OpenCitations Team

[The creation of the ]{style="font-weight: 400"}[[Open Biomedical
Citations in Context Corpus
(CCC)]{style="font-weight: 400"}](https://wellcome.ac.uk/funding/people-and-projects/grants-awarded/open-biomedical-citations-context-corpus)[
is the goal of a one-year project funded by the
]{style="font-weight: 400"}[[Wellcome
Trust]{style="font-weight: 400"}](https://wellcome.ac.uk/)[. The aim is
to create a new open corpus of bibliographic and citation data that
contain detailed information about individual in-text reference pointers
in biomedical journal articles. The project is led by Professor Silvio
Peroni of the ]{style="font-weight: 400"}[[Research Centre for Open
Scholarly
Metadata]{style="font-weight: 400"}](https://openscholarlymetadata.org/)[
(University of Bologna), is being undertaken by Dr Marilena Daquino
(University of Bologna), and actively involves the Oxford e-Research
Centre (University of Oxford), the École de Bibliothéconomie et des
Sciences de l'Information (Université de Montréal), and the Centre for
Science and Technology Studies (CWTS), (Leiden
University).]{style="font-weight: 400"}

[An in-text reference pointer is a textual device (e.g. "\[1\]", or
"(Peroni and Shotton 2012)") that appears in the main text of a citing
work and denotes a bibliographic reference listed in the Bibliography
section of the citing work. While a single in-text reference pointer
uniquely denotes a single bibliographic reference, it can occur together
with one or more other pointers, forming an in-text reference pointer
list that denotes several references (e.g. "\[5-13\]", or "(Peroni and
Shotton 2012; Peroni and Shotton 2019)"). In-text reference pointers may
appear in several places within the same citing publication (e.g.
Introduction, Methods, Discussion), may occur within different document
components (e.g. body text, figure captions, tables), and may address
the cited publication for different purposes (e.g. as the source of an
experimental protocol, as a data source, or for general background
information).]{style="font-weight: 400"}

[Unfortunately, current citation indexes contain no information about
in-text reference pointers, such as the number of times a particular
work is referenced in the citing work, the text of the sentences in
which they occur, or the rhetorical purpose of such
citations.]{style="font-weight: 400"}

[Having data at the level of individual in-text reference pointers
offers many new opportunities, enabling one: (1) to distinguish between
works that are referenced just once in a citing publication and those
that are referenced multiple times, and thereby (potentially) to
distinguish when a citation is fundamental for the understanding or the
development of the citing work, or merely incidental; (2) to see which
in-text reference pointers occur together (e.g. in the same sentence or
the same paragraph), thus, potentially, to infer similarities between
the co-cited publications; and (3) to determine in which specific
sections of the publication these in-text references occur (e.g.
Introduction, Methods, Results), and thus, potentially, by means of
textual analysis of the citation contexts, to retrieve the rhetorical
functions of the citations -- i.e. the reason why an author cites
another work. ]{style="font-weight: 400"}

[The goal of the CCC Project is to provide stakeholders with an exemplar
Linked Open Data corpus, created from the open access biomedical
research literature, that is tailored for such deep citation analyses.
The corpus will be a new member of the collection of OpenCitations
datasets, and will be accompanied by services for accessing and querying
data.]{style="font-weight: 400"}

[In the CCC Project, we have achieved or are currently dealing with the
following developments:]{style="font-weight: 400"}

