Using the ORCID Public API for author disambiguation in the OpenCitations Corpus

Among the external services used, the ORCID Public API is of crucial importance for the task of author disambiguation. During the OCC ingestion workflow, the main metadata of an article are usually retrieved from the Crossref API. While the JSON schema used by Crossref to return the information requested by its APIs includes a field for specifying the ORCID for each of the authors of an article, this field is usually blank, since such information is commonly not available in the data provided by publishers. We therefore routinely use the ORCID Public API to try to retrieve ORCIDs for all authors and editors named in the Crossref metadata for a given DOI.

The process is organised as follows. Once we get back from Crossref the metadata about an article, we call the ORCID Public API and search for ORCIDs associated with the family names returned by Crossref of all the authors and editors (‘agents’) associated with that particular DOI. For instance, using the Crossref metadata about the article with DOI “10.1108/jd-12-2013-0166” (API call: https://api.crossref.org/works/10.1108/jd-12-2013-0166), we extract all the agents’ family names and call the ORCID Public API as follows:

https://pub.orcid.org/v2.1/search?q=(doi-self:10.1108/JD-12-2013-0166%20OR%20doi-self:10.1108/jd-12-2013-0166)%20AND%20(family-name:Peroni%20OR%20family-name:Dutton%20OR%20family-name:Gray%20OR%20family-name:Shotton)

The result of this query returned by ORCID is as follows:

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<search:search num-found="2" 
  xmlns:search="http://www.orcid.org/ns/search" 
  xmlns:common="http://www.orcid.org/ns/common">
  <search:result>
    <common:orcid-identifier>
      <common:uri>https://orcid.org/0000-0003-0530-4305</common:uri>
      <common:path>0000-0003-0530-4305</common:path>
      <common:host>orcid.org</common:host>
    </common:orcid-identifier>
  </search:result>
  <search:result>
    <common:orcid-identifier>
      <common:uri>https://orcid.org/0000-0003-1448-3114</common:uri>
      <common:path>0000-0003-1448-3114</common:path>
      <common:host>orcid.org</common:host>
    </common:orcid-identifier>
  </search:result>
</search:search>

Then, for each ORCID returned, we call again the ORCID Public API, shown as follows for ORCID “0000-0003-0530-4305”, so as to get the full personal details of the agent with that ORCID:

https://pub.orcid.org/v2.1/0000-0003-0530-4305/personal-details

The result of this query is shown as follows:

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<personal-details:personal-details
  path="/0000-0003-0530-4305/personal-details"
  xmlns:personal-details="http://www.orcid.org/ns/personal-details"
  ...>
  <personal-details:name 
    visibility="public" path="0000-0003-0530-4305">
    ...
    <personal-details:given-names>
      Silvio
    </personal-details:given-names>
    <personal-details:family-name>
      Peroni
    </personal-details:family-name>
  </personal-details:name>
  ...
</personal-details:personal-details>

Then, two possible alternative situations exist:

  • If the OpenCitations Corpus has already recorded the personal details and ORCID of that agent, we associate that agent with the new bibliographic resource identified by the input DOI; otherwise,
  • If the personal details and ORCID of that agent have not been previously recorded in the OpenCitation Corpus, we create a new agent record with that ORCID as external identifier, specified by means of the DataCite Ontology, and we associate this new agent with the new bibliographic resource identified by the input DOI.
  • This process is repeated for all ORCIDs associated with that DOI.

Software reuse in different applications

While the OCC ingestion workflow explained above regulates the ingestion of new citation data directly into the OpenCitations Corpus, the particular software library that implements this ingestion is generic in form, and is being reused in another application that we have recently released in prototype, namely BCite (sources available on GitHub). BCite is a Web application that enables users such as journal editors, starting with the ‘raw’ reference text strings supplied by the author as items in an article’s reference list, to obtain ‘clean’ verified and enriched bibliographic reference text strings, for inclusion in the reference list of the citing article they have in hand, so that accurate rather than erroneous references can be published in the version of record.  Additionally, these references are at the same time transformed into RDF data compliant with the OpenCitation Data Model, including ORCIDs where available, thereby (in principle, although not yet in practice) permitting inclusion of the metadata for these cited works, and the citations for which they are the targets, into the OpenCitations Corpus itself.

The OpenCitations Enhancement Project – final report

The OpenCitations Enhancement Project
Final report for the Alfred P. Sloan Foundation

Report period: 1st May 2017 – 30 November 2018.
Report written: 30th December 2018

Background

OpenCitations (http://opencitations.net) is a scholarly infrastructure organization dedicated to open scholarship and the publication of open bibliographic and citation data by the use of Semantic Web (Linked Data) technologies, and engaged in advocacy for semantic publishing and open citations [Peroni and Shotton, 2018b]. It provides the OpenCitations Data Model [Peroni and Shotton, 2018d], the SPAR (Semantic Publishing and Referencing) Ontologies [Peroni and Shotton, 2018e] for encoding scholarly bibliographic and citation data in RDF, and open software of generic applicability for searching, browsing and providing APIs over RDF triplestores. It has developed the OpenCitations Corpus (OCC) [Peroni et al., 2017] of open downloadable bibliographic and citation data recorded in RDF, and a system and resolution service for Open Citation Identifiers (OCIs) [Peroni and Shotton, 2018c], and it is currently developing a number of Open Citation Indexes using the data openly available in third-party bibliographic databases.

The Directors of OpenCitations are David Shotton, Oxford e-Research Centre, University of Oxford (david.shotton@opencitations.net), and Silvio Peroni, Digital Humanities Advanced Research Centre, Department of Classical Philology and Italian Studies, University of Bologna (silvio.peroni@opencitations.net). We are committed to open scholarship, open data, open access publication, and open source software. We espouse the FAIR data principles developed by Force11, of which David Shotton was a founding member (https://www.force11.org/group/fairgroup/fairprinciples), and the aim of the Initiative for OpenCitations (I4OC, https://i4oc.org), of which both David Shotton and Silvio Peroni were founding members, to promote the availability of citation data that is structured, separable, and open.

Project personnel and roles

Ivan Heibi – Research Fellow

Ivan Heibi was appointed to the 12 months Research Fellowship position funded by the Sloan Foundation.

Ivan has been responsible for the development of new visualization and programming interfaces for exploring and making sense of the citation data included in the OCC and in the new OpenCitations Indexes, for the main part of the scripts related to the population and regular maintenance of COCI (The OpenCitations Index of Crossref open DOI-to-DOI citations, the first of the OpenCitations Indexes), and for conference presentations and paper writing.

Silvio Peroni – Lead Applicant and Principal Investigator

Silvio has been responsible for project management, for interview, appointment and supervision of the work of Ivan Heibi, for all aspects of software coding and technical developments required for the OpenCitations Corpus (OCC), the OpenCitations Indexes, and the Open Citation Identifier Resolution Service, for the ordering and management of new Sloan-funded hardware, and for conference presentations, paper writing and other forms of outreach and dissemination (e.g. blog and social networks).

David Shotton – Consultant Co-Investigator

David has been responsible for project management, interaction with publishers, conference presentations, paper writing, other forms of outreach and dissemination (e.g. blog and social networks), for web site and data model revision, and for independent usability evaluation, stress-testing and design feedback of new user interfaces and applications.

Project management

Project management has been straightforward, as should be the case, given the small size of our team. It has involved more than 1500 e-mail exchanges between David Shotton and Silvio Peroni, about 500 e-mail exchanges between Silvio Peroni and Ivan Heibi since November 2017, two dozen or so video conferences, some of which have involved collaborators, and an extended face-to-face meeting during the WikiCite 2017 Conference in Vienna at the start of the project and the Workshop on Open Citations 2018 in Bologna.

We have together harmoniously developed the concept of and vision for OpenCitations as an infrastructure organization, the structure and content of the OpenCitations web site (http://opencitaitons.net), the classes and properties of our supporting SPAR ontologies (http://www.sparontologies.net), and the community of collaborators and users of our developments. This has involved outreach and dissemination at a number of international research conferences, involvement with publishers through the Initiative for Open Citations, and associated publications.

