The OpenCitations Roadmap is now publicly available on Trello

Want to keep yourself updated about the ongoing activities of OpenCitations? We have now publicly released the OpenCitations Roadmap, available on Trello.com:

https://trello.com/b/RprHYoKL/opencitations

The OpenCitations Roadmap consists of a board fulfilled with colour-labelled cards which present the goals so far reached, the present projects and activities, and the future plans. By clicking on the cards, it is possible to visualize a description for each activity, the progress state, and who in the OpenCitations team is working on it.

The OpenCitations Roadmap covers all kinds of activities divided according to the scope, identified by the coloured labels, in particular:

  • light blue for the technical development, such as the development of the software for the creation of the new database OpenCitations Meta and of DOCI, the OpenCitations Index of DataCite open DOI-to-DOI citations, and the re-engineering of the infrastructure and the website;
  • green for the data model implementation;
  • yellow for the data development, such as the bi-monthly COCI releases;
  • purple for the events and outreach activities.

The cards also highlight the activities related to the two EC-funded projects OpenCitations is involved in, OpenAIRE Nexus (blue label) and RISIS2 (orange label). We thank the OpenAIRE team for the help and suggestions during the Roadmap review process.

The OpenCitations Roadmap is an open work in progress that will reflect the developments and growth of OpenCitations. At OpenCitations, we don’t want this Roadmap to be just an online ‘showcase’, but a room in which to share ideas and opinions. We invite you – the members of our community, our stakeholders, the other Open Science actors, researchers, and librarians, and anyone who is interested in OpenCitations activities – to add a comment or a question in the ‘Leave feedback‘ card. This will help us to better understand our strong and weak points, and to stay in touch with the needs and thoughts of the community.

In this way, supplementing the conventional communications channels of email and the social platforms (our blog, Twitter, LinkedIn), the OpenCitations Roadmap will become a new virtual place for dialogue, where you can directly contribute to improve OpenCitations.

Cite this article as: Chiara Di Giambattista, "The OpenCitations Roadmap is now publicly available on Trello," in OpenCitations blog, 29/03/2022, https://opencitations.hypotheses.org/1519.

OpenCitations and EC funding: OpenAIRE Nexus and RISIS2

The incentives for new OpenCitations innovative solutions

Two years ago, in their canonical 2020 QSS paper on OpenCitations, Silvio Peroni and David Shotton anticipated the creation of the new database, OpenCitations Meta, able to “offer a faster and richer service” by storing bibliographic metadata “in house”. Meta would “avoid duplication of data by efficiently permitting us to keep […] a single copy of the metadata for each of the bibliographic entities involved as citing or cited entities in the different OpenCitations’ citation indexes”, would remove the requirement for potentially slow API calls to external metadata sources such as Crossref and ORCID, and would enable us to index citations involving entities lacking DOIs.

Important synergies to achieve goals

Today, thanks to the recent involvement of OpenCitations in two EC-funded projects, the OpenAIRE-Nexus Project (Horizon 2020 EU funded project, GA: 101017452) and the RISIS2 Project (Horizon 2020 EU funded project, GA: 824091), the development of OpenCitations Meta has commenced, with a planned release date later in 2022.

The OpenAIRE-Nexus project started in January 2021 to embrace and expand the operation of a portfolio of thirteen services, provided by OpenAIRE infrastructure, public institutions, organisations and universities, classified into three portfolios entitled PUBLISH, MONITOR, and DISCOVER. The OpenAIRE-Nexus portfolios focus on the demands of the three main categories of the research lifecycle.  Therefore, OpenAIRE-Nexus makes sure such services are integrated to provide a uniform Open Science Scholarly Communication package for the European Open Science Cloud (EOSC). Within the OpenAIRE Nexus project there is scope for producing not only support materials (factsheet, guides, video tutorials, demos) but also training sessions where the services in the three portfolios will be showcased, anticipating the EOSC onboarding process. The role of OpenCitations in the project is to provide open bibliographic citations, and interconnect and integrate (and vice versa) functionalities with the  OpenAIRE Research Graph and more OpenAIRE-Nexus services such as EpiSciences, OpenAIRE MONITOR) the core component of OpenAIRE infrastructure and services and of the EOSC Resource Catalogue. 

