However, COCI and similar citation indexes do not provide any information about where within the citing paper a citation is generated, the textual contexts of the in-text reference pointers, or the reasons for including different in-text reference pointers denoting the same reference at different points within the text.

As explained in the preceding post describing the Open Biomedical Citations in Context Corpus funded by the Wellcome Trust and under development by OpenCitations, deep citation analysis requires a more nuanced approach to citations, which acknowledges that each in-text reference pointer that denotes a bibliographic reference in the reference list of a citing publication instantiates its own citation, as shown in Figure 1.

Figure 1. Citations between a citing paper and a cited paper instantiated both by the inclusion of a bibliographic reference within the reference list of the citing paper and by the inclusion within the text of the citing paper of one or more in-text reference pointers denoting that reference.

The pointer citations clearly involve the same cited publication as does the reference citation itself, but each has its own unique characteristics: the location and textual context of its in-text reference pointer within the text of the citing publication, and its particular rhetorical function which is determined by that context.

If the reference citation is open (as defined in [2]) and identified by an OCI, each in-text reference pointer related to that citation can be identified uniquely using an In-Text Reference Pointer Identifier (InTRePID).

InTRePIDs facilitate in-depth scholarship on in-text reference pointer locations and citation functions, and fine-grained analysis of the relationships between publications, by making it possible

  • to identify each in-text reference pointer with a unique PID,
  • to distinguish references that are cited only once from those that are cited multiple times,
  • to see which references are cited together (e.g. in the same sentence or within an in-text reference pointer list),
  • to determine from which section(s) of the article references are cited (e.g. Introduction, Methods, Discussion), and, potentially,
  • to determine the rhetorical function of the citations from analysis of their textual contexts, by the application of natural language processing, machine learning and artificial intelligence techniques to conduct sentiment analysis on the citation contexts.

Definition of an InTRePID

An InTRePID is composed of two parts separated by an oblique stroke

intrepid:<oci-numerals>/<ordinal>–<total>

where

  • <oci-numerals> is the numerical part of the OCI uniquely identifying the particular open citation to which the in-text reference pointer and its denoted bibliographic reference relate. Thus an InTRePID can be assigned for any in-text reference pointer that relates to an open citation for which a valid OCI has been assigned;
  • <ordinal> identifies the nth occurrence of an in-text reference pointer within the text of the citing paper relating to that citation; and
  • <total> defines the total number of in-text reference pointers denoting that bibliographic reference within the citing paper.

For example, intrepid:070433-070475/4–6 is a valid InTRePID for an in-text reference pointer defined within the OpenCitations Citations in Context Corpus.

A formal definition document for the InTRePID is given in [3].

Exemplar in-text reference pointers

Consider the following citing paper:

Zou, J. et al. (2020). Phenotypic and genotypic correlates of penicillin susceptibility in nontoxigenic Corynebacterium diphtheriae, British Columbia, Canada, 2015–2018. Emerging Infectious Diseases, 26: 97-103. https://doi.org/10.3201/eid2601.191241

This paper contains six in-text reference pointers denoting Reference 13 in the reference list:

13. Lowe, C. et al. (2011). Cutaneous diphtheria in the urban poor population of Vancouver, British Columbia, Canada: a 10-year review. J. Clinical Microbiology 49: 2664-2666. https://doi.org/10.1128/JCM.00362-11

The InTRePIDs for these pointers are recorded within the OpenCitations Biomedical Citations in Context Corpus, together with the corpus identifiers and DOIs of the citing and cited papers, as shown in the excerpt presented in Figure 2.

Figure 2. An excerpt from the OpenCitations Biomedical Citations in Context Corpus, showing highlighted the InTRePIDs for the six in-text reference pointers within Zou, J. et al. (2020) denoting Reference 13, the reference to Lowe, C. et al. (2011), together with the internal corpus identifiers for each in-text reference pointer, and the corpus identifiers and DOIs for the citing and cited papers.

