Elsevier endorses DORA and opens its journal article reference lists

We congratulate and thank Elsevier, the world’s largest academic publisher, for endorsing the DORA Declaration on Research Assessment (https://sfdora.org/), thereby joining the hundreds of other publishers and scientific organizations which have endorsed DORA over the previous eight years, and also for making a commitment to open the references from all its journal articles submitted to Crossref. The text of Elsevier’s endorsement, dated 16th December 2020, is to be found at https://www.elsevier.com/connect/advancing-responsible-research-assessment, and includes the statement:

“We will make reference lists for all articles published in Elsevier journals openly available via Crossref so they can be available for reuse. This means other important initiatives like I4OC can draw on this metadata.”

Particular thanks are due to Kumsal Bayazit, Elsevier’s CEO, and to Andrew Plume, head of Elsevier’s International Center for the Study of Research (ICSR), for spearheading this change in stance on the part of Elsevier, which until this week has been alone among the major scholarly publishers in keeping its reference lists at Crossref closed, for which it has attracted much criticism from the academic community.

This change of heart on the part of Elsevier now means that by next spring, after Crossref has had a chance to implement this change in status over the large corpus of Elsevier journal metadata, the reference lists of articles in the vast majority of the world’s academic journals will be open, enabling such metadata to be used to enhance publication discovery and enable transparent research assessment.  The I4OC web site and COCI, OpenCitations Index of Crossref open DOI-to-DOI citations, will reflect this change once it has happened.

The Institute of Electrical and Electronics Engineers (IEEE), the American Chemical Society (ACS), and the University of Chicago Press now stand alone as the only significant scholarly publishers who choose not to make their publication reference lists open.

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:070433-070475/46 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

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!

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.

Taylor & Francis to open article reference lists

I am very pleased to announce that last year Ian Bannerman, Managing Director for Journals at Taylor & Francis, confirmed this publisher’s willingness to pilot the opening of the reference lists from articles in 29 of their subscription access journals, as well as from all of their current list of 15 Open Access journals, for inclusion in the Open Citations Corpus.  The reference lists for these journals are already being supplied to CrossRef as part of the CrossRef CitedBy Linking service, and will be made available publicly via the CrossRef XML query API.

Taylor & Francis is a major international publisher of over 1,000 academic journals and more than 1,800 books per year, incorporating well-known publishing names including Bios Scientific Publishing, CRC Press, Garland Science, Marcel Decker and Routledge.  It is the largest publisher of subscription access journals yet to agree to make reference lists available from its journal articles, and I welcome them warmly into the Open Citations fold.

Incorporation of new reference data from Taylor and Frances journals into the Open Citations Corpus will commence in the near future.

Open Citations Extension Project

I am pleased to announce that the JISC have funded an extension to the Open Citations Project to run from 1st August 2012 until 31st January 2013, during which we will review and revise the technology used to create the Open Citations Corpus, will update the content provided by PubMed Central, and will improve its presentation.  We will also prototype value-added services over the open citations data, to demonstrate their usefulness and to justify further funding that will permit a major expansion of the corpus in 2013 to include reference lists from subscription-access journals, including those from Nature Publishing Group, Science and other AAAS publications, and Oxford University Press.  In preparation for this, we will collaborate with CrossRef to determine how best to ingest reference data into the Open Citations Corpus in an on-going manner.

Full details are given in the Case for Support.  Watch this space!

Oxford University Press to support Open Citations

I am delighted to announce that Cathy Kennedy, OUP’s Senior Publisher for Journals, has just written to me as follows:

“Oxford University Press is delighted to support the Open Citation Corpus initiative in the interest of furthering and disseminating scholarship.  We are making the reference lists of articles in a number of journals we own available for inclusion in the Open Citations Corpus, and will be consulting further with our partner societies on extending the initiative to include their journals in due course”.

OUP thus becomes the third publisher of subscription-access journals, and the first university press, to declare its willingness to make the reference lists in journal articles publicly available.  Congratulations, OUP!

Are we starting to see the beginning of a sea change in attitudes?  Watch this space.

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