We have studied and preliminarily tested a new scalable architecture centred on one powerful independent physical server, that both stores and handles all the data in the Corpus and in the new OpenCitations Indexes, and also offers adequate performance for query services. This server is supplemented by 30 additional small physical machines, Raspberry Pi 3Bs, working in parallel, each in charge of ingesting a defined set of reference lists and feeding the ingested data to the central server for further processing and storage as RDF in our Blazegraph triplestore.

Current status of the OpenCitations services

Currently, we release two different datasets – the OpenCitations Corpus and COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations – and several interfaces so as to make these data queryable from different access points.

Functionality and holdings

As of 29th December 2018, the OpenCitations Corpus (OCC) contains information about 13,964,148 citation links to 7,565,367 cited resources, ingested from 326,743 citing bibliographic resources obtained from the Open Access corpus of Europe PubMed Central and from the citation data imported from the EXCITE project. The main part of the development effort in the past months has been spent in implementing ingestion strategies that allow partners to provide us citation data, stored according the OpenCitations Data Model [Peroni and Shoton, 2018b], so as to be added directly into the Corpus. In September 2018, we successfully completed the ingestion of the initial data coming from the EXCITE project (citations from social sciences scholarly papers published by German publishers), and we are actively interacting with the LOC-DB project and the Venice Scholar Index so as to add their data to the OCC as well. In ongoing work, we are also collaborating with arXiv and EXCITE to harvest all the references from all PDF documents in the arXiv ePrints collection, to record these in RDF according to the OpenCitations Data Model, and to ingest them into the OpenCitations Corpus, as well as creating a new Index of these citations.

The first of these OpenCitations Indexes is COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations, an RDF dataset containing details of all the citations that are specified by the open references to DOI-identified works present in Crossref, as of the latest COCI update. COCI does not index Crossref references that are closed, nor Crossref references to entities that lack DOIs. These citations are treated as first-class data entities, with accompanying properties including the citations timespan and possible kinds of self-citation characteristics, modelled according to the index data model described in the OpenCitations Indexes page. COCI was launched in July 2018, and the most recent update of COCI is dated 12 November 2018. It presently contains 449,840,503 citations between 46,534,705 bibliographic resources. COCI is the first citation index released by OpenCitations, being a bibliographic index recording citations between publications that permits the user to establish which later documents cite earlier documents, and to create citation graphs of these citations.).

While full coverage of the scholarly citation graph depicted by the aforementioned datasets (or as full as practically possible) is required for the calculation of certain bibliometric indicators such as journal impact factors and individual h-indexes (Hirsch numbers), partial coverage while OCC grows is still of value, since it includes citations of all the most important biomedical papers obtained from the Open Access Subset off PubMed Central. These can be easily recognized by their large number of inward citation links, and can be used to explore the development of disciplines and research trends. In addition, COCI, with its wider scope, has sufficient coverage to be used for large-scale bibliometrics analysis.

Purchase of new hardware, and testing and development of new software

Because of unavoidable academic teaching commitments for Silvio Peroni, the installation of the new Sloan-funded hardware for OCC, purchased in autumn 2017, had to be postponed. All the services (old and new) of OpenCitations were successfully transferred to our new server in October 2018. In order to implement such transition, the ingestion process of the OCC was halted, so as to allow Silvio Peroni to properly test the new hardware and to extend the existing ingestion software so as to be usable within the new parallel processing architecture. The final tests are currently running, and we will recommence the full ingestion process of the OCC using the new hardware configuration, with its greatly enhanced ingest rate, in January 2019. In the meantime, the new infrastructure has been used to allow us to create COCI, so far the largest RDF dataset of open citation data available worldwide.

In addition, we have completed the transition of all the OpenCitations software from the old GitHub repository (i.e. https://github.com/essepuntato/opencitations) to a new GitHub organization, namely https://github.com/opencitations. This organisation includes several repositories which permit third parties to initiate the whole suite of OpenCitations software on a local machine. This is of key importance for the resilience of this open source project.

User interfaces

SPARQL, the query language used to interrogate RDF triplestores, is a quite powerful language. However, one needs appropriate skills with Semantic Web technologies to master it for solving even easy search tasks. Thus normal web users are unable to use appropriately such technologies if not appropriately instructed, leaving all these technologies in the hands of a limited number of experts. The datasets made available by OpenCitations suffered similar issues.

Initially, the goal we had was to develop ad-hoc user interfaces to abstract the complexities of the SPARQL endpoints into well-designed Web interfaces that anyone could use. During the development, though, we thought it would be better to develop generic frameworks for building customizable interfaces that allow one to expose, in a more human-understandable way, RDF data stored in any RDF triplestore and accessible through any SPARQL-endpoint, so as to forster reuse of such software in contexts that, in principle, might go far beyond the OpenCitations domain.

To this end we developed three different open software applications:

  • OSCAR [Heibi et al., 2018a] [Heibi et al., 2018b], a Javascript application for creating textual search interfaces to RDF data;
  • LUCINDA, another Javascript application for creating Web browsers over RDF data;
  • RAMOSE, a Python application that permits one to easily create and serve a conventional HTTP REST API over a SPARQL endpoint.

All these tools provide a configurable mechanism – by means of one single textual configuration file – that allows one to generate Web-based interfaces to any SPARQL endpoint. In practice, these tools are flexible Web-interface makers to RDF data, and as such represent a significant advance available to the entire community.

All these applications have been used to produce several interfaces to all the datasets released by OpenCitations. In particular, we have created user-friendly textual search interfaces (via OSCAR) both for the OCC (see the search box now on the OpenCitations home page, and the related search page) and for COCI (see the related search page). We have additionally developed browsing applications (via LUCINDA) to permit humans an easier navigation of all the entities included in the OCC (e.g. see the bibliographic resource br/1791056) and in COCI (e.g. see the citation oci:02001010806360107050663080702026306630509-02001010806360107050663080702026305630301). Finally, we have also implemented REST HTTP APIs (via RAMOSE) for simplifying the queries to both datasets, the OCC and COCI, by Web developers with no expertise in Semantic Web technologies.

In addition, in order to demonstrate its flexibility, we have also created two web pages using OSCAR, LUCINDA, and RAMOSE for permitting similar tasks (text query, browsing, and REST APIs) on the scholarly data in Wikidata / WikiCite – another project recently funded by the Alfred P. Sloan Foundation. These interfaces have been introduced in two distinct event: during the hack day of the Workshop on Open Citations 2018 and during the WikiCite 2018 Conference.

A further prototypical interface / service has been recently proposed so as to try to gather additional open citation data to include in the OCC, involving users of the scholarly domain such as editors and researchers. This application is called BCite [Daquino et al., 2018]. BCite is designed to provide a full workflow for citation discovery, allowing users to specify the references as provided by the authors of an article, to retrieve them in the required format and style, to double-check their correctness, and, finally, to create new open citation data according to the OpenCitations Data Model [Peroni and Shotton, 2018d], so as to permit their future integration into the OCC. While presently only a prototype, we received several commendations for this tool, and we are currently studying funding strategies to develop a full standalone application that can be used by anyone and that allows users to directly interact with the OCC, so as to upload new data into the Corpus.

Open Citation Identifiers

During the reporting period, it became increasingly evident to us that citations deserved treating as First Class Data Entities, which would give the following advantages:

  • All the information regarding each citation would be available in one place.
  • Citations become easier to describe, distinguish, count and process.
  • If available in aggregate, citations become easier to analyze using bibliometric methods, for example to determine how citation time spans vary by discipline.

Four developments were required to make this possible:

  • The metadata describing the citation must be definable in a machine-readable manner.
  • Such metadata must be storable, searchable and retrievable.
  • Each citation must be identifiable, using a globally unique Persistent Identifier.
  • There must be a Web-based resolution service that takes the identifier as input and returns a description of the citation.

