=Paper=
{{Paper
|id=Vol-2184/paper-01
|storemode=property
|title=Creating Open Citation Data with BCite
|pdfUrl=https://ceur-ws.org/Vol-2184/paper-01.pdf
|volume=Vol-2184
|authors=Marilena Daquino,Ilaria Tiddi,Silvio Peroni,David Shotton
|dblpUrl=https://dblp.org/rec/conf/semweb/DaquinoTPS18
}}
==Creating Open Citation Data with BCite==
https://ceur-ws.org/Vol-2184/paper-01.pdf
Creating Open Citation Data with BCite
Marilena Daquinoφ , Ilaria Tiddiϵ , Silvio Peroniφ , and David Shottonϯ
φ
Department of Classical Philology and Italian Studies, University of Bologna,
Bologna, Italy
ϵ
Department of Computer Science, VU University Amsterdam, Amsterdam, The
Netherlands
ϯ
Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom
marilena.daquino2@unibo.it, ilaria.tiddi@vu.nl, silvio.peroni@unibo.it,
david.shotton@oerc.ox.ac.uk
Abstract. In the past year we have seen the release of a huge volume
of open bibliographic citation data, thanks primarily to the efforts of the
Initiative for Open Citations (I4OC, https://i4oc.org). However, the
incomplete coverage of these data is one of the most important issues
that the open scholarship community is currently facing. In this paper
we present an approach for creating open citation data while supporting
journal editors in their task of curating the reference lists contained
within articles submitted to them for publication. Our contributions are
twofold: (a) a basic workflow that supports editors in the management
and correction of bibliographic references, and (b) a tool, called BCite,
that creates open citation data compliant with an existing RDF-based
citation repository: the OpenCitations Corpus4 .
Keywords: Citation Data Curation, Open Citation Data, Open Science,
OpenCitations, Semantic Publishing
1 Introduction
The Initiative for Open Citations (I4OC, https://i4oc.org) was launched in
April 2017 to persuade publishers, who were already depositing their article
references in Crossref (https://crossref.org), to make them open and accessible
for reuse. More generally, I4OC campaigned for bibliographic citations to be
structured (i.e. expressed in machine-readable formats), separate (i.e. available
without the need to access the source bibliographic products in which the citations
are created) and open (i.e. freely accessible and reusable) data – what we will
term ’open citation data’ in this paper (see [10] for a technical definition
of “open citation”). As a consequence of these activities, about 500 million
citation links from 19 million published articles have been made open during
the past year and are now available through the Crossref API (https://api.
4
This work will be published as part of the book “Emerging Topics in Semantic
Technologies. ISWC 2018 Satellite Events. E. Demidova, A.J. Zaveri, E. Simperl
(Eds.), ISBN: 978-3-89838-736-1, 2018, AKA Verlag Berlin”.
2 Marilena Daquino et al.
crossref.org). However, they are not exposed natively using Semantic Web
technologies. To achieve this further end, several projects and organisations
supporting I4OC, such as OpenCitations (http://opencitations.net) [9], are
active in curating open citation data in RDF, so as to be queryable using
SPARQL and downloadable in various formats using the normal web content
negotiation mechanism.
Despite the success of the I4OC campaign, the incomplete coverage of such
open citation data is one of the most important issues that the open scholarship
community is currently facing. This is due to at least two factors. First, some
academic disciplines, in particular the Social Sciences and the Humanities, are
inherently under-represented in such citation datasets. In fact, bibliographic
references included in articles within these disciplines tend to be missed even
in the major commercial citation indexes such as Scopus (https://www.
scopus.com/) and Web of Science (https://clarivate.com/products/web-
of-science/). For instance, according to our knowledge, while the article [3]
(published in the journal Conservation Science in Cultural Heritage) references
the book chapter [13], the related citation is not reported in any citation index.
On the other hand, several smaller journals and/or publishers do not have the
financial capabilities nor the technical support to submit their citation data to
Crossref so as to expose them in a centralized repository as open citation data,
where they can easily be reused by other parties.
Three particular research questions (RQs) can be derived by analysing the
aforementioned situation:
1. Is it possible to develop a workflow that allows stakeholders (e.g. a publisher,
a journal editor, a researcher) to increase the coverage of existing RDF-based
open citation datasets?
2. To which extent can stakeholders benefit of such a workflow in the course of
their daily activities?
3. How much additional data would such a workflow contribute to the existing
RDF-based open citation datasets?