Of these six in-text reference pointers, having InTRePIDs intrepid:070433-070475/1-6 to intrepid:070433-070475/6-6, the first and the fourth of these, together with their document locations, their embedding sentences, their in-text reference pointer lists, and their InTRePIDs, chosen as examples, are as follows:

Introduction. “Nontoxigenic strains have been shown to have epidemic potential, causing infections in persons afflicted by homelessness, alcohol abuse, and injection drug use (9,13–15).” (intrepid:070433-070475/1-6)

Discussion. “We also noted ST5 and ST32 in our review from downtown Vancouver during 1998–2007 (13).” (intrepid:070433-070475/4-6)

The first of these discusses those people most susceptible to diphtheria infection, while the other discusses which multilocus sequence types (STs) of C. diphtheriae were found, thus relating to the organism causing the infection rather than to the infected individuals. The rhetorical function of these two in-text reference pointers is quite distinct.

To permit this information to be recorded within the OpenCitations Citations in Context Corpus, extensions were required to the OpenCitations Data Model, a new extended version of which was recently published [4], as described in a related blog post.

The OpenCitations InTRePID Resolution Service

To support the use of InTRePIDs to identify in-text reference pointers, OpenCitations has recently developed an InTRePID Resolution Service (currently in ‘beta’ in its development cycle), which is running at http://opencitations.net/intrepid. A screenshot of this service is shown in Figure 3.

Figure 3. A screenshot of the user interface of the InTRePID Resolution Service.

In addition to using the Web user interface shown in Figure 3, InTRePIDs can be entered into this resolution service in the form of resolvable URIs, e.g.

http://opencitations.net/intrepid/070433-070475/4-6

As shown in Figure 4, the OpenCitations InTRePID Resolution service returns metadata concerning the in-text reference pointer identified by the InTRePID, and the bibliographic reference that it denotes, from which further information about the citation and the citing and cited publications may be obtained by following the links provided.

Figure 4. A screenshot of the Web page displaying metadata returned by the InTRePID Resolution Service.

Note that as well as rendering this information in HTML on a web page, the resolution service can also provide it in a variety of machine-readable formats.

Conclusion

InTRePIDs, which enable the identification of individual in-text reference pointers, and the InTRePID Resolution Service, are new services from OpenCitations that will facilitate scholarship on the textual contexts and rhetorical functions of such in-text reference pointers, and of the citations that they instantiate.

InTRePIDs were first announced on 30th January 2020 at PIDapalooza 2020 in Lisbon, the Open Festival of Persistent Identifiers.

References

[1] Silvio Peroni and David Shotton (2019): Open Citation Identifier: Definition. Figshare. https://doi.org/10.6084/m9.figshare.7127816.v2

[2] Silvio Peroni and David Shotton (2018). Open Citation: Definition. Figshare. https://doi.org/10.6084/m9.figshare.6683855

[3] David Shotton, Marilena Daquino and Silvio Peroni (2020). In-Text Reference Pointer Identifier: Definition. Figshare. https://doi.org/10.6084/m9.figshare.11674032

[4] Marilena Daquino, Silvio Peroni and David Shotton (2019). The OpenCitations Data Model. Version 2.0. Figshare. https://doi.org/10.6084/m9.figshare.3443876

Workshop on Open Citations

OpenCitations [1], the EXCITE Project [2] and Europe PubMed Central [3] are pleased to announce a Workshop on Open Citations at the University of Bologna in Bologna, Italy [4] on 3-5 September – https://workshop-oc.github.io.

Format and topics

  • Day One and Day Two: Formal presentations and discussions on the creation, availability, uses and applications of open bibliographic citations, and of bibliometric studies based upon them. This will involve both invited and contributed presentations.
  • Day Three: A Hack Day on Open Citations to see what services can be prototyped using large volumes of open citation data.

We look forward to welcoming all those interested in open citation data, including researchers, computer scientists, scholarly publishers, academic administrators, research funders and policy makers. The workshop will be organised around the following topics:

  1. Opening up citations: Initiatives, collaborations, methods and approaches for the creation of open access to bibliographic citations.
  2. Policies and funding: Strategies, policies and mandates for promoting open access to citations, and transparency and reproducibility of research and research evaluation.
  3. Publishers and learned societies: Approaches to, benefits of, and issues surrounding the deposit, distribution, and services for open bibliographic metadata and citations.
  4. Projects: Metrics, visualizations and other projects. The uses and applications of open citations, and bibliometric analyses and metrics based upon them

Participation

If you would like to participate in this event, please enter your details and a mini-biography at https://bit.ly/2JEd0r9.