Additionally, we are happy to announce our recent involvement in the RISIS2 Project. The Research Infrastructure for Science and Innovation Policy Studies (RISIS) is a project funded by the European Union under a Horizon2020 Research and Innovation Programme. RISIS2 involves 18 partners working together to create and maintain a research infrastructure for the field of Science, Technology, and Industry (STI) Studies, and to build an advanced research community in this field. OpenCitations’ contributions to RISIS2 will include not only the creation of OpenCitations Meta but also the development of a new citation index of open references, the OpenCitations Index of DataCite Open Citations (DOCI), which will be based on the open reference holdings of DataCite and, together with COCI, will be cross-searchable through our unified OpenCitations API.

Lessons learnt so far

A year into the OpenAIRE-Nexus project, we have found that one of the most significant benefits for OpenCitations is our involvement with this wide cooperative network of European research infrastructures, services, and communities, within which we can exchange experiences, ideas, and knowledge, and discuss any challenges and outcomes with our colleagues. More importantly, OpenCitations becomes positioned within the Open Science ecosystem, as a valuable innovative infrastructure with strong proof of integration and interoperable operations. Being part of the OpenAIRE-Nexus team has opened up more future challenges and expectations, and raised the bar for the inclusion of more functionalities of value. Thanks to the dedication of its efficient communication team, OpenAIRE is also helping us by communicating OpenCitations services to additional users and stakeholders, by inclusion within the comprehensive OpenAIRE services catalogue, by releasing an OpenCitations factsheet and by permitting us to present the latest information on OpenCitations through established events (i.e. Open Science FAIR 2022). FAIR and openness of information is our motto, and we strongly promote this through all our activities.

Expanding our team

As announced in our previous blog post “Five reasons why 2021 has been a great year for OpenCitations”, the support we receive from the EU as part of OpenAIRE-Nexus has enabled our recent appointment of Arcangelo Massari, a software developer who is now playing a crucial role in the creation and development of OpenCitations Meta.

As the year 2022 progresses, we look forward to bringing you further information about other new goals for OpenCitations, made possible by the support we receive from our numerous partnerships.

Cite this article as: Chiara Di Giambattista, "OpenCitations and EC funding: OpenAIRE Nexus and RISIS2," in OpenCitations blog, 08/03/2022, https://opencitations.hypotheses.org/1510.

Open citations in Informatics: current status and lines of research

This post was first published on QWERTY: musings from the rabbit hole, a blog by Silvio Peroni

A few months ago, I was invited to have a talk at the European Computer Science Symposium on an aspect of my research I particularly care about, that of open citations. What I tried to address during the presentation concerned the current status of open citation availability in a particular domain, Informatics, by using two open datasets, i.e. DBLP for gathering bibliographic metadata about relevant publications and OpenCitations’ COCI for identifying citations where such publications are involved. This post briefly introduces the preliminaries and results obtained from the material used to prepare the talk.

Open citations and where to find them

A citation is a conceptual directional link between a citing entity and a cited entity which is defined by means of specific textual devices contained in the text of the citing entity, e.g. a bibliographic reference denoted by an in-text reference pointer (e.g. “[3]” or “(Doe et al, 2021)”). While reasons for citing may vary, citations are used in academia for acknowledging others’ work and enabling building trails of relations defining how science evolves in time.

The data needed to describe a citation should include, at least, a representation of such a conceptual link and the basic bibliographic metadata to identify the citing and cited entities, i.e. those typically used for defining bibliographic references such as authors’ names, year of publication, the title of the work, venue of publication, pages, identifiers, etc. We say that a citation is open when these citation data are in the public domain and can be retrieved freely (via the HTTP protocol) in a structured and machine-readable format (e.g. JSON or RDFwithout accessing the source of citing article defining it, which, potentially, could be behind a paywall.

OpenCitations [full disclosure: I am one of its directors] is one of the founders of the Initiative for Open Citations (I4OC) and one of the open scholarly infrastructures providing open citation data through several channels (REST APIs, SPARQL endpoints, Web interfaces, full dumps in different formats). As of 31 December 2021, it makes available more than 1.2 billion open DOI-to-DOI citation links between more than 69.5 million bibliographic resources, which are mainly journal articles but also include books, book chapters, datasets, and other DOI-identified resources. The entities involved in such citations come from different domains, spanning from Medicine articles to Humanities publications, and have recently approached parity with those included in well-known proprietary services such as Web of Science and Scopus.