A possible solution to the aforementioned questions is to develop or adopt
easy-to-use interfaces that allow users to create new RDF citation data while,
at the same time, supporting them in some routine task involving bibliographic
data, specifically the task of checking that the reference list of an accepted work
has been correctly formatted according to specific requirements of the publisher
(e.g. the reference style, the selection of the information included, presence of
identifiers and external links) before it appears in the final version-of-record of
the work.
To this end, we have developed a prototype tool called BCite, which we
introduce in this paper. BCite is based on a strategy of reciprocal benefit,
enabling editors to obtain ’clean’ verified references for the citing article they
have in hand, while at the same time transforming those references into RDF
data so as potentially to contribute to a public citation corpus. BCite is designed
to provide a full workflow for citation discovery, allowing users to specify the
references as provided by the authors of the article, to retrieve them in the
Creating Open Citation Data with BCite 3
required format and style, to double-check their correctness, and, finally, to
create new open citation data according to the OpenCitations Data Model [11],
so as to permit their future integration into the OpenCitations Corpus (OCC)
[9], i.e. the RDF dataset of open citation data maintained by OpenCitations.
We have undertaken a preliminary evaluation of BCite’s ability to answer the
aforementioned research questions. The outcome of our experiments, albeit with
a limited set of input documents, is encouraging and shows that the current
coverage of citation data in the OpenCitations Corpus could easily be extended
by using the application.
The rest of the paper is structured as follows. In Section 2 we introduce
the materials and methods we have used for implementing BCite. In Section 3
we introduce BCite by briefly describing its components and the workflow it
implements. In Section 4 we evaluate our tool by using the reference lists included
in some published articles of different disciplines. In Section 5 we introduce some
of the most important related works in the area. Finally, in Section 6 we conclude
the work sketching out some future works.
2 Material and Methods
OpenCitations is a scholarly infrastructure organisation dedicated to provision of
open bibliographic citations and associated tools and services. To date, the main
work of OpenCitations has been the creation and current expansion of the Open
Citations Corpus (OCC) [9], an open repository of scholarly citation data made
available under a Creative Commons public domain dedication, which provides
in RDF accurate citation information (bibliographic references) harvested from
the scholarly literature. These are described using the SPAR Ontologies [12]
according to the OpenCitations Data Model [11], and are made freely available
so that others may freely build upon, enhance and reuse them for any purpose,
without restriction under copyright or database law. The contents of OCC can
be explored by humans using OSCAR, the OpenCitations search interface, and
navigated by means of its browse interface LUCINDA. Programmatic access
to the OCC is available either using its SPARQL endpoint or its REST API
(coming Q3 2018). Additionally, metadata for individual bibliographic entities
can be accessed via a simple HTTP request using their individual URIs (e.g.
https://w3id.org/oc/corpus/br/1).
The ingestion of citation data into OCC is currently handled by two Python
modules, the Bibliographic Entries Extractor (BEE) and the SPAR Citation
Indexer (SPACIN). While BEE is responsible for the creation of JSON files
containing reference lists of published articles, SPACIN processes each of these
JSON files, retrieves metadata about all citing/cited articles by querying the
Crossref and the ORCID APIs, and stores the generated RDF resources both
in the file system (as JSON-LD files) and in the OCC triplestore. Parts of these
two Python modules have been reused for the development of BCite, which
consequently creates open citation data compliant with the OpenCitations Data
Model.
4 Marilena Daquino et al.
3 BCite: a bibliographic reference correction service
BCite is a Web application that (a) facilitates some of the tasks of a user
(e.g. a journal editor) since it allows him/her to semi-automatically curate
the list of bibliographic references included in a soon-to-be-published article,
and, simultaneously, (b) creates RDF-based open citation data compliant
with the OpenCitations Data Model. According to the OpenCitations Data
Model specification, we will refer to an article and to the bibliographic
references included in its reference list as the citing bibliographic resource
and its bibliographic entries respectively, to the referenced works as the cited
bibliographic resources, and to the links between citing and cited works as
citations.
Components. BCite is developed as a Python Web application (using
the web.py framework) that can be run on a local machine. It is available
on GitHub at https://github.com/opencitations/bcite, and includes the
following logical components: (i) the BCite App, a web interface for data entry
and data curation; (ii) the BCite triplestore, a Blazegraph instance (https:
//www.blazegraph.com) for storing the generated RDF triples, the triplestore
that is used by OpenCitations for allowing the access to all its RDF repositories;
(iii) the BCite API, which is responsible for using the OpenCitations Python
modules for creating open citation data and storing them in the triplestore. The
BCite workflow and its components are shown in Fig. 1.