To this end, we have achieved:

  • the first requirement by the addition of appropriate classes and properties to CiTO, the Citation Typing Ontology, and by the addition of a new member of the class datacite:ResourceIdentifierScheme in the DataCite Ontology, namely Open Citation Identifier;
  • the second requirement by modifying the OpenCitations Data Model [Peroni and Shotton, 2018d] so that citations can be properly described using these new ontology terms within the OpenCitations Corpus;
  • the third requirement by creating the syntax for this new Open Citation Identifier (OCI) [Peroni and Shotton, 2018c], and enabling the creation of such identifiers, both to specify citations within the OpenCitations Corpus, and also (importantly) to specify citations described in Wikidata (by QIDs) and in Crossref (by DOIs); and
  • the fourth requirement by creating a resolving service for OCIs at http://opencitations.net/oci and additional software (in Python) for retrieving information about a particular citation identified by an OCI.

To date, OCIs have been actively used both in the OCC and in COCI to identify all the citations they contain. In addition, we now plan to create and publish additional OpenCitations Indexes of all the citations DataCite, Wikidata and (of course) the OCC, which we hope will be of great benefit to bibliometricians in their analysis of citation networks, self-citation, etc., and in the calculation of citation metrics. OCIs have been recognised by the EU Project FREYA as unique global identifiers for bibliographic citations.

Collaborations and Users

OpenCitations Data Model

We are collaborating with the following groups and academic projects, both to promote the use of the OpenCitations Data Model (OCDM), and to provide a publication venue for the citation data that they are liberating from the scholarly literature:

  • Matteo Romanello of the Digital Humanities Laboratory at the University of Lausanne is using OCDM for modelling citations of the classical literature within ancient Venetian documents in the context of the Venice Scholar Index, and is currently working on producing a dataset of citation data compliant with OCDM so as to be ingested in the OCC.
  • Two DFG-funded German projects that are extracting citations from Social Science publications:
    • The Linked Open Citations Database (LOC-DB) at the University of Mannheim is using OCDM to model their data, with the aim of producing them accordigly with such model so as to be ingested in the OCC.
    • Steffen Staab (University of Koblenz) and Philipp Mayr (GESIS) are running the EXCITE Project, which uses OCDM to model their citation data, and already adopted the OCC as their publication platform. In fact, in September 2018, ~1 million citations coming from the EXCITE Project were successfully ingested in the OCC.
  • Sergey Parinov is technically leading CitEcCyr, which is an open repository of citation relationships obtained from research papers in the Russian language and Cyrillic script. This project intends to model its citations using the OCDM, and will use the OpenCitations Corpus as its publication platform.

Users of OpenCitations data

The following project and organizations have let us know that they are using data from the OCC and COCI:

  • Wikidata includes alignments between several bibliographic entries with OCC resources;
  • OpenAIRE imported OCC metadata about articles into their LOD database;
  • Daniel Ecer and Lisa Knoll of eLife performed analytics on the OCC data;
  • Ontotext demonstrated SPARQL query federation between Springer Nature LOD and OCC;
  • Anna Kamińska published a bibliometrics case study of PLOS ONE articles in OCC;
  • Daniel Himmelstein processed OpenCitations data to create DOI-to-DOI citation tables;
  • Thiago Nunes and Daniel Schwabe are using OCC to exemplify their XPlain framework;
  • Antonina Dattolo and Marco Corbatto are using the OCC as source for VisualBib framework;
  • Nees Jan van Eck and Ludo Waltman extended VOSviewer so as to use data in the OCC + COCI, that will be officially published in the next release of the tool;
  • Barney Walker developed Citation Gecko, a graph-based citation discovery tool based on the OCC and COCI for retrieving citation data about the papers;
  • Philipp Zumstein developed a Zotero plugin that gives information about open citations using COCI;
  • Dominique Rouger developed a Web application that provides a visual graph representation of citation links in COCI.

Website statistics

From May 2017 to November 2018, the official OpenCitations website has been accessed ~5.8M times – we have excluded from this list the hits done by well-known spiders and crawlers. It is worth mentioning that the pages related to the data available and the services for querying them (i.e. “/corpus”, “/sparql”, and “/index” in the following diagram) have together gained a very high percentage of the overall accesses, showing that the main reason people access the OpenCitations website is to explore and use the data in the OCC and in COCI. It is also clear how the introduction of COCI brought additional accesses to the OpenCitations services, and the trend is increasing – e.g. in December 2018 (not shown in the following diagram) we got more than 200M accesses to “/index”, mainly related to the use of the COCI REST APIs.

Community outreach

From May 2017 to November 2018, the documents (i.e. [Peroni and Shotton, 2018b] [Peroni and Shotton, 2018c] [Peroni and Shotton, 2018d]) and the dumps of the OCC and of COCI available on Figshare (see http://opencitations.net/download) have been viewed 37,960 times and downloaded 3,842 times. The figure below summarizes how many views and downloads such resources have received month by month. For example, the latest version of COCI in CSV has been downloaded 239 times since its release in November (see https://doi.org/10.6084/m9.figshare.6741422.v3).

In the past nineteen months, the posts published by the official Twitter account of OpenCitations have been engaged by 599,200 distinct Twitter accounts, the Twitter profile (@opencitations) has been visited 12,719 times and has been mentioned in 565 tweets written by others, and it has collected an additional 1,925 followers. The diagram below shows all these statistics month by month.

Although we made relatively few new blog posts in the reporting period (there have been twenty more since then), from May to November 2018, the blog dedicated to OpenCitations (http://opencitations.wordpress.com) received 19,454 visits by 15,184 distinct users. As shown in the diagram below, the biggest peaks in terms of visits has been in July 2018 (the month when we launched COCI) and in September 2018 (the month of the Workshop on Open Citations).

Users of the SPAR Ontologies

The SPAR Ontologies [Peroni and Shotton, 2018e] are in use by about 40 other projects and organizations, including:

  • The United States Global Change Information System, which encodes federal information relating to climate change, makes extensive use of SPAR ontology terms.
  • The United Nations Document Ontology (UNDO) has been specifically aligned with FaBiO.
  • Wikidata has many classes that have been alighted with FaBiO or CiTO.
  • DBPedia’s DataID ontology uses the FaBiO and DataCite ontologies.
  • W3C’s Data on the Web Best Practices: Dataset Usage Vocabulary uses SPAR Ontologies.

For the full list, see http://www.sparontologies.net/uptake.

To date, as far as we are aware, more than 677 papers have been published that cite or use one or more of the SPAR ontologies. For the full list, see http://www.sparontologies.net/uptake#publications.

OpenCitations and the Initiative for Open Citations

OpenCitations and the Initiative for Open Citations, despite the similarity of title, are two distinct organizations. The primary purpose of OpenCitations is to host and build the OpenCitations Corpus (OCC) and the OpenCitations Indexes, as long as additional service to browse, query, and analyse citation data. In contrast, the Initiative for Open Citations (I4OC, https://i4oc.org) is separate and independent organization, whose founding was spearheaded by Dario Taraborelli of the WikiMedia Foundation. OpenCitations is one of several founding members of the Initiative for Open Citations, as documented at https://i4oc.org/#founders. I4OC is a pressure group to promote the unrestricted availability of scholarly citation data, but does not itself host citation data.

Because open reference lists are necessary for the population of OCC, we at OpenCitations have devoted considerable effort to promoting I4OC’s aims, and we host the I4OC web site on behalf of that community.

Within a short space of time, I4OC has persuaded most of the major scholarly publishers to open their reference lists submitted to Crossref, so that the proportion of all references submitted to Crossref that are now open has risen from 1% to over 50%. These are now available for OpenCitations to harvest into the OpenCitations Corpus and publish in RDF, as well as for others to harvest and use as they wish [Shotton, 2018].