What about Informatics

Such a huge mass of open citations available enables us to analyse citation coverage in different scholarly disciplines, e.g. to understand which publishers contributed to the availability of open citation data in a discipline and to check what are the citation trails between different disciplines. However, to compute such citation coverage, we need to have some information that allows us to identify when a particular bibliographic resource involved in a citation belongs to the particular discipline we want to analyse. We can use information about the subject categories of publications (e.g. that of Web of Science), if included in citation indexes, to identify the discipline(s) of a given bibliographic resource. Unluckily, OpenCitations does not provide this information and, as such, we need to rely on external repositories for gathering subject categories of publications, e.g. collections of bibliographic metadata of disciplinary publications.

In the context of Informatics, there is at least one well-known resource gathering and exposing bibliographic metadata of a large part of Computer Science publications, i.e. DBLP. As of 30 December 2021, DBLP contains more than 5.9 million publications published in 1,781 journals and in the proceedings of 5,621 conferences, involving more than 2.9 million authors that are manually curated (and disambiguated) by the DBLP team.

DBLP can be used as a proxy to understand if a particular publication belongs to the Computer Science subject category. Through it, it is possible to understand how many citations in OpenCitations involve Computer Science publications by comparing the DOIs of citing and cited entities with those available in DBLP. In particular, using the OpenCitations’ COCI September 2021 dump and DBLP October dump, I found that more than 80 million citations in COCI involved at least one of the 4,637,865 entities in DBLP (considering only journal articles, conference proceedings papers, books and book chapters). As shown in Figure 1, only 39% of these citations are between citing and cited entities both included in DBLP, while the rest of them either come from or go to publications not listed in DBLP – that, potentially, could not be Computer Science publications.

Figure 1. A Venn diagram showing how many citations involving Computer Science publications (obtained from DBLP) are included in OpenCitations.

Additional information about the publishers of such DBLP entities, retrieved by querying the Crossref API and the DataCite API with entities’ DOIs, are shown in Table 1. IEEE is the publisher with the biggest number of entities of those considered for this study, and its entities are involved in more than 18.9 million incoming and 21.5 million outgoing citations. The other bigger publishers, in terms of entities and citations, are Springer, Elsevier, ACM and Wiley. It is worth mentioning that the two publishers responsible for publishing mainly Computer Science journals and a relatively low number of conference proceedings (if any), i.e. Elsevier and Wiley, are those providing the highest number of openly-available references per publication (on average, around 29 and 37 cited works for each publication respectively).

PublisherDBLP entitiesCOCI incoming citationsCOCI outgoing citations
IEEE1,730,48518,930,05521,582,093
Springer1,012,53418,482,13211,179,566
Elsevier574,86015,536,20717,019,716
ACM433,1883,695,2556,050,342
Wiley89,6623,350,1833,357,065
Table 1. The DBLP entities retrieved in the study grouped by their publisher and their incoming and outgoing citations according to COCI.

Future developments

Of course, this study does not provide full coverage of open citations in Computer Science but just a preliminary insight. First, as anticipated below, DBLP does not have the complete coverage of all CS-related publications since there are some venues that are not listed there (yet). Thus, some relevant open citations could not be extracted from COCI if these involve as citing and cited entity non-DBLP publications that belong to the CS domain. However, it is worth mentioning that no bibliographic and citation database (including commercial and proprietary ones) has a full disciplinary coverage anyway and DBLP is, probably, the most comprehensive collection of Computer Science publications metadata (something that could be assessed in future analysis).

Along the same lines, the index of open citations used, i.e. COCI, does not contain all the citations defined in CS publications, but only DOI-to-DOI citations as retrievable from Crossref data. Although Crossref is the biggest DOI provider and it is used by the majority of the big publishers,citations defined in publications with a non-Crossref DOI (e.g. DataCite) and those not having any DOI assigned (e.g. the papers published in CEUR Workshop Proceedings) are not included in COCI and, consequently, have not been used in the analysis. However, OpenCitations plans to extend its data coverage adding more sources in the next years. Thus, it would be interesting to replicate the same analysis in the future to see if and how much the coverage increase, at least in the context of Computer Science publications.