If additionally you would like to speak at this event, please select the session your talk would fit in, and provide a title and abstract for your talk. Selected submissions will involve either a talk of 10 minute duration, with a 5 minute discussion following, or a poster presentation.

The deadline for application and submission of these details is the 20th of May 2018. Notifications of acceptance will be sent to you by the 1st of June. In case of oversubscriptions, the organisers will select speakers and attendees from among those have applied.

Please circulate this invitation to any colleagues that you think might be interested in attending this workshop.

Fees and expenses

For those accepted, we request a small registration fee of €100 to cover expenses (€25 for students), which must be paid by the 15th of July 2018, but which will be waived in cases of financial hardship. Details of how to pay will be sent to those accepted. Registration for the Hack Day is free of charge.

Those attending will be expected to cover the cost of their own travel and accommodation. We will provide a list of recommended hotels and guest houses. We will provide lunches and refreshments on all days, and a free workshop dinner on Monday 3rd September.

Organizers

David Shotton (OpenCitations)
Jo McEntyre (Europe PMC)
Maria Levchenko (Europe PMC)
Marilena Daquino (University of Bologna)
Philipp Mayr (EXCITE project)
Silvio Peroni (OpenCitations)
Steffen Staab (EXCITE project)

Links

[1] OpenCitations – http://opencitations.net
[2] EXCITE Project – http://west.uni-koblenz.de/en/research/excite
[3] Europe PMC – https://europepmc.org/About
[4] University of Bologna – http://www.unibo.it/en/homepage

Follow us on Twitter at https://twitter.com/workshop_oc.

Early adopters of the OpenCitations Data Model

OpenCitations is very pleased to announce its collaboration with four new scholarly Research and Development projects that are early adopters of the recently updated OpenCitations Data Model, described in this blog post.

The four projects are similar, in that they each are independently using text mining and optical character recognition or PDF extraction techniques to extract citation information from the reference lists of published works, and are making these citations available as Linked Open Data. Three of the four will also use the OpenCitations Corpus as publication platform for their citation data.  The academic disciplines from which these citation data are being extracted are social science, humanities and economics.

1     Linked Open Citation Database (LOC-DB)

The Linked Open Citation Database, with partners in Mannheim, Stuttgart, Kiel, and Kaiserslautern (LOC-DB, https://locdb.bib.uni-mannheim.de/blog/en/), is the first of two German projects funded by the Deutsche Forschungsgemeinschaft (DFG) that are extracting citations from Social Science publications.  Dr. Annette Klein, Deputy Director of the Mannheim University Library, is the project manager.

The project is using Deep Neural Networks based approaches for reference detection and state-of-the-art methods for information extraction and semantic labelling of reference lists from electronic and print media with arbitrary layouts [3].  The raw data obtained will be manually checked against and linked with existing bibliographic metadata sources in an editorial system.  They will then be structured in RDF using the OpenCitations Data Model, and published in the Linked Open Citations Database under a CC0 waiver. Using its libraries’ own Social Science print holdings and licensed electronic journals as subject material, this project will demonstrate how these citation extraction processes can be applied to the holdings of individual academic libraries, and can be integrated with library catalogues [1, 2, 3].

References

[1]       Kai Eckert, Anne Lauscher and Akansha Bhardwaj (2017) LOC-DB: A Linked Open Citation Database provided by Libraries. Motivation and Challenges.  EXCITE Workshop 2017: “Challenges in Extracting and Managing References”.  https://locdb.bib.uni-mannheim.de/wordpress/wp-content/uploads/2016/11/LOC-DB@EXCITE.pdf

[2]      Lauscher, Anne; Eckert, Kai; Galke, Lukas; Scherp, Ansgar; Rizvi, Syed Tahseen Raza; Ahmed, Sheraz; Dengel, Andreas; Zumstein, Philipp; Klein, Annette  (2018) Linked Open Citation Database: Enabling libraries to contribute to an open and interconnected citation graph. Accepted for the JCDL 2018: Joint Conference on Digital Libraries 2018, June 3-6, 2018 in Fort Worth, Texas [Preprint of the conference publication].
https://locdb.bib.uni-mannheim.de/wordpress/wp-content/uploads/2018/04/LOCDB-JCDL2018-paper-camera-ready.pdf

[3]       Bhardwaj A., Mercier D., Dengel A., Ahmed S. (2017). DeepBIBX: deep learning for image based bibliographic data extraction. In: Liu D., Xie S., Li Y., Zhao D., El-Alfy ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science, vol 10635. Springer, Cham [Conference publication].