Publications during the reporting period

Scholarly papers

Marilena Daquino, Ilaria Tiddi, Silvio Peroni, David Shotton (2018). Creating Open Citation Data with BCite. In Emerging Topics in Semantic Technologies – ISWC 2018 Satellite Events: 83-93. DOI: https://doi.org/10.3233/978-1-61499-894-5-83, OA at http://ceur-ws.org/Vol-2184/paper-01.pdf

Ivan Heibi, Silvio Peroni, David Shotton (2018). Enabling text search on SPARQL-endpoints through OSCAR. Submitted for publication to Data Science – Methods, Infrastructure, and Applications. OA at at https://w3id.org/people/essepuntato/papers/oscar-datascience2019/

Ivan Heibi, Silvio Peroni, David Shotton (2018). OSCAR: A Customisable Tool for Free-Text Search over SPARQL Endpoints. In Semantics, Analytics, Visualization – 3rd International Workshop, SAVE-SD 2017, and 4th International Workshop, SAVE-SD 2018, Revised Selected Papers: 121-137. DOI: https://doi.org/10.1007/978-3-030-01379-0_9, OA at https://w3id.org/people/essepuntato/papers/oscar-savesd2018.html

Silvio Peroni, David Shotton (2018). OpenCitations: enabling the FAIR use of open citation data. In Proceedings of the GARR Conference 2017 – The data way to Science – Selected Papers. DOI: https://doi.org/10.26314/GARR-Conf17-proceedings-19

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

Silvio Peroni, David Shotton, Fabio Vitali (2017). One year of the OpenCitations Corpus: Releasing RDF-based scholarly citation data into the Public Domain. In Proceedings of the 16th International Semantic Web Conference (ISWC 2017): 184-192. DOI: https://doi.org/10.1007/978-3-319-68204-4_19, OA at https://w3id.org/people/essepuntato/papers/oc-iswc2017.html

David Shotton (2018). Funders should mandate open citations. Nature 553: 129. https://doi.org/10.1038/d41586-018-00104-7

Additional documents

Silvio Peroni, David Shotton (2018). Open Citation: Definition. Figshare. DOI: https://doi.org/10.6084/m9.figshare.6683855.v1

Silvio Peroni, David Shotton (2018). Open Citation Identifier: Definition. Figshare. DOI: https://doi.org/10.6084/m9.figshare.7127816.v1

Silvio Peroni, David Shotton (2018). The OpenCitations Data Model. Figshare. DOI: https://doi.org/10.6084/m9.figshare.3443876.v5

Blog posts

6 May 2017: Querying the OpenCitations Corpus

15 May 2017: The Sloan Foundation funds OpenCitations

24 Nov 2017: Milestone for I4OC – open references at Crossref exceed 50%

24 Nov 2017: Elsevier references dominate those that are not open at Crossref

28 Nov 2017: Openness of non-Elsevier references

9 Jan 2018: The new Crossref reference distribution policy

9 Jan 2018: Barriers to comprehensive reference availability

15 Jan 2018: Funders should mandate open citations

16 Jan 2018: Oxford University Press opens its references!

29 Jan 2018: OpenCitations and the Initiative for Open Citations: A Clarification

19 Feb 2018: Citations as First-Class Data Entities: Introduction

22 Feb 2018: Citations as First-Class Data Entities: Citation Descriptions

25 Feb 2018: Citations as First-Class Data Entities: The OpenCitations Data Model

4 Mar 2018: Citations as First-Class Data Entities: The OpenCitations Corpus

12 Mar 2018: Citations as First-Class Data Entities: Open Citation Identifiers

15 Mar 2018: Citations as First-Class Data Entities: The Open Citation Identifier Resolution Service

23 Mar 2018: Early adopters of the OpenCitations Data Model

17 Apr 2018: Workshop on Open Citations

12 Jul 2018: COCI, the OpenCitations Index of Crossref open DOI-to-DOI references

19 Nov 2018: New release of COCI: 450M DOI-to-DOI citation links now available

Conference presentations and other outreach

Workshop on Open Citations 2018

OpenCitations, the EXCITE Project and Europe PubMed Central ran the first Workshop on Open Citations (Twitter: @workshop_oc) at the University of Bologna in Bologna, Italy, on 3-5 September 2018. It was organised as follows:

  • 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;
  • Day Three: A Hack Day on Open Citations to see what services can be prototyped using large volumes of open citation data.

The workshop involved 60 participants, including researchers, computer scientists, scholarly publishers, academic administrators, research funders and policy makers. The workshop was organised around the following topics:

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

All the sessions were recorded and are available on the official YouTube channel of the University of Bologna, and are linked (together with slides) at the website of the workshop – https://workshop-oc.github.io.

A further Workshop on Open Citations is being planned for autumn 2019.

Presentations

We have made conference presentations on OpenCitations, the Initiative for Open Citations, and Open Citation Identifiers at the following international conferences and workshops:

WikiCite Conference 2017, Vienna, 23 May 2017, https://www.slideshare.net/essepuntato/opencitations (Silvio Peroni and David Shotton)

COASP 9, 9th Conference of Open Access Scholarly Publishing, Lisbon, 20 September 2017, https://www.slideshare.net/essepuntato/the-initiative-for-open-citations-and-the-opencitations-corpus (David Shotton)

SemSci 2017, 1st International Workshop on Enabling Open Semantic Science, Vienna, 21 October 2017, https://w3id.org/people/essepuntato/presentations/the-open-citations-revolution.html (Silvio Peroni)

ISWC 2017, 16th International Semantic Web Conference, Vienna, 24 October 2017, https://w3id.org/people/essepuntato/presentations/oc-iswc2017.html (Silvio Peroni)

FORCE 2017, Research Communication and e-Scholarship Conference, Berlin, 27 October 2017, http://w3id.org/people/essepuntato/presentations/oc-force2017.html (Silvio Peroni)

Linked Open Citation Database (LOC-DB) Workshop, Mannheim, 7 November 2017, https://locdb.bib.uni-mannheim.de/wordpress/wp-content/uploads/2017/10/Shotton-LOC-DB-Mannheim.pdf (David Shotton)

GARR Conference 2017, Venice, 16 November 2017, https://www.eventi.garr.it/it/documenti/conferenza-garr-2017/presentazioni-2/232-conf2017-presentazione-peroni/file (Silvio Peroni)

OpenCon 2017, Oxford, 1 December 2017, https://doi.org/10.6084/m9.figshare.5844981.v1 (David Shotton)

PIDapalooza Conference of Persistent Identifiers, Girona, 24 January 2018, https://doi.org/10.6084/m9.figshare.5844972.v2 (David Shotton)

2018 International Workshop on Semantics, Analytics, Visualisation: Enhancing Scholarly Dissemination, Lyon, 24 April 2018, https://doi.org/10.6084/m9.figshare.7531577.v1 (Ivan Heibi)

Workshop on Open Citations 2018, Bologna, 3 September 2018, https://workshop-oc.github.io/presentations/D1S3_David_Shotton.pdf (David Shotton)

Workshop on Open Citations 2018, Bologna, 4 September 2018, https://docs.google.com/presentation/d/1mybQmjhFY6kLtTE1TdONaxsl0nSjmRGOSCnFMTwfzWQ/edit?usp=sharing (Silvio Peroni)

The 5th Conference on Scholarly Publishing in the Context of Open Science (PUBMET 2018), Zadar, 20 September 2018, https://doi.org/10.6084/m9.figshare.7110653.v3 (Silvio Peroni)

The 17th International Semantic Web Conference (ISWC 2018), Monterey, 12 October 2018, https://doi.org/10.6084/m9.figshare.7151759.v1 (Silvio Peroni)

WikiCite Conference 2018, Berkeley, 27 November 2018, https://doi.org/10.6084/m9.figshare.7396667.v1 (Ivan Heibi)

A further presentation on Open Citation Identifiers will be given at the 2019 PIDapalooza Conference of Persistent Identifiers in Dublin in January 2019.