Still about coverage, currently (i.e. 31 December 2021) the only publisher of those included in Table 1 which is not providing open references through Crossref is IEEE. Indeed, while COCI includes several citations involving IEEE publications as citing entities, there is no availability of such citation after October 2018, when IEEE decided not to allow anymore Crossref Metadata Plus users to access these reference data.

Finally, analysing the preliminary results of this study, it would be interesting to understand which are the main subject categories of non-DBLP publications included in the 61% of citations shown in Figure 1 (e.g. by using the Scimago Journal and Country Rank database to retrieve their subject categories) to understand what are the citation dynamics between Informatics and other disciplines. However, I will leave the answer to this question to future analysis.

A final remark on reproducibility

Since several of the suggestions provided above start from the idea of either replicating or extending this study with additional materials and insights, it is important that all data and software used to perform the analysis are available online to permit its reproducibility. To this end, I have published both the software and the data retrieved online with open licenses to enable anyone to reuse it freely for any purpose.

Cite this article as: Silvio Peroni, "Open citations in Informatics: current status and lines of research," in OpenCitations blog, 01/01/2022, https://opencitations.hypotheses.org/1471.

IBRG projects to facilitate data publication and data citation

In the previous post, I outlined reasons why researchers don’t publish data, presented as evidence to the Royal Society’s Policy Study “Science as a Public Enterprise” Call for Evidence.  Here, I summarize activities by members of my Image Bioinformatics Research Group (IBRG) at Oxford University to facilitate data publication and data citation, and thus to help catalyze a cultural shift to a situation in which data publication is as natural a part of research life as is undertaking experiments.

= = =

Data management services and data repositories

We are developing tools and services to assist researchers in their local data management, for their own personal benefit, while facilitating automated data submission to appropriate institutional or subject-specific data repositories, in ways that fit with their normal working practices and impose as little as possible in terms of cognitive overhead – what we term sheer curation.  These include the two-stage data management services we are currently funded to develop by the University Modernization Fund through the JISC DataFlow Project, namely (a) DataStage, a private local data management file system, with automated backup, Web access, and security access control, for use by individual research groups, and (b) DataBank, a cloud-deployable data repository for use by universities, research institutes or large research consortia.  These open source services will be made available for installation by third parties on the Eduserv academic cloud and elsewhere, as required by research groups, institutions and universities both in the UK and internationally.  We seek early adopters!

Curation by addition

For automated data submissions from DataStage to DataBank, that will use the SWORDv2 repository submission protocol to standardize data package ingest, we are intentionally lowering the barriers in terms of metadata requirements for initial data submission, with the the possibility of enriching the metadata at a later date – what we call curation by addition – in order to kick-start the cultural sea change required for data deposition to become routine.  We are trying to avoid the best – the requirement for perfect and complete metadata – becoming the enemy of the good – data publication by any means.

Dryad

We are, through the JISC Dryad-UK Project, working to promote the Dryad Data Repository, a domain-specific repository for biological datasets linked to peer-reviewed journal articles, by bringing additional publishers and journals on board, and enabling Dryad metadata to be published as open linked data.

SWORD

We are also promoting the adoption of SWORDv2 repository communication protocol for data package wrapping, to permit automated deposit to DataBank, Dryad or other SWORD-compliant repositories, and the exchange of metadata between them.

SPAR (Semantic Publishing and Referencing) Ontologies

To enable Dryad, DataBank and similar repository metadata to be published as open linked data, we are creating appropriate data description and data citation ontologies, including FaBiO and CiTO4Data, as part of our suite of SPAR Ontologies, and are using them to provide mappings from the DataCite XML Metadata Kernel to RDF.

Data citation

We are working with DataCite to assign DOIs to Dryad and DataBank datasets, so that data publications become citable, gaining academic credit for the data depositor.

These data citations, when they exist, will fit naturally within the Open Citations Corpus, a collection of some 3.4 million bibliographic citations from within PubMed Central that we have recently established as open linked data, as part of the JISC Open Citations Project.

We have also worked to establish best practice for citing data publications from within the literature, and with one open access journal publisher to influence their Data Publishing Policies and Guidelines to Authors regarding data citation, as detailed in earlier posts on this blog.