2     The EXCITE (Extraction of Citations from PDF Documents) Project

The EXCITE Project (http://west.uni-koblenz.de/en/research/excite/), run jointly at the University of Koblenz-Landau and GESIS (Leibniz Institute for Social Sciences), is the second project funded by the Deutsche Forschungsgemeinschaft (DFG) that is extracting citations from Social Science publications.  It is headed by Steffen Staab, head of the Institute for Web Science and Technologies at the University of Koblenz-Landau, and Philipp Mayr of GESIS.

Since the social sciences are given only marginal coverage in the main bibliographic databases, this project aims to make more citation data available to researchers, with a particular focus on the German language social sciences.  It has developed a set of algorithms for the extraction of reference information from PDF documents and for matching the reference entry strings thus obtained against bibliographic databases (see EXCITE git https://github.com/exciteproject/).  It is using as its data sources the following Social Science collections: full texts from SSOAR, the Gesis Social Science Open Access Repository (https://www.gesis.org/ssoar/home/) and scattered pdf stocks from other social science collections including SOLIS, Springer Online Journals and CSA Sociological Abstracts [4, 5].

The EXCITE project organized an international developer and researcher workshop “Challenges in Extracting and Managing References” in March 2017 in Cologne. http://west.uni-koblenz.de/en/research/excite/workshop-2017

EXCITE will then structure the extracted bibliographic and citation data in RDF using the OpenCitations Data Model, and will use the OpenCitations Corpus as its publication platform, employing the OCC EXCITE supplier prefix 0110, described here, to identify the provenance of these citations.

References

[4]       Martin Körner (2016). Extraction from social science research papers using conditional random fields and distant supervision, Master’s Thesis, University of Koblenz-Landau, 2016.

[5]       Körner, M., Ghavimi, B., Mayr, P., Hartmann, H., & Staab, S. (2017). Evaluating reference string extraction using line-based conditional random fields: a case study with german language publications. In M. Kirikova, K. Nørvåg, G. A. Papadopoulos, J. Gamper, R. Wrembel, J. Darmont, & S. Rizzi (Hrsg.), New Trends in Databases and Information Systems (Bd. 767, S. 137–145). Springer International Publishing. https://doi.org/10.1007/978-3-319-67162-8_15   Preprint: https://philippmayr.github.io/papers/Koerner-et-al2017.pdf

3    The Venice Scholar Index

The Venice Scholar Index is a citation index of literature on the history of Venice, indexing nearly 3000 volumes of scholarship from the mid 19th century to 2013, from which some 4 million bibliographic references have been extracted.

The Venice Scholar Index is the first prototype resulting from Linked Books Project (https://dhlab.epfl.ch/page-127959-en.html), a project spearheaded by Giovanni Colavizza and Matteo Romanello of the Digital Humanities Laboratory at EPFL (École Polytechnique Fédérale de Lausanne), with partners in Venice, Milan and Rome.

The project is exploring the history of Venice through references to scholarly literature as well as archival documents found within publications.  To achieve this goal, the project has developed a system to automatically extract bibliographic references found within a large set of digitized books and journals, which has then been applied to the publications on the history of Venice, its main use case [6].

The Linked Books Project is specifically interested in analysing the interplay between citations to primary (e.g. archival) documents and those to secondary sources (scholarly literature), and the citation profiles of publications through time.  To this end, it developed the Venice Scholar Index, a rich search interface to navigate through the resulting network of citations, with the final aim of interlinking digital archives and digital libraries.

The citation data underlying the Venice Scholar Index are modelled using the OpenCitations Data Model, and will use the OpenCitations Corpus as its publication platform, using the OCC Venice Scholar Index supplier prefix 0120 to identify the provenance of these citations.