Tweets

We have tweeted about the project and related matters under the names @opencitations, @dshotton, @essepuntato, @ivanHeiB, @workshop_oc, and @i4oc_org.

Future sustainability

While presently the OpenCitations Corpus has only partial coverage, our aim is that OpenCitations should become a comprehensive source of open citation information from all disciplines of scholarly endeavour, used on a daily basis by scholars worldwide, to equal or better the commercial offerings from Clarivate Analytics (Web of Science) and Elsevier (Scopus).

We also wish to develop effective graphical user interfaces to explore the citation network, and analytical tools over our open data. Since the OCC and COCI data are all open and available for others also to build such tools, we anticipate that such developments will best be undertaken collaboratively, under some open community organization, and indeed such development is currently being undertaken in collaboration with colleagues from CWTS at the University of Leiden, famous for their development of VOSviewer.

In order to fully support open scholarship, OpenCitations need to mature from being an academic research and development project to become a recognised scholarly infrastructure service such as PubMed. We wish to avoid becoming a commercial company, and see our development better served by being ‘adopted’ by a major established scholarly institution such as national or university library or an internationally recognised centre providing scholarly bibliographic services, that has already shown a commitment to open scholarship, where the interaction between that institution and OpenCitations would be mutually beneficial. To this end, we are currently in the mid-phase of negotiations with two institutions.

Conclusions

The grantees wish to express their deep gratitude to the Alfred P. Sloan Foundation for financial support enabling them to undertake the OpenCitations Enhancement Project, without which the rapid developments reported here would not have been possible.

References

Marilena Daquino, Ilaria Tiddi, Silvio Peroni, David Shotton (2018). Creating Open Citation Data with BCite. In Emerging Topics in Semantic Technologies – ISWC 2018 Satellite Events: 83-93. DOI: https://doi.org/10.3233/978-1-61499-894-5-83, OA at http://ceur-ws.org/Vol-2184/paper-01.pdf

Ivan Heibi, Silvio Peroni, David Shotton (2018a). Enabling text search on SPARQL-endpoints through OSCAR. Submitted for publication to Data Science – Methods, Infrastructure, and Applications. OA at at https://w3id.org/people/essepuntato/papers/oscar-datascience2019/

Ivan Heibi, Silvio Peroni, David Shotton (2018b). OSCAR: A Customisable Tool for Free-Text Search over SPARQL Endpoints. In Semantics, Analytics, Visualization – 3rd International Workshop, SAVE-SD 2017, and 4th International Workshop, SAVE-SD 2018, Revised Selected Papers: 121-137. DOI: https://doi.org/10.1007/978-3-030-01379-0_9, OA at https://w3id.org/people/essepuntato/papers/oscar-savesd2018.html

Silvio Peroni, Alexander Dutton, Tanya Gray, David Shotton (2015). Setting our bibliographic references free: towards open citation data. Journal of Documentation, 71: 253-77. DOI: https://doi.org/10.1108/JD-12-2013-0166, OA at http://speroni.web.cs.unibo.it/publications/peroni-2015-setting-bibliographic-references.pdf

Silvio Peroni, David Shotton (2018a). OpenCitations: enabling the FAIR use of open citation data. In Proceedings of the GARR Conference 2017 – The data way to Science – Selected Papers. DOI: https://doi.org/10.26314/GARR-Conf17-proceedings-19

Silvio Peroni, David Shotton (2018b). Open Citation: Definition. Figshare. DOI: https://doi.org/10.6084/m9.figshare.6683855.v1

Silvio Peroni, David Shotton (2018c). Open Citation Identifier: Definition. Figshare. DOI: https://doi.org/10.6084/m9.figshare.7127816.v1

Silvio Peroni, David Shotton (2018d). The OpenCitations Data Model. Figshare. DOI: https://doi.org/10.6084/m9.figshare.3443876.v5

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

Silvio Peroni, David Shotton, Fabio Vitali (2016a). Building Citation Networks with SPACIN. Knowledge Engineering and Knowledge Management – EKAW 2016 Satellite Events, EKM and Drift-an-LOD, Revised Selected Papers: 162-166. DOI: https://doi.org/10.1007/978-3-319-58694-6_23, OA at https://w3id.org/oc/paper/spacin-demo-ekaw2016.html

Silvio Peroni, David Shotton, Fabio Vitali (2016b). Freedom for bibliographic references: OpenCitations arise. In Proceedings of 2016 International Workshop on Linked Data for Information Extraction (LD4IE 2016): 32-43. http://ceur-ws.org/Vol-1699/paper-05.pdf

Silvio Peroni, David Shotton, Fabio Vitali (2017). One year of the OpenCitations Corpus: Releasing RDF-based scholarly citation data into the Public Domain. In Proceedings of the 16th International Semantic Web Conference (ISWC 2017): 184-192. DOI: https://doi.org/10.1007/978-3-319-68204-4_19, OA at https://w3id.org/people/essepuntato/papers/oc-iswc2017.html

David Shotton (2013). Open citations. Nature, 502: 295-297. https://doi.org/10.1038/502295a

David Shotton (2018). Funders should mandate open citations. Nature 553: 129. https://doi.org/10.1038/d41586-018-00104-7

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

Citations as First-Class Data Entities: The Open Citation Identifier Resolution Service

Requirements for citations to be treated as first-class data entities

In my introductory blog post, I listed five requirements for the treatment of citations as first-class data entities.  The fifth and final of these requirements is that there must be a Web-based identifier resolution service that takes the citation identifier as input and returns a description of the citation.

At the recent PIDapalooza Conference on persistent identifiers, held in Gerona, Spain, I described the Open Citation Identifier Resolution Service, the new resolution service for Open Citation Identifiers created and operated by OpenCitations [1].

In this post, I describe this Open Citation Identifier Resolution Service, which supports the resolution of Open Citation Identifiers not only of the citations documented in the OpenCitations Corpus (OCC), but also of open citations recorded in other bibliographic databases.

What is the Open Citation Identifier Resolution Service

The Open Citation Identifier Resolution Service runs on the OpenCitations server, presenting itself to the user as a web page with the URI http://opencitations.net/oci.

When a user enters a valid OCI and clicks the “Look up citation” button, this activates the resolution service, which, after a brief delay, returns information about the citation itself and about the citing and cited bibliographic resources, as shown in the following screen image (which for clarity omits the provenance data associated with this citation).

This information can optionally be returned to the user in a variety of other formats: RDF/XML, Turtle or JSON-LD.

Clicking on the links provided will return additional metadata held by the OpenCitations Corpus for the citing and the cited documents.  In the near future, this service will be integrated with LUCINDA, the forthcoming OCC browse interface, to present this information in a more user-friendly fashion.

Using the Resolution Service with citations in an external resource via a SPARQL endpoint

The Open Citation Identifier Resolution Service currently works for citations between bibliographic resources both within the OpenCitations Corpus and within external bibliographic databases, provided that the external service uses bibliographic resource identifiers having a unique numerical part, and provides a SPARQL endpoint to makes available information about bibliographic resources and the references they contain.

It can therefore resolve OCIs identifying citations within Wikidata, such as oci:01027931310-01022252312, where, as explained in the previous blog post, “010” is the assigned OCC supplier prefix for Wikidata.

Entering this OCI in the Open Citation Identifier Resolution Service pulls live data from the Wikidata SPARQL endpoint and returns the following information about that citation, as shown in the following screen image (which, again, omits for clarity the provenance data associated with that citation):

Clicking on the links provided here returns information about the relevant Wikidata entities.

Citing paper:

Cited paper:

How the Resolution Service works

The bibliographic database supplying the metadata for a particular citation identified by an OCI is specified by the assigned OCC supplier prefix that forms part of the OCI, as described in the previous blog post. Each OCI is thus specific for and unique within a particular bibliographic database.