Fig. 1. BCite’s workflow to clean bibliographic data and generate open RDF citations.
Workflow. BCite includes three main activities: the creation of the metadata
for a new citing bibliographic resource, the lookup of the cited bibliographic
resources specified by its bibliographic entries (and if necessary the correction of
those entries using the metadata returned for the cited bibliographic resources),
and the update of the triplestore.
Creating Open Citation Data with BCite 5
Creating a citing bibliographic resource. At first, the user inputs via the BCite
App all the metadata of a citing bibliographic resource (authors, title, journal,
volume, issue, year, publisher, and DOI) and the list of bibliographic entries
to be matched. A citation style can also be selected for the formatting of the
output references. A request is then sent to the BCite API, which first creates
a RDF representation of the citing bibliographic resource compliant with the
OpenCitations Data Model, and then writes the generated triples into the BCite
triplestore.
Reference lookup. For each of the citing bibliographic resource’s references
(bibliographic entries) provided by the user, a request is sent to the BCite API
to look for matches with the cited bibliographic resources within the BCite
triplestore. If no matches are found in the BCite triplestore, the BCite API
uses the OpenCitations scripts to send a request to the Crossref API for any
available metadata on the cited bibliographic resource – and to the ORCID API
for author disambiguation purposes. For each of the matched references, an RDF
entity for the cited bibliographic resource is either retrieved (if already present
in the BCite triplestore) or created (if returned by the Crossref API). Then, the
BCite API sends back to the BCite App the text of the bibliographic entry of
the cited bibliographic resource, formatted according to the requested citation
style, for delivery to the user. If no record is found within the BCite triplestore
and the Crossref API does not return any match, an empty string is returned
instead.
Correction and update. As shown in Fig. 2, all the results are presented to
the user in a table, with the submitted references from the citing bibliographic
resource in the first column, and the proposed matched or corrected references
in the second column. The user can then (a) accept the proposed text of the
bibliographic entry as is; (b) accept it after modifying some part of it within
the table itself; or (c) reject the proposed bibliographic entry when it does not
specify the intended cited bibliographic resource, keeping instead the originally
submitted text for the bibliographic entry. Finally, all the accepted/corrected
bibliographic entry texts are sent back to the BCite API, and all the triples
relevant to the citing and cited bibliographic resources are stored in the
BCite triplestore, including the related provenance information according to the
OpenCitations Data Model. An example of the RDF statements generated by
BCite is shown as follows (in JSON-LD):
{
"@context ": "https :// w3id.org/oc/corpus/context.json",
{
"a": [ "document", "article" ],
"citation ": [
"http :// localhost :8000/ corpus/br/21",
"http :// localhost :8000/ corpus/br /17"
],
"contributor ": [
"http :// localhost :8000/ corpus/ar/7",
"http :// localhost :8000/ corpus/ar/5",
"http :// localhost :8000/ corpus/ar/3",
"http :// localhost :8000/ corpus/ar/4",
"http :// localhost :8000/ corpus/ar/6"
],
6 Marilena Daquino et al.
"format ": "http :// localhost :8000/ corpus/re/1",
"identifier ": [
"http :// localhost :8000/ corpus/id/5",
"http :// localhost :8000/ corpus/id/3"
],
"iri": "http :// localhost :8000/ corpus/br/5",
"label ": "bibliographic resource 5 [br/5]",
"part_of ": "http :// localhost :8000/ corpus/br/6",
"prism:publicationDate ": {
"a": "year_month_day",
"value ": "2015 -03 -09"
},
"reference ": [
"http :// localhost :8000/ corpus/be/7",
"http :// localhost :8000/ corpus/be/5",
"http :// localhost :8000/ corpus/be/8",
"http :// localhost :8000/ corpus/be/6",
"http :// localhost :8000/ corpus/be/3",
"http :// localhost :8000/ corpus/be/4"
],
"title ": "Setting our bibliographic references free: towards open citation
data"
},
{
"a": "role",
"iri": "http :// localhost :8000/ corpus/ar/4",
"label ": "agent role 4 [ar/4]",
"next ": "http :// localhost :8000/ corpus/ar/5",
"role_of ": "http :// localhost :8000/ corpus/ra/4",
"role_type ": "author"
},
{
"a": "agent",
"fname ": "Peroni",
"gname ": "Silvio",
"iri": "http :// localhost :8000/ corpus/ra/4",
"label ": "responsible agent 4 [ra /4]"
},
...
