This blog post is the first of a series which will highlight some of the ways OpenCitations is currently adopted and used by the community. This series also gives us the chance to thank our users for trusting OpenCitations and for giving us the opportunity to improve our services through their feedback. With you, OpenCitations is a drop generating countless circular waves of innovation in research.
The dblp computer science bibliography (https://dblp.org/) is the on-line reference for bibliographic information on major computer science publications, with the mission “to support computer science researchers in their daily efforts by providing free access to high-quality bibliographic meta-data and links to the electronic editions of publications”.
Currently, dblp indexes over 7 million publications, published by more than 3.4 million authors. Despite the small team of editors from the Schloss Dagstuhl, which run the service, in the last few years, dblp has grown from a small-scale server to a service used by thousands of people worldwide.
In 2022, they released the dblp Knowledge Graph, and in June 2024 they released a first major extension to the dblp KG by adding publications venues (e.g., journals and conference series) as first-class entities to the graph. This new release also includes a new property (i.e. dblp:omid) to link dblp publications to their OpenCitations Meta Identifier (OMID). This ID is crucial for making use of open citation and reference data available in OpenCitations since it is the internal identifier we use to identify every bibliographic entity (publications, authors, venues, etc.) stored in our system.
Indeed, the dblp computer science bibliography doesn’t collect and store citation information itself, but instead ingest directly the open citation data released by OpenCitations. Using the linkage provided by OMID, the dblp users can perform citation analyses using its SPARQL query service.
Dblp has published a detailed guide to help “beginners” find data in the dblp Knowledge Graph, and you can find it here.
If you are looking for more information about the dblp project, please explore their exhaustive F.A.Qs.
Blog post by Ivan Heibi (University of Bologna), Arianna Moretti (University of Bologna) and Chiara Di Giambattista (University of Bologna).
In the past five years, the OpenCitations data has been enriched with numerous new indexes of open citation data from different sources. However, the quantity and diversification of the ingested information have raised several issues, which recently made it essential to conduct a complete revision of the ingestion workflow. The result was a revolution in the way OpenCitations data is delivered. In this blog post, we will explain the context and challenges raised by the old procedure. Then, we will present the new ingestion workflow, designed to produce just two comprehensive collections: OpenCitations Index, collecting open citation data, and OpenCitations Meta, for the open bibliographical metadata.
Once upon a time, there were five OpenCitations indexes…
In 2018, OpenCitations released the kickoff version of its first citation index, COCI (citations from Crossref), which contained around 300 million citation links derived from the subset of the reference lists in the Crossref database, where citing and cited entities were identified using Digital Object Identifiers (DOIs). COCI gathered citations with associated metadata in compliance with the recommendations from the Initiative for Open Citations (I4OC) that citation data should be structured, separable, and open, thus marking a turning point by providing a disruptive and free and open alternative to earlier sources such as Google Scholar, which provided freely accessible data although not downloadable, and Web of Science or Scopus, which demanded paid access.
In a short time, COCI became a competitive and trusted index of citation data, used by numerous institutional repositories, including B!son and Optimeta. In 2021, COCI was taken into account in a comparative study with the most relevant sources in the landscape, including the proprietary ones, which showed its coverage approaching parity with those of the other sources involved in the analysis (Microsoft Academic, Scopus, Dimensions, and Web of Science). At the time of its most recent update in January 2023, COCI counted more than 1.4 billion citations. The reason behind this outstanding number lies in several factors, including Elsevier’s endorsement of the Declaration on Research Assessment (DORA) in December 2020, leading to the open release via Crossref of the reference lists of the articles published in all its journals, and confirming the value of initiatives such as the Initiative for Open Citations (I4OC).
However, before this change of heart, in 2019 OpenCitations had tried to narrow the open citations coverage gap by launching its second index, the Crowdsourced Open Citations Index (CROCI). This index allowed publishers and scholars to contribute directly by uploading crowdsourced open citations into the OpenCitations infrastructure.
In December 2022, a new concrete step towards a factual plurality of OpenCitations indexes was taken by the ingestion of new data sources into the infrastructure, with the publication of the inaugural dumps of DOCI (citations from DataCite) and POCI (citations from PubMed). In June 2023, the first version of the OROCI (citations from OpenAIRE) dump was released too, and JOCI (citations from JALC) is expected to be available by the end of November 2023, for a total of five collections from different sources.
Why a new workflow? The issues with multiple sources management and new challenges
While having such a variety and richness of indexes helped present the extent of OpenCitations sources, the recent increment in the number of sources and the diversification of data integrated led to two primary issues:
the necessity to handle the ingestion of new identifier types in a DOI-based software infrastructure, and
the consequent possibility of encountering the same citation expressed by several sources with different identifiers.