The resolution service takes the OCI entered into the search box, recognises the supplier prefix specifying the bibliographic database holding the citation information, parses the OCI into the database identifiers for the citing and cited entities, and then sends an appropriate SPARQL query to interrogate the SPARQL endpoint of the relevant database. When that database has returned information about the citation itself and about the citing and cited bibliographic resources, this is displayed to the user as shown in screen images above – or in other RDF formats (Turtle, JSON-LD, RDF/XML) according to the request.

It is important to realize that no other databases are contacted during this resolution process, and that the quality and accuracy of the metadata retrieved by the Open Citation Identifier Resolution Service is the responsibility of the database hosting that citation.  The OCI Resolution Service does no more than retrieve this information, and does nothing to address possible errors or omissions in the metadata coming from the hosting database.

Using the Resolution Service with external citations via a REST API

While the resolution service presently works only to retrieve information from bibliographic databases having a SPARQL endpoint, we plan soon to extend this resolution service to work with information supplied by a bibliographic database via a REST API.

Coupled with the ability to create OCIs by numerical conversions of Digital Object Identifiers (DOIs), as explained in the previous blog post, the Open Citation Resolution Service could then be used to pull metadata live from the Crossref REST API for any of the ~350 million Crossref open references in which the cited paper as well as the citing paper has a DOI, and for which an OCI can thus be created.

Watch this space!

References

[1]     David Shotton (2018). Citations as first-class data entities. Open Citation Identifiers.  Conference presentation. PIDapalooza 2018, Girona, 23-23 January 2018. https://doi.org/10.6084/m9.figshare.5844972

Citations as First-Class Data Entities: Open Citation Identifiers

Requirements for citations to be treated as First-Class Data Entities

In my introductory blog post, I listed five requirements for the treatment of citations as first-class data entities.  The fourth of these requirements is that they must be identifiable using a global persistent identifier scheme.

At the recent PIDapalooza Conference on persistent identifiers, held in Girona, Spain, I launched the Open Citation Identifier (abbreviated OCI, in line with DOI), the new persistent identifier for citations [1].

In this post, I describe the Open Citation Identifier scheme, created and operated by OpenCitations, which supports the assignment of Open Citation Identifiers not only to the citations present in the OpenCitations Corpus (OCC) but also to open citations present in other bibliographic databases.

Structure and syntax of the Open Citation Identifier

Each OCI has a simple structure: oci:number-number, where “oci:” is the identifier prefix.

OCIs for citations stored within the OpenCitations Corpus are constructed by combining the OpenCitations Corpus local identifiers for the citing and cited bibliographic resources, separating them with a dash.  (For definition of OCC local identifiers, see the OpenCitations Data Model).

For example, oci:2544384-7295288 is a valid OCI for the citation between two papers stored within the OpenCitations Corpus, the first number being the OCC local identifier for the citing bibliographic resource [2], and the second being the OCC local identifier for the cited bibliographic resource [3], these bibliographic resource local identifiers being unique within the OCC.  [Note: Supplier prefixes are omitted from OCC local identifiers of bibliographic resources ingested into the OpenCitations Corpus prior to February 2018, but will be included within all OCC local identifiers of bibliographic resources ingested into Corpus after that date.]

OCIs for external resources identifies by numerical identifiers

OCIs can also be created for bibliographic resources described in an external bibliographic database, if they are similarly identified there by identifiers having a unique numerical part.  For example, the OCI for the citation that exists between Wikidata resources Q27931310 (the citing resource, [4]) and Q22252312 (the cited resource, [5]) is oci:0102793131001022252312, where “010” is the assigned OCC supplier prefix for Wikidata.  (The colours here and below are added simply for clarity.)

The OCC supplier prefix consist of a positive number (following the pattern “nnn”, where “nnn” is a string of numerals of variable length which includes no zeros), enclosed between two zeros (e.g. “0420”).  The list of all assigned OCC supplier prefixes is given at https://github.com/opencitations/oci/blob/master/suppliers.csv.

OCIs for citations between resources identified by DOIs

OCIs can also be created for bibliographic resources described in external bibliographic database such as Crossref or DataCite where they are identified by alphanumeric Digital Object Identifiers (DOIs), rather than purely numerical strings.

To achieve this, each case-insensitive DOI is first normalized to lower case letters. Then, after omitting the initial “doi:10.” prefix, the alphanumeric string of the DOI is converted reversibly to a pure numerical string using the simple two-numeral lookup table for numerals, lower case letters and other characters presented at https://github.com/opencitations/oci/blob/master/lookup.csv. For example, using this lockup table, “1” becomes “01”, “2” becomes “02”, “a” becomes “10”, “b” becomes “11”, and “/” becomes “36”.  To the resulting number, the appropriate OCC supplier prefix is then added, to clearly identify its provenance.

A citation documented in Crossref exists between the two publications [3] and [6], which are there identified by the DOIs doi:10.1108/jd-12-2013-0166 and doi:10.1371/journal.pcbi.1000361.  We can thus create an OCI for this Crossref citation by using numerical representations of the two DOIs. These numerical representations are:

0200101000836191363010263020001036300010606

and

02001030701361924302723102137251211183701000000030601

where the initial “020” in each case is the assigned OCC supplier prefix for Crossref.

From these two numerical representations of DOIs, the OCI for the Crossref citation between these two paper is easily constructed, and is:

oci:0200101000836191363010263020001036300010606-02001030701361924302723102137251211183701000000030601

While this is long for an identifier, it should be remembered that it will be processed computationally, and is not intended for human readability.

In this way, Crossref OCIs can be assigned to all ~350 million open references within Crossref in which the cited paper as well as the citing paper has a DOI [7].

OCIs for the same citation recorded within different databases

If a citation is recorded in more than one bibliographic database, a separate OCI can be created for each instance, each OCI having a distinct supplier prefix and being specific to that database.

Thus, in addition to the Crossref OCI created from DOIs and described above for the citation from [3] to [6], a Wikidata OCI exists for the same citation recorded within Wikidata, having the form oci:01024260641-01021092566.

Upon resolution of an OCI, the Open Citation Identifier Resolution Service will pull metadata only from the database specified by the supplier prefix of the OCI.  Details of the Open Citation Identifier Resolution Service are given in the next blog post.

It is important to note that an OCI can only be used to specify a citation between a citing and a cited publication which is actually recorded within a bibliographic database.  For this reason, the OCI “oci:7295288-3962641” shown below the second diagram in the introductory blog post to this series is presently invalid.  While the OpenCitations Corpus has metadata describing both bibliographic resources [3] and [6], it has not yet ingested the reference list for the first bibliographic resource [3] (which has the OCC local identifier 7295288), having information about it only from a reference within a third paper, with no information about the references [3] itself contains.  As a result, at present OCC has no record that a citation actually exists between [3] and the second bibliographic resource [6] (which has the OCC local identifier 3962641).

Representing OCIs in RDF

To permit the description of OCIs in RDF, “oci” has been added as a new member of the class datacite:ResourceIdentifierScheme within the DataCite Ontology.

The resolvable URL for any citation identified by a OCI has the form “https://w3id.org/oc/virtual/ci/nnn-mmm”, where nnn-mmm represents the OCI with its “oci:” prefix removed. Currently, we are able to return the RDF description of all the citations contained in the OpenCitations Corpus and Wikidata. We are working to extend the coverage so as to include other datasets, e.g. Crossref.