Tools for metadata curation

The above tools and services are generic.  Specifically in the biomedical area, we are developing MIIDI, a Minimal Information standard for reporting an Infectious Disease Investigation, to specify the metadata that should for completeness accompany such an investigation, and have recently developed MIIDI Forms, a web tool that facilitates the entry of such metadata, that involves interaction with appropriate web services to enable autocompleting of bibliographic information and specification of geo-coordinates for place names, and permits automated look-up of ontology terms from the NCBI BioPortal

Open Research Reports

We are working to create Open Research Reports, open access structured digital abstracts in both human- and machine-readable form that describe datasets or journal articles that relate to infectious disease, based on MIIDI and to be published in an instant data journal format with DOIs to permit referencing and citation.

Tools for creating data management plans

We have recently started working with the Digital Curation Centre to help improve their DMPonline data management planning tool for creating the data management plans increasingly required to accompany grant applications, and useful for managing the flow of data from funded projects.  If our current funding application is successful, this work will be carried forward in the OXFORD DMPonline Project, in which, in addition to adoption, adaption, customization and integration of the tool for use by University of Oxford researchers, we will develop the following generic improvements to the tool that will be fed back to the DCC as open source enhancements for general use across UK academia and internationally:

a)     creation of DaMO, a simple data management ontology,

b)     use of DaMO to create RDF metadata for data management plans,

c)     SWORDv2-wrapping of data management plans for repository submission, and

d)     creation of DMPBank, a DataBank instance specifically tailored for archiving and publishing data management plans.

Cite this article as: davidshotton, "IBRG projects to facilitate data publication and data citation," in OpenCitations blog, 04/08/2011, https://opencitations.hypotheses.org/250.

Pensoft Journals policy and author guidelines on data publication and citation

In a recent blog post, Heather Piwowar, in discussing the advantages of citing datasets in the reference list of the article, said “No journals have standardized on this approach so far”. However, Pensoft Journals, a publisher that specializes in publishing biodiversity and biological systematics papers, and that has taken the lead in promoting the publication of datasets with DOIs, has exactly such a policy.

Recently, in response to my Data Citation Best Practice Discussion Document [1] discussed in the preceding blog post, I was invited to work with Pensoft Journals to contribute to and help revise their now-published Data Publishing Policies and Guidelines for Biodiversity Data [2].  This 34-page paper has a three-page section on how to cite data in Pensoft Journals.

While recognising that citations of Genbank and similar bioinformatics datasets are by custom made by placing the database accession number somewhere in the text, with no entry in the reference list of the article, we make the following generic recommendation:

“Data citations may relate either to the author’s own data, or to data created and published by others (“third-party data”). In the former case, the dataset may have been previously published, or may be published for the first time in association with the article that is now citing it. All these types of data should, for consistency, be cited in the same manner.

“As is the norm when citing another research article, any citation of a data publication, including a citation of one’s own data, should always have two components:

  • An in-text citation statement containing an in-text reference pointer that directs the reader to a formal data reference in the paper’s reference list.

and

  • A formal data reference within the article’s reference list.

“The data reference in the article’s reference list should contain the minimal components recommended in the DataCite Metadata Kernel v2.0 specification. In DataCite terms: Creator PublicationYear Title Publisher Identifier; alternatively (but meaning the same thing): Author PublicationYear Title DataRepositoryName DOI. These components should be presented in whatever format and punctuation style the journal specifies for its references. The following example demonstrates in general terms what is required.

“In-text citation:

This paper uses data from the [name] data repository at http://dx.doi.org/***** (Jones et al. 2008a), first described in Jones et al. 2008b.

“Data reference in reference list:

Jones A, Bloggs B, Smith C (2008a). Title of data package. Repository name. doi:*****.

“Article reference in reference list:

Jones A, Saul D, Smith C (2008b). Title of journal article. Journal Volume: Pages. doi:###. ”

Pensoft also recommends that the in-text data citation statement in Pensoft journals should be included in the body of the paper, in a separate section named Data Resources situated after the Material and Methods section.  More details are given in the paper [2].