Reference

[6] Giovanni Colavizza, Matteo Romanello, and Frédéric Kaplan (2017). The references of references: a method to enrich humanities library catalogs with citation data. In International Journal on Digital Libraries 18 (March 8, 2017): 1–11. https://doi.org/10.1007/s00799-017-0210-1.

4    CitEcCyr – Citations in Economics published in CyrillicCitEcCyr  (https://github.com/citeccyr/CitEcCyr) is an open repository of citation relationships obtained from research papers in the Russian language and Cyrillic script from Socionet (https://socionet.ru/) and RePEc (http://repec.org/) [7, 8].  The CitEcCyr project is headed by Oxana Medvedeva, is technically led by Sergey Parinov, and is funded by RANEPA (http://www.ranepa.ru/eng/), the Russian Presidential Academy of National Economy and Public. CitEcCyr is also developing a suite of open software for the citation content analysis of these papers.  This project intends to model its citations using the OpenCitations Data Model, and will use the OpenCitations Corpus as its publication platform, using the OCC CitEcCyr supplier prefix 0140 to identify the provenance of these citations.

However, since this is the first project from which OpenCitations will be importing bibliographic metadata and citations in a language other than English and in a script other than the Latin script, we at OpenCitations are going to have to crawl out of our comfortable ‘Western’ shells and learn to handle foreign languages and scripts other than Latin scripts.

For Russian language papers written using Cyrillic script, we at OpenCitations will to decide how best to handle Russian language written using Cyrillic script, Cyrillic script transliterated into Latin script, and Russian language translated into English and rendered using Latin script.  In particular, since in the OpenCitations Corpus our reference entry records are the uncorrected literal texts of the references in the reference lists of the citing papers, these will need to be recorded as given in Cyrillic.

We will need to develop a policy for when to provide Latin script translations of (for example) titles and abstracts, if these are not provided by the data supplier.  To facilitate use of the OpenCitations Corpus by Russian scholars, we will also need to modify the OpenCitations web site, so as to render the static information displayed in the web pages in the language and script appropriate to the language setting on the user’s web browser.

Unfortunately, all this will take time, so we do not anticipate publishing citation data from the CitEcCyr project within OCC any time soon.  However, this collaboration will be of tremendous value to OpenCitations as well as to CitEcCyr, since the lessons learned by our collaboration with the CitEcCyr project will enable the OpenCitations Corpus to handle citation data not just in Russian, but also in Arabic, Chinese, Japanese and other languages where the Latin script is not used, something that is not found in other major bibliographic databases.

Watch this space!

References

[7]       Jose Manuel Barrueco, Thomas Krichel, Sergey Parinov, Victor Lyapunov, Oxana Medvedeva and Varvara Sergeeva (2017).  Towards open data for the citation content analysis.    https://arxiv.org/abs/1710.00302

[8]       Thomas Krichel (2017). CitEc to CitEcCyr – A stab at distributed citation systems.  Presented at the 2017 EXCITE workshop. http://west.uni-koblenz.de/sites/default/files/research/projects/excite/workshop-2017/slides/excite-workshop-2017_krichel_citec-to-citeccyr.pdf

Oxford University Press opens its references!

Good news!  Today, on January 16th 2018, Oxford University Press (OUP) announced its participation in the Initiative for Open Citations, and requested Crossref to turn on reference sharing for all OUP deposited references from more than half a million publications.  Oxford University Press is the largest university press in the world, publishing in 70 languages and 190 countries.

OUP logo

Their announcement is at https://academic.oup.com/journals/pages/announcements_from_oup/oup_joins_I4OC.

OUP now joins the elite band of four university presses that have already made their references open at Crossref in response to the I4OC call (https://i4oc.org/#publishers).

This decision by OUP has been a long time in gestation – see my 2012 post Oxford University Press to support Open Citations – but is no less welcome for that!

The Sloan Foundation funds OpenCitations

The OpenCitations Enhancement Project funded by Sloan

The Alfred P. Sloan Foundation, which funds research and education in science, technology, engineering, mathematics and economics, including a number of key technology projects relating to scholarly communication, has agreed to fund The OpenCitations Enhancement Project, a new project to develop and enhance the OpenCitations Corpus.