Moreover, it soon became evident the need to optimize the reuse of the already developed software components to facilitate the metadata crosswalk processes between the new sources’ data models and the OpenCitations Data Model, with the aim to define a functional and easily extendable workflow to be easily reused when it comes to incorporating new data sources, which should be:
sufficiently generic to establish a globally unique procedure;
customizable enough to capture the necessary information within each of the specific data models and formats.
As a solution, we decided to use OpenCitations Meta, the new OpenCitations database and tool for managing bibliographic data related to the publications involved in the citations. OpenCitations Meta makes it possible to assign each entity involved in a citation an internal identifier, nominally the OpenCitations Meta Identifier (OMID), to which all the associated persistent identifiers of the same publication are redirected.
As a result, the allocation of an OMID for each bibliographic resource also enabled the unambiguous identification of each citation, regardless of the persistent identifier schema originally used by the data source to identify the resources. This approach allowed us to perform data deduplication and finally make all the sources’ contributions converge into a unified index containing all the unique citations managed by OpenCitations, expressed as OMID to OMID citation links.
The revised workflow
The new workflow is based on three main components with the benefit of optimizing the process both in terms of computational cost and in terms of flexibility. As shown in Fig. 1, in a preliminary step, source-specific software converts the input dataset – structured according to the source data model – to extract two OpenCitations Data Model compliant data collections in tabular format for bibliographic metadata and citation data, respectively.
The following steps are common to the process of each dataset.
STEP 1: The bibliographic metadata collection is used as input for the META software. At this stage, it is checked whether or not the bibliographic entities have been previously integrated into our infrastructure (coming from other data sources). If so, the existing OMID is linked also to the new alternative identifiers of the new bibliographic resources. New metadata values, if any, are also integrated. A new OMID identifier is produced for entities never previously encountered, uniquely representing the bibliographic resource in OpenCitations. The outputs of the process are: (I) an updated version of the OpenCitations Meta collection that also includes the metadata of the bibliographic entities provided by the new source, and (II) a collection of provenance data. An internal database is constantly refreshed to preserve correspondence between IDs and the associated internal OMIDs.
STEP 2: Starting from the collection of citations expressed as directional links between identifiers of potentially any type (e.g., DOI-DOI, PMID-PMID, PMC-PMID, etc.), the INDEX software queries the internal database mapping IDs to OMIDs to produce an updated version of the OpenCitations Index: unique citations expressed as OMID-OMID links in different formats, accompanied by their corresponding provenance data.
Fig. 1: An overview of the data ingestion workflow, starting from the data source-specific conversion and production of citations and bibliographic metadata tables, progressing through the META process and the assignation of an OMID identifier to each bibliographic record involved in a citation, and culminating with the exposition of the OpenCitations Index collection of OMID-OMID unique citations.
What we have now: The OpenCitations Index
From now on, OpenCitations will no longer display an index of citation data for each source. Instead, we will publish a single collection of citations into which the contributions from each of the sources will flow, which we will simply call ‘The OpenCitations Index‘. The first version of this unified index of OMID-OMID citations is posted on Figshare. It was produced in RDF, CSV, and SCHOLIX formats, together with a collection of its provenance information, provided in RDF and CSV formats. For each citation, it is possible to trace the source of the information by consulting the Provenance data collection, thanks to the http://www.w3.org/ns/prov#atLocation property, which defines the location of each citation.
This new solution has the benefit of simplifying the consultation of the data maintained by our infrastructure without reducing the information content. In addition, by including efficient handling of the deduplication problem, the new Index not only provides accurate data on the exact number of unique citations exposed by the framework but also verifies the individual contribution of each source, as well as their overlapping data (Fig. 2).
Fig. 2: An overview of the number of citations stored in the OpenCitations Index as of October 31, 2023. The diagonal cells in the table (highlighted in yellow) show the unique contribution of each collection to the OpenCitations Index, while the other cells represent the citations that are shared between the collections. More in detail, the green cells show the overall input of each source, while the pink cells represent the number of overlapping citations between two data sources.
Currently, the Index contains almost 2 billion unique citations. By the end of November, a new version of the collection will be published, including the contribution of the new Japan Link Centre (JaLC) source.
How to access the OpenCitations Index data
To maximize the reuse of the exposed information and to ensure the greatest possible interoperability, the collection will always be published on Figshare in all formats listed above. In addition, the data will be accessible via an API, a SPARQL endpoint, and a web interface.
The redesign of the ingestion workflow marks a fundamental step for OpenCitations towards a more intuitive and simple access to our services while always preserving and improving the quality of our data. If you need further information on how the new workflow works, please visit our website, contact us at contact@opencitations.net or leave feedback and/or suggestions in the dedicated card on our public roadmap to help us improve our services and communications. Thank you!
The four supported infrastructures (OpenCitations, the DOAB, LA Referencia and ROR) “were evaluated