References

[1]     David Shotton (2018). Citations as first-class data entities. Open Citation Identifiers.  Conference presentation. PIDapalooza 2018, Girona, 23-23 January 2018. https://doi.org/10.6084/m9.figshare.5844972

[2]     Armen Yuri Gasparyan, Marlen Yessirkepov et al. (2015). Preserving the integrity of citations and references by all stakeholders of science communication.  J. Korean Med. Sci. 30:1545-1552. (English.)  https://doi.org/10.3346/jkms.2015.30.11.1545

[3]     Silvio Peroni, Alexander Dutton, Tanya Gray and David Shotton (2015). Setting our bibliographic references free: towards open citation data. Journal of Documentation, 71 (2): 253-277.  https://doi.org/10.1108/jd-12-2013-0166

[4]     Daniel K. Bricker, Eric B. Taylor et al. (2012). A Mitochondrial Pyruvate Carrier Required for Pyruvate Uptake in Yeast, Drosophila, and Humans. Science 337: 96-100.
https://doi.org/10.1126/science.1218099

[5]     Douglas Hanahan and Robert A. Weinberg (2011). Hallmarks of cancer: the next generation.  Cell 144: 646–674.  https://doi.org/10.1016/j.cell.2011.02.013

[6]     David Shotton, Katie Portwin, Graham Klyne and Alistair Miles (2009).  Adventures in semantic publishing: exemplar semantic enhancement of a research article. PLoS Computational Biology 5: e1000361. http://dx.doi.org/10.1371/journal.pcbi.1000361

[7]     Daniel Ecer (2017). Crossref Data Notebook (updated). Available at https://elifesci.org/crossref-data-notebook

 

Citations as First-Class Data Entities: The OpenCitations Corpus

Requirements for citations to be treated as First-Class Data Entities

In my introductory blog post, I listed five requirements for the treatment of citations as first-class data entities.  The third of these requirements is that they must be storable, searchable and retrievable in an open database designed for bibliographic citations.

In this post, I describe the current status of the OpenCitations Corpus, a well-structured open database specifically developed by OpenCitations and designed to store information about bibliographic citations as Linked Open Data, encoded in RDF (specifically JSON-LD).

What is OpenCitations?

OpenCitations (http://opencitations.net) is an scholarly infrastructure organization that has created and is currently expanding the coverage of the Open Citations Corpus (OCC), an open repository of scholarly citation data made available under a Creative Commons CC0 public domain dedication, which provides in RDF accurate citation information (bibliographic references) harvested from the scholarly literature.

The Co-Directors of OpenCitations are David Shotton, Oxford e-Research Centre, University of Oxford (david.shotton@opencitations.net) and Silvio Peroni, Department of Computer Science and Engineering, University of Bologna (silvio.peroni@opencitations.net).

We are committed to open scholarship, open data, open access publication, and open source software.  We espouse the FAIR data principles developed by Force11, of which David Shotton was a founding member, and the aim of the Initiative for OpenCitations (I4OC), of which David Shotton and Silvio Peroni were both founding members, to promote the availability of citation data that is structured, separable, and open.

The principal activity of OpenCitations to date has been the establishment and population of the OpenCitations Corpus.

Holdings of the OpenCitations Corpus

We have so far concentrated on ingesting into the OpenCitations Corpus bibliographic references from open access papers available at PubMed Central, the encoding of these data in RDF, and high-quality curation of the citation links they represent, involving metadata enrichment from the Crossref API and (for authors) the ORCID API.

To date (19th February 2018), the OCC has ingested the references from 302,758 citing bibliographic resources, and contains information about 12,830,347 citation links to 6,549,665 cited resources. Plans to expand the coverage of the OCC are outlined below.

User interfaces

The information within the OCC can be accessed via OSCAR, our new generic OpenCitations RDF Search Application (http://opencitations.net/search) [1], which can be used for textual searches over any triplestore presenting a SPARQL endpoint.  Users can employ OSCAR to search the OCC for publication titles, author names, publication years, and identifiers (DOIs, PubMed IDs PubMed Central IDs, ORCIDs, and OCC corpus identifiers). Such a search returns details of all bibliographic resources within the OCC matching the search term, from which their references can be obtained, if known. In the near future, we will complement OSCAR with a browse interface named LUCINDA.

We also provide a SPARQL endpoint for directly querying the Blazegraph triplestore in which we store the OCC RDF, and we plan in the near future to supplement such programmatic access with a REST API.  In addition, the contents of the entire triplestore, and of the various sub-databases within the Corpus, together with their provenance information, are downloadable from Figshare as monthly dumps.  Once the REST API has been developed, we will turn our attention to developing user interfaces for the interactive visualization of citation graphs.

The OpenCitations Data Model

As described in the previous blog post, we have just completed a comprehensive revision of the OpenCitations Data Model (OCDM, available at https://doi.org/10.6084/m9.figshare.3443876), which we use to capture descriptions of all aspects of the OCC citations and their provenance. This model makes extensive use of our SPAR (Semantic Publishing and Referencing) Ontologies (http://www.sparontologies.net/), which we developed to describe all aspects of the scholarly publishing domain in RDF .

The OpenCitations Data Model is freely available for third parties to use when recording their own bibliographic and citation information in RDF, with the advantage that data so modelled will be immediately compatible with those within the OpenCitations Corpus, which can act as a publishing venue for such third-party data.

Future ingest rate and data sources

Since July 2016, the instantiation of the OpenCitations Corpus currently running at the University of Bologna has been ingesting reference lists from biomedical journal articles at the relatively slow rate of about 200,000 citing bibliographic resources per year. During February 2018, ingestion into the Corpus is suspended, while we move the system to a completely new and more powerful server, supplemented by thirty Raspberry Pi ingest engines that will work in parallel feeding ingested data to the server.

This will increase our ingestion rate ~30-fold to about six million citing bibliographic resources per year, equivalent to ~240 million citations per year at 40 references per paper (the current OCC value is 42.4 references per paper).  We should then be able to complete ingestion of the ~1.4 million remaining OA resources at PubMed Central within about three months.

At that stage, we plan to start ingesting references from the ~17 million journal articles whose deposited references are now open at Crossref as a consequence of the Initiative for Open Citations.  The scholarly world currently publishes about 2.5 million new journal articles each year, of which about half will be probably be open at Crossref (assuming Elsevier has not by then opened its references).  So, by the end of 2020, Crossref will have ~650 million open references.  In addition to ingesting new open Crossref references as they are made available, we will be able to eat into the backlog of existing Crossref open references at a catch-up rate of ~190 million per year.  By the end of 2020, we anticipate that the OCC should contain ~650 million citations harvested from PMC and Crossref, roughly half the coverage of Web of Science.  We are currently also considering ingest of references from other major bibliographic databases.

Our vision for OpenCitations

Our vision is that OpenCitations should become a comprehensive source of open citation information from all disciplines of scholarly endeavour encoded as Linked Open Data, a key component of the academic open infrastructure used on a daily basis without charge by scholars worldwide.

To be of maximum utility, it requires effective graphical user interfaces and analytical tools to interrogate and quantify the data contained within the OCC.  Since these data are all open, we anticipate that such interface and tool development will best be undertaken collaboratively within the open scholarly community, and we invite developers interested in such collaboration to contact us at contact@opencitations.net.

Reference

[1]     Ivan Heibi, Silvio Peroni and David Shotton (2018).  OSCAR: A customisable tool for free-text search over SPARQL endpoints. Accepted to the 2018 International Workshop on Semantics, Analytics, Visualisation: Enhancing Scholarly Dissemination Workshop (https://save-sd.github.io/2018/, co-located with The Web Conference), 24 April 2018 – Lyon, France.  Preprint available at https://w3id.org/people/essepuntato/papers/oscar-savesd2018.html

Citations as First-Class Data Entities: The OpenCitations Data Model

Requirements for citations to be treated as First-Class Data Entities

In my introductory blog post, I listed five requirements for the treatment of citations as first-class data entities.  The second of these requirements is that they must have metadata structured using a generic yet appropriately detailed data model.

To fulfil that requirement, OpenCitations is pleased to announce the publication on 13 February 2018 of the OpenCitations Data Model, v1.6 [1].  This replaces the previous version, v1.5.3, published on 13 July 2016.

The data model has been expanded and enhanced to improve the recording of publication dates, to include the treatment of citations as first-class data entities, and to permit the model’s adoption by third parties who may wish to use it to model their own citation data, or to prepare their citation data for publication in the OpenCitations Corpus (OCC).  To facilitate this, the document describing this data model is published under a Creative Commons Attribution 4.0 International license.