As readers of this blog will know, the OpenCitations Corpus is an open scholarly citation database that freely and legally makes available accurate citation data (academic references) to assist scholars with their academic studies, and to serve knowledge to the wider public.

Objectives

The OpenCitations Enhancement Project, funded by the Sloan Foundation for 18 months from May 2017, will make the OpenCitations Corpus (OCC) more useful to the academic community both by significantly expanding the volume of citation data held within the Corpus, and by developing novel data visualizations and query services over the stored data.

At OpenCitations, we will achieve these objectives in the following ways:

(a) By establishing a new powerful physical server to handle the Corpus data and offer adequate performance for query services.

(b) By increasing the rate of data ingest into the Corpus, by integrating with server 30 small data-ingest computers, Raspberry Pi 3Bs, working in parallel to harvest references, thus increasing the current rate of corpus data ingest some thirty-fold to about half a million citation links per day.

(c) By employing a post-doctoral computer science research engineer specifically to develop information visualisation interfaces and sense-making tools that will both provide smart ways of envisaging and comprehending the citation data stored within the OpenCitations Corpus, and will also ease the task of manual curation of the OCC.

Personnel

This post-doctoral appointment will start in the autumn of 2017, once the new hardware has been commissioned and programmed. We seek a highly intelligent, skilled and motivated individual who is an expert in Web Interface Design and Information Visualization, and who can demonstrate a commitment to increasing the openness of scholarly information. A formal advertisement for this post, which will be held at the University of Bologna in Italy under the supervision of Dr Silvio Peroni, will be published in the near future. In the mean time, individuals with the relevant skills and background who would like to express early interest in joining the OpenCitations team in this role should contact him by e-mail to <silvio.peroni@opencitations.net>.

Expected Outcomes

By the end of the OpenCitations Enhancement Project, we will have harvested approximately 190 million citation links obtained from the reference lists of about 4.4 million scholarly articles (~15% of Web of Science’s coverage). In this way, in a significant initial step towards the comprehensive literature coverage we seek for the OCC, we will establish the OpenCitations Corpus as a valuable and persistent free-to-use global scholarly on-line Linked Open Data service.

In so doing, we aim at empower the global community by liberating scholarly citation data from their current commercial shackles, publishing such data with a Creative Commons CC0 Public Domain Dedication that will enable novel third-party services to be built over them.

Three publications describing the Open Citations Corpus

Last September, I attended the Fifth Annual Conference on Open Access Scholarly Publishing, held in Riga, at which I had been invited to give a paper entitled The Open Citations Corpus – freeing scholarly citation data.  A recording of my talk is available here, and my PowerPoint presentation is separately available here.  My own reflections on the major themes of the conference are given in a separate Semantic Publishing Blog post.

While in Riga preparing to give that talk about the importance of open citation data, I received an invitation from Sara Abdulla, Chief Commissioning Editor at Nature, to write a Comment piece for their forthcoming special issue on Impact.  My immediate reaction was that this should be on the same theme, an idea to which Sara readily agreed.  The deadline for delivery of the article was 10 days later!

As soon as the Riga conference was over, I first assembled all the material I had to hand that could be relevant to describing the Open Citations Corpus (OCC) in the context of conventional access to academic citation data from commercial sources.  That gave me a raw manuscript of some five thousand words, from which I had to distil an article of less than 1,300 words.  I then started editing, and asked my colleagues Silvio Peroni and Tanya Gray for their comments.

The end result, enriched by some imaginative art work by the Nature team, was published a couple of weeks later on 16th October [1], and presents both the intellectual argument for open citation data, and the practical obstacles to be overcome in achieving the goal of a substantial corpus of such data, as well as giving a general description of the Open Citations Corpus itself and of the development work we have planned for it.

Because of the drastic editing required to reduce the original draft to about a quarter of its size, all material not crucial to the central theme had to be cut.  I thus had the idea of developing the original draft subsequently into a full journal article that would include these additional themes, particularly Silvio’s work on the SPAR ontologies described in this Semantic Publishing Blog post [2], Tanya’s work on the CiTO Reference Annotation Tools described in this Semantic Publishing Blog post, and a wonderful analogy between the scholarly citation network and Venice devised by Silvio.  I also wanted to give authorship credit to Alex Dutton, who had undertaken almost all of the original software development work for the OCC.  For this reason, instead of assigning copyright to Nature for the Comment piece, I gave them a license to publish, retaining copyright to myself so I could re-use the text.  I am pleased to say that they accepted this without comment.