}
4 Evaluation
A preliminary evaluation of BCite was performed with the goal of demonstrating
that our tool allows us to answer the three research questions mentioned in
the introduction, i.e. to implement a mechanism to increase the coverage of
existing RDF-based open citation datasets and to facilitate the editor’s task
of reference list processing of to-be-published journal articles. In particular, we
were interested in (i) measuring the number of the references returned by the
BCite API; and (ii) quantifying the contribution of new citation entries to the
OpenCitations Corpus (OCC), i.e. how much new knowledge could, in principle,
be added to it, bearing in mind that the OCC presently contains mainly articles
coming from the biomedical and life science domains. All the data gathered
during the experiment are available in [14].
4.1 Use cases
To demonstrate the aforementioned points, we use three journal articles from
different disciplines. They are introduced as follows.
Creating Open Citation Data with BCite 7
Fig. 2. The BCite App. The editor inputs metadata about citing and cited entities, and
obtains the bibliographic references formatted according to a selected citation style.
A work by Hammarfelt and Haddow [4] published by the Journal of the
Association for Information Science and Technology (JASIST), that deposits all
its bibliographic metadata in Crossref, where, presumably, a large proportion
of the bibliographic resources referenced by the reference entries contained in
the journal’s articles are included in Crossref, due to the authoritativeness of
the journal in its domain – it is one of the top-rated journals in Library and
Information Science. In this scenario, aimed at assessing mostly the ability of
BCite to obtain the correct text of the reference entries in the specified format,
we modified the reference list of the article to reproduce common mistakes that
can be possibly introduced by either article authors or bibliographic curators
(missing authors, wrong publication years, incomplete references, etc.). We
expected that BCite would return an high number of ’known’ reference entries,
8 Marilena Daquino et al.
and that some of these references would already be present in the OCC, due to
the authoritativeness of the journal.
A work by Biagetti [2] from the Journal of Library and Information Science
(JLIS). While the bibliographic data of the journal are curated and indexed in
major citation indexes, this article belongs to the Digital Humanities area that
is not fully represented in Crossref – in particular the pure Humanities section.
Hence, we expected that BCite would return a lower number of ’known’ reference
entries. However, in principle, the contribution of new citation data to the OCC
should still be high. In fact, it is likely that the cited bibliographic resources are
not already present in the Corpus, since it covers mainly a different domain.
A work by Citti [3] from a minor journal of the Humanities domain, i.e.
Conservation Science in Cultural Heritage. This journal usually contains articles
that cites older bibliographic resources from the same domain, which is poorly
covered in Crossref, as mentioned above. Therefore, we expected that BCite
would not be able to retrieve a large number of reference entries. However, due
to the scholarly domain under consideration, we expected that almost all the
retrieved bibliographic resources could be added to the OCC as new citations,
since they were likely not to be already contained within the Corpus.
4.2 Results
As shown in Table 1, for the aforementioned articles (“Citing article”), we
recorded the total number of reference entries in their reference lists (column
“Reference entries”); the number of the reference entries – and, consequently,
the related cited bibliographic resources – returned by BCite (column “Returned
by BCite”); the number of such cited bibliographic resources that were already
present in the OCC (column “Already included in the OCC”), and thus the
potential contribution to the OCC from the bibliographic resources created
by BCite that were not previously included in the OCC (column “Potential
contribution to the OCC”).
4.3 Discussion
While these studies are at a very early stage, some conclusions can already be
drawn. First, we can confirm that all the reference entries returned by BCite in
the test case 1 were correct, even when the reference entries specified initially as
input had been modified to include errors. Indeed, no mismatches were produced
by BCite for such altered references. This suggests that BCite could provide good
support for editors by automating the reconciliation of bibliographic data.
The outcomes of the first two test cases (1 and 2) are pretty close. While,
as expected, BCite returned more information for the reference entries in the
Hammarfelt and Haddow’s article [4] (i.e. 73.8% of the references were found),
the figures of those already included in the OCC and the related potential
contribution to the Corpus – i.e. the number of cited bibliographic resources
returned by BCite that were not included in the OCC – were similar. In
fact, we had that only 21.4% (test case 1) and 16.5% (test case 2) of the
Creating Open Citation Data with BCite 9
Table 1. The outcomes of our experiments run on the three journal articles considered.
The figures track the number of reference entries in the citing articles, the number of
the results returned by BCite, the number of such resources already included in the
OCC (which is a subset of the previous one), and the potential contribution that the
result of BCite can bring to the OCC.