- **Extending the OpenCitations Data Model (OCDM).**[ The OpenCitations
  Data Model has been extended and enriched with new terms and relations
  to represent bibliographic entities related to in-text reference
  pointers, such as the in-text reference pointers themselves, in-text
  reference pointer lists, discourse elements (e.g. sections,
  paragraphs, sentences), and annotations on citations, bibliographic
  references and in-text reference pointers. In addition, the provenance
  layer of the data model has been revised to provide meaningful
  provenance information in a more compact way. A revised version of the
  OCDM including these terms was published on November 8, 2019, and it
  is available on Figshare \[1\].]{style="font-weight: 400"}
- **Extending the OpenCitation harvesting and data re-engineering
  pipeline.**[ The CCC Project leverages existing OpenCitations
  technologies for building this new corpus, using as input articles
  from the Open Access Subset of biomedical literature hosted by Europe
  PubMed Central (EPMC) and encoded in XML. The OpenCitations pipelines
  for knowledge extraction (i.e. the software called BEE) and for data
  re-engineering (i.e. the software called SPACIN) have been enhanced so
  as to harvest relevant information from the full-text of the XML
  sources provided by EPMC, rather than just the reference lists,  and
  to transform these data into RDF according to the revised OCDM. The
  ]{style="font-weight: 400"}[[source
  code]{style="font-weight: 400"}](https://github.com/opencitations/ccc)[
  of the new pipeline is available on GitHub.]{style="font-weight: 400"}
- **Creating InTRePID, a new persistent identifier for in-text reference
  pointers.**[ Different in-text reference pointers denoting the same
  bibliographic reference have distinct logical, rhetorical and textual
  contexts wherein they occur. To permit them to be identified
  individually and handled properly, we have recently developed a new
  persistent identifier, the ]{style="font-weight: 400"}[**In-Text
  Reference Pointer Identifier
  (InTRePID)**](https://doi.org/10.6084/m9.figshare.11674032)[, for
  identifying individual in-text reference pointers relating to an open
  bibliographic citation. The InTRePID is based on the Open Citation
  Identifier (OCI), currently being used to identify the \>624 million
  citations present in the new release of COCI, the OpenCitations Index
  of Crossref open DOI-to-DOI citations, described in the
  ]{style="font-weight: 400"}[[previous blog
  post]{style="font-weight: 400"}](https://opencitations.hypotheses.org/997)[.
  The formal definition of an InTRePID is available on Figshare \[2\].
  In addition, an ]{style="font-weight: 400"}[[InTRePID Resolution
  Service]{style="font-weight: 400"}](http://opencitations.net/intrepid)[
  has been developed (currently in beta-testing) to facilitate the
  retrieval of the metadata relating to in-text reference pointers. At
  the moment, a subset of the CCC corpus is available online for testing
  the InTRePID Resolution Service.]{style="font-weight: 400"}
- **Development of services for accessing and querying the Citations in
  Context Corpus.**[ Along with the development of the CCC itself, we
  are also developing services for querying data within the CCC. In
  particular, we are currently working to extend the RAMOSE software to
  provide an API for accessing the CCC triplestore. This CCC API will
  permit users to access the CCC corpus and retrieve detailed
  information about in-text reference pointers and their related
  annotations in a variety of human- and machine-readable formats. The
  ]{style="font-weight: 400"}[[source
  code]{style="font-weight: 400"}](https://github.com/opencitations/ramose)[
  of the API Manager is available on GitHub. The configuration file for
  querying the CCC corpus is still in the process of
  development.]{style="font-weight: 400"}

[Moreover, we are currently working to evaluate the content data quality
of the CCC corpus and to develop reconciliation activities with
information stored in Crossref. Specifically, by means of new validation
methods, we are testing whether the extracted in-text reference pointers
are complete (i.e. determining that ]{style="font-weight: 400"}***all***
[the in-text reference pointers for a particular bibliographic reference
have been correctly extracted from the text), and that in-text reference
pointer lists (e.g. "\[5-13\]") have been correctly parsed to extract
all the implicit pointers (in this case "\[6\]", "\[7\]", "\[8\]",
"\[9\]", "\[10\]", "\[11\]" and "\[12\]"), and to associate them
correctly with the appropriate bibliographic references that they
denote. This activity is fundamental, in order to address the diverse
citation styles adopted by different journals and to overcome possible
incoherencies in the publishers' XML markup of the articles. Secondly,
whenever a DOI is not specified for the citing or cited publications in
the full-text of the citing publication, a text search using the
]{style="font-weight: 400"}[[Crossref
API]{style="font-weight: 400"}](https://www.crossref.org/services/metadata-delivery/rest-api/)[
is performed in order to match possible candidates and supply the
missing DOI. This reconciliation process itself can be error-prone since
recommended matches are obtained by means of a non-transparent scoring
mechanism. Therefore we are currently testing the application of a
scoring threshold that will eliminate false positives and provide us
only with correct results.]{style="font-weight: 400"}

[The deployment of the enhanced OpenCitations pipeline for populating
the CCC corpus automatically is planned to start in the next weeks. For
more details and to provide suggestions, please
]{style="font-weight: 400"}[[contact
us]{style="font-weight: 400"}](mailto:marilena.daquino@opencitations.net)[!]{style="font-weight: 400"}

**References**

[\[1\] Marilena Daquino, Silvio Peroni and David Shotton (2019). The
OpenCitations Data Model. Version 2.0. Figshare. DOI: 
​]{style="font-weight: 400"}[[https://doi.org/10.6084/m9.figshare.3443876]{style="font-weight: 400"}[ ]{style="font-weight: 400"}](https://doi.org/10.6084/m9.figshare.3443876)

[\[2\] David Shotton, Marilena Daquino and Silvio Peroni (2020). In-Text
Reference Pointer Identifier: Definition. Figshare.  DOI:
]{style="font-weight: 400"}[[https://doi.org/10.6084/m9.figshare.11674032]{style="font-weight: 400"}](https://doi.org/10.6084/m9.figshare.11674032)


The creation of the Open Biomedical Citations in Context Corpus (CCC) is the goal of a one-year project funded by the Wellcome Trust. The aim is to create a new open corpus of bibliographic and citation data that contain detailed information about individual in-text reference pointers in biomedical journal articles.

Messaggi di Rogue Scholar

The Open Biomedical Citations in Context Corpus: Progress Report