Silvio and I then set to work to develop the draft into a proper article.  The result was a ten-thousand word paper submitted to the Journal of Documentation a week before Christmas [3].  We await the referees’ comments!

 References

[1]     Shotton D. (2013).  Open citations.  Nature 502: 295–297. http://www.nature.com/news/publishing-open-citations-1.13937. doi:10.1038/502295a.

[2]     Peroni S and Shotton D (2012). FaBiO and CiTO: ontologies for describing bibliographic resources and citations. Web Semantics: Science, Services and Agents on the World Wide Web. 17: 33-34. doi:10.1016/j.websem.2012.08.001.

[3]    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

This is the main article about OpenCitations, which includes several background information and the main ideas and works supporting the whole project, the Corpus, and some possible future developments in terms of new kinds of data to be included, e.g. citation functions.

 

Open Citations Corpus Import Process

As part of the Open Citations project, we have been asked to review and improve the process of importing data into the Open Citations Corpus, taking the scripts from the initial project as our starting point.

The current import procedure evolved from several disconnected processes and requires running multiple command line scripts and transforming the data into different intermediate formats. As a consequence, it is not very efficient and we will be looking to improve on the speed and reliability of the import procedure. Moreover, there are two distinct procedures depending on the source of the data (arXiv or PubMed Central); we are hoping to unify the common parts of these procedures into a single process which can be simplified and normalised to improve code re-use and comprehensibility.

The Workflow

As PubMed Central provides an OAI-PMH feed, this could be used to retrieve article metadata, and for some articles, full text. Using this feed, rather than an FTP download (as used currently) would allow the metadata import for both arXiv and PubMed Central to follow a near-identical process, as we are already using the OAI-PMH feed for arXiv.

Also, rather than have intermediate databases and information stores, it would be cleaner to import from the information source straight into a datastore. The datastore could then be queried, allowing matches and linking between articles to be performed in situ. The process would therefore become:

  1. Pull new metadata from arXiv (OAI-PMH) and PubMed Central (OAI-PMH) and insert new records into the Open Citations Corpus datastore
  2. Pull new full-text from arXiv and PubMed Central, extract citations, and match with article data in Open Citations server, creating links between these references and the metadata records for the cited articles. Store unmatched citations as nested records in the metadata for each article.
  3. On a scheduled basis (e.g. nightly), review each existing article’s unmatched citations and attempt to match these with existing bibliographic records of other articles.

In outline, this looks like this:

The Datastore

Neo4J is currently used as the final Open Citations Corpus datastore for the arXiv data, by the Related Work system. We propose instead to use BibServer as the final datastore, for its flexibility and scalability, and suitability for the Open Citations use cases.

The Data Structure

The data stored within BibServer as BibJSON will be a collection of linked bibliographic records describing articles. Associated with each record and stored as nested data will be a list of matched citations (i.e. those for which the Open Citations Corpus has a bibliographic record), a list of unmatched citations, and a list of authors.

Authors will not be stored as separate entities. De-coupling and de-duplicating authors and articles could form the basis of a future project, perhaps using proprietary identifiers (such as ORCHID, PubMed Author ID or arXiv Author ID) or email addresses, but this will not be considered further in this work package.

Overall Aim

The overall aim of this work is to provide a consistent, simple and re-usable import pipeline for data for the Open Citations Corpus. In the fullness of time we’d expect it to be possible to add new data sources with minimal additional complexity. By using an approach whereby data is imported into the datastore at as early a stage as possible in the import pipeline, we can use common tools for extracting, matching, deduplicating citations; the work for each datasource, then, is just to convert the source data format into BibJSON and store it in BibServer.

Postscript

David Shotton writes: This productive collaboration between Cottage Labs and the Open Citations Corpus came to an end when Jisc funding ran out.  The corpus has more recently been given a new lease of life, as described here, with a new instantiation named OpenCitations hosted at the Department of Computer Science and Engineering of the University of Bologna, with Silvio Peroni as Co-Director.