Potential
Citing article Returned by Already included
Reference entries contribution to
(and test case) BCite in the OCC
the OCC
Hammarfelt and
Haddow [4] (test 42 31 (73.8%) 9 (21.4%) 22 (70.9%) out of 31
case 1)
Biagetti [2] (test
30 15 (50.0%) 5 (16.5%) 10 (66.6%) out of 15
case 2)
Citti [3] (test case
40 7 (17.5%) 0 (0%) 7 (100%) out of 7
3)
bibliographic resources returned by Bcite that were already included in the OCC,
thus resulting in a potential addition of 70.9% (test case 1) and 66.6% (test case
2) additional bibliographic resources (among the returned ones) to the Corpus.
The outcomes of the test case 3 were more radical, since only a limited
amount of input reference entries (17.5% of the total) were returned by BCite.
However, the potential contribution to the OCC is incredibly high, since, in this
case, none of the returned bibliographic resources where already available in the
Corpus.
Recalling the research questions introduced in Section 1, these outcomes
reveal that editors, in principle, could give a significant contribution to the OCC
through the addition of the data retrieved by using BCite. This would also allow
us to extend significantly the actual coverage of the OCC, since to date it has
been mainly covered the biomedical and life sciences works. In addition, in all
the three test cases, the reference entries that were not returned by BCite (i.e.
26.2%, 50%, and 82% of the total respectively) were also missing in Crossref and
in the OCC. A possible reason for this could be related to the publication dates
of the cited bibliographic resources (since older publications are less likely to be
openly accessible and available in open indexes), to publications in non-English
languages (e.g. publications in Italian), or to publications in specific domains
(e.g. Humanities).
5 Related Works
Plenty of works have been published in the past years on the main topics touched
on in this paper: curation methodologies and tools, and the promotion and
release of open scholarly data.
Curation methodologies have been extensively studied over the years – see,
for instance [1] [5] [7]. Tools to support authors for data curation have been
also proposed, such as Recite (https://reciteworks.com/) which however
10 Marilena Daquino et al.
only supports in-text reference checking. Other tools have been released to
help users and librarians in the management of citations (e.g. RefWorks,
EndNote, Mendeley and Zotero, compared at https://en.wikipedia.org/
wiki/Comparison_of_reference_management_software), although these do
not offer the production of RDF data.
A number of initiatives for producing open scholarly bibliographic data
have been also proposed in the recent years, in addition to the OpenCitations
Corpus [9]. For instance, OpenAIRE (https://www.openaire.eu/) provides a
number of services (from deposition to discovery to statistics) for thousands
of Open Access scholarly datasets, although it currently does not include
article citations. Springer Nature has recently published its SciGraph (http:
//scigraph.springernature.com), i.e. an open knowledge graph of Spinger
Nature’s scholarly data, but again this does not include article citations.
Scholarly Data (http://www.scholarlydata.org/) [8] allows the creation and
exploration of data about Computer Science Conferences and Workshops.
WikiCite includes a series of a collaborative activities to build a bibliographic
database in Wikidata using a semi-automatic workflow. In the context of the
Linked Open Citation Database, the work of [6] presents a semi-automated
system for the creation and storage of citation data to support digital libraries
in the data curation workflow.
6 Conclusions
In this paper we presented BCite, a service for bibliographic data curation and
generation of RDF-based open citation data compliant with the OpenCitations
Data Model. We showed how a simple tool based on a strategy for reciprocal
benefit can support journals (especially the smaller ones that have less resources
for curatorial activities) and their editors, aiding them in the process of
bibliographic data cleaning, while also providing potential contributions to an
existing open citation data repository, namely the OpenCitations Corpus.
In the future, we plan to organise an extensive user-based evaluation of
BCite in order to assess also its usability when it is used for addressing the
task of bibliographic reference correction in real environments (e.g. in journals
management systems such as the Open Journal Systems, https://pkp.sfu.ca/
ojs/). In addition, we also plan to integrate BCite within the OpenCitations
ingestion workflow, so as to import additional open citation data directly into
the OCC from the BCite App. The current implementation of BCite does not
support such direct import, since a careful study about possible issues, e.g. the
openness of the license associated to the to-be-published articles, as well as
the trustworthiness of BCite users,data quality issues and compliancy with the
evolving OpenCitations Data Model, must be performed in advance by test users
in association with the OpenCitations team.
Creating Open Citation Data with BCite 11
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