In addition to a change in the title from “Metadata for the OpenCitations Corpus” to “The OpenCitations Data Model”, and the use of the name “OpenCitations” (one token with two words in camel case) in place of “Open Citations” (with the space separating the two words), the substantive changes in the model from the previous version are as follows:

New class

A new class, Archival document, has been added as a subclass of bibliographic resource, to permit the model to be used for work on ancient manuscripts.

Publication dates

The mechanism for recording the publication dates of bibliographic resources has been improved, and now accepts the full date of publication (yyyy-mm-dd, if available), or the year plus the month of publication (yyyy-mm, if the full date is not available), or failing that just the year of publication (yyyy, as in the previous version of the data model).   In order to support this modification in the OWL mapping, prism:publicationDate is now used instead of fabio:hasPublicationYear.

Citations as first-class data entities

A new class of bibliographic entity, Citation, has been added to permit the description of citations as first-class data entities.  This class has been assigned sub-classes (e.g. Author self-citation) and properties (e.g. citation time span) to permit the description of citations in a manner helpful for bibliometric analysis.  These, and associated changes to CiTO, the Citation Typing Ontology, are described more fully in the previous blog post.

Virtual entities

The OpenCitations Data Model now permits the definition of virtual entities, i.e. bibliographic entities that are defined on-the-fly, only when they are requested (for example, by accessing their URLs). These are defined either by using data relating to non-virtual bibliographic entities that are already available within the OCC, or by using data that are themselves obtained on-the-fly from an external supplier (e.g. Wikidata).

This approach of using virtual RDF resources is optional, and is simply employed for storage efficiency, to avoid duplication of information within the OCC triplestore. As of January 2018, only one type of bibliographic entity is defined as a virtual entity, namely a citation (a members of the class Citation).

Such a virtual entity does not have the full provenance information normally associated with other bibliographic entities within the OCC, but it does have associated with itself the date of its creation and direct links both to the agent responsible for such creation and to the source data used in its construction.

Because we do not separately store these virtual entities within the Corpus triplestore, they cannot be directly queried by means of the OCC SPARQL end-point, neither are they stored within its data dumps. However, the data associated with an OCC virtual entity can be obtained by accessing its URL, which has form “https://w3id.org/oc/virtual/xyz”, clearly distinguishable from those URIs used for other (non-virtual) OCC bibliographic entities which have the form “https://w3id.org/oc/corpus/xyz”.  More details and examples are given in the Data Model document itself.

Additionally, for citations defined using Open Citation Identifiers (OCIs, described in a subsequent blog post), details of the cited and citing publications may be readily obtained by using the Open Citation Identifier Resolution Service at http://opencitations.net/oci.

Supplier prefixes

To enable citation data created by third parties to be incorporated within the OpenCitations Corpus, from February 2018 the OCC local identifiers for bibliographic resources now include a supplier prefix which clearly identifies the provenance of the data.  The prefix consists of a positive number (following the pattern “nnn”, where “nnn” is a string of numerals of variable length which includes no zeros), enclosed between two zeros (e.g. “0420”).

To ensure uniqueness of prefixes used by different suppliers, all organizations wishing to adopt the OpenCitations Data Model and to use it to create publicly available citation data, whether these are published in the OpenCitations Corpus or independently, must apply to OpenCitations for a unique supplier prefix, by sending an email to support@opencitations.net.  A list of already assigned supplier prefixes is available at https://github.com/opencitations/oci/blob/master/suppliers.csv.

The appropriate supplier prefix is combined with a unique numerical string that forms the ‘body’ of the identifier to create the local identifier used in OCC to identify an individual bibliographic resource.  OCC local identifiers for citations (as opposed to bibliographic resources) are constructed by combining the local identifiers for the citing and cited bibliographic resources, separating them with a dash.  Thus, for a citation between two bibliographic resources described in an external bibliographic database where they are each identified by an identifier having a unique numerical part, the OCC local identifiers for the citing and cited bibliographic resources are combined, separating them with a dash.

For example, the citation between citing Wikidata resource Q27931310 and cited Wikidata resource Q22252312 is given the OCC local citation identifier “01027931310-01022252312”, where “010” is the OCC supplier prefix (defined above) for Wikidata.  How these OCC local identifiers for citations are used to create Open Citation Identifiers is described in a separate blog post.

We commend the OpenCitations Data Model to anyone considering the storage of citation information, particularly if it is to be encoded in RDF, and we welcome contributions of citation data encoded using this model for publication within the OpenCitations Corpus.

Reference

[1]     Silvio Peroni, David Shotton (2018). The OpenCitations Data Model. Version 1.6. figshare. https://doi.org/10.6084/m9.figshare.3443876

Citations as First-Class Data Entities: Introduction

Citations are now centre stage

As a result of the Initiative for Open Citations (I4OC), launched on April 6 last year, almost all the major scholarly publishers now open the reference lists they submit to Crossref, resulting in more than half a billion references being openly available via the Crossref API.

It is therefore time to think carefully about how citations are treated, and how they might be better handled as part of the Linked Open Data Web.

Citations are normally treated simply as the links between published entities.

Conventional citation

However, an alternative richer view is to regard a citation as a data entity in its own right.

First class citation

This permits us to endow a citation with descriptive properties, such as

has citation creation date:   3rd March 2015
has citation time span:       6 years, 5 months and 23 days
has type:                     Self-citation
has identifier:               oci:7295288-3962641

[Note: a later blog post entitled “Open Citation Identifiers” will include an explanation of the identifier shown here.]

Advantages of treating citations as First-Class Data Entities

  • All the information regarding each citation is available in one place.
  • Citations become easier to describe, distinguish, count and process.
  • If available in aggregate, citations described in this manner are easier to analyze using bibliometric methods, for example to determine how citation time spans vary by discipline.

Requirements for citations to be treated as First-Class Data Entities

  • They must be definable in a machine-readable manner as a member of the class “Citation”, and describable using appropriate ontology terms.
  • They must have metadata structured using a generic yet appropriately detailed data model.
  • They must be storable, searchable and retrievable in an open database designed for bibliographic citations.
  • They must be identifiable using a global persistent identifier scheme.
  • There must be a Web-based identifier resolution service that takes the citation identifier as input and returns a description of the citation.

Blog post detailing how these requirements are met

Subsequent blog posts will describe how we at OpenCitations have satisfied these requirements, permitting citations to indeed be treated as First-Class Data Entities:

  1. Citations as First-Class Data Entities: Citation Descriptions
  2. Citations as First-Class Data Entities: The OpenCitations Data Model
  3. Citations as First-Class Data Entities: The OpenCitations Corpus
  4. Citations as First-Class Data Entities: Open Citation Identifiers
  5. Citations as First-Class Data Entities: The Open Citation Identifier Resolution Service

OpenCitations and the Initiative for Open Citations: A Clarification

Some folk are confused, but OpenCitations and the Initiative for Open Citations, despite the similarity of their names, are two distinct organizations.

OpenCitations (http://opencitations.net) is an open scholarly infrastructure organization directed by Silvio Peroni and myself, and its primary purpose is to host and build the OpenCitations Corpus (OCC), an RDF database of scholarly citation data that now contains almost 13 million citation links.

In contrast, the Initiative for Open Citations (I4OC; https://i4oc.org) is a separate and independent organization, whose founding was spearheaded by Dario Taraborelli of the WikiMedia Foundation.  OpenCitations was just one of several organizations that founded the Initiative for Open Citations, as documented at https://i4oc.org/#founders.

I4OC is a collaboration between scholarly publishers, researchers, and other interested parties to promote the unrestricted availability of scholarly citation data, but it does not itself host citation data.

Within a short space of time, I4OC has persuaded most of the major scholarly publishers to open their reference lists submitted to Crossref, so that the proportion of all references submitted to Crossref that are now open has risen from 1% to over 50%.

These references are now available for OpenCitations to harvest into the OpenCitations Corpus and publish in RDF, as well as for others to harvest and use as they wish.

All clear now?

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