Furthermore, Pensoft has reached an agreement for cooperation in data hosting and developing of data publishing workflows with GBIF, the Global Biodiversity Information Facility, with the Dryad Data Repository and with the Consortium for Barcode of Life.

Clearly, these Pensoft data citation recommendations, which work fine for on-line journals without a numerical limit on the number of citations, would not be feasible in journal articles with a strict limit to the number of citations, which is why Heather’s emphasis of exploring alternative ways for data citation in such cases is important.

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

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

Cite this article as: davidshotton, "Pensoft Journals policy and author guidelines on data publication and citation," in OpenCitations blog, 30/06/2011, https://opencitations.hypotheses.org/156.

Questions of granularity – Dryad’s use of DataCite DOIs for data citation, and the Annotation Ontology

DataCite is an international organisation, founded in 2009, which promotes the use of DOIs (Digital Object Identifiers) for published datasets, in order to establish easier access to research data, to increase acceptance of research data as legitimate contributions in the scholarly record, and to support data archiving to permit results to be verified and re-purposed for future study.

Its founding members were the British Library; the Technical Information Center of Denmark; TU Delft Library; the National Research Council’s Canada Institute for Scientific and Technical Information (NRC-CISTI); California Digital Library; Purdue University; and the German National Library of Science and Technology. Since its foundation, it has been joined by several other leading organisations from around the world, and it therefore provides a stable basis for the ongoing use of DOIs for data.

This recent availability of DOIs from DataCite for the identification of data entities has made all the difference to data repositories wishing to give unique global identifiers to their data holdings, since DOIs are widely recognised and respected throughout the academic world, because of their widespread prior use for identifying journal articles, made possible by CrossRef.

However, in their recent discussion paper Data Citation and Linking, published on 8th June 2011, Alex Ball and Monica Duke of UKOLN at the University of Bath ask:

“At what granularity should data be made citable? If single datasets are given identifiers, what about collections of datasets, or subsets of data?”

Individual data files and metadata documents will, of course, have their own unique internal identifiers within any data repository, but may not have externally resolvable identifiers such as DOIs.  Practice varies.

This post is to explain how DOIs are employed in the Dryad Data Repository, that specializes in publishing data linked to peer-reviewed biological journal articles, since it is both elegant and addresses at least some of the issues raised by Alex and Monica.

The Dryad DOI usage policy is described at https://www.nescent.org/wg_dryad/DOI_Usage, and involves assigning unique DOIs to each version of every data package, and to each version of every data file, in a principled and easy-to-understand manner. In summary:

  • Each data package is given a DataCite DOI, which can be versioned by adding “.2”, “.3”, etc. after the original DOI to create new DOIs for new versions of the same data package.
  • Within each data package, each data file has a unique DOI defines by suffixing the data package DOI with “/1”, “/2”. etc., with versions indicated as for data packages.

Thus the third version of the second data file in the second version of a Dryad data package would have a DOI of the form doi:10.5061/dryad.1234.2/2.3.

One might argue that it would result in an awfully large number of DOIs if a single data package was made up of thousands of data files. True, but numbers themselves are limitless and free, and the cost of a DataCite DOI is small relative to the cost of data creation and preservation. The real problem at present is lack of identifiable, citable data entities within repositories – to have so many that the cost of DOIs becomes an issue should be regarded as an achievement, not a problem!

Dryad does not have a mechanism for assigning identifiers to a portion of a data file (“a subset of data”), and DOIs are probably not the correct identifiers for that purpose, since they are primarily designed for citation and resource discovery.

A more appropriate method for identifying portions of a data file, or of any other digital object or document, is to use the Annotation Ontology (AO) developed by Paolo Ciccarese of Harvard University, described at http://code.google.com/p/annotation-ontology/wiki/Homepage. AO can be used to identify and annotate portions of a wide variety of resources such as HTML, PDF, Word, Excel, XML documents, images, videos, databases, web services, experimental data and metadata files. Paolo is currently working with a group in Harvard that focuses on biodiversity, who are using OA to address databases and data, and he anticipates publishing version 2.0 of AO in September.

Cite this article as: davidshotton, "Questions of granularity – Dryad’s use of DataCite DOIs for data citation, and the Annotation Ontology," in OpenCitations blog, 30/06/2011, https://opencitations.hypotheses.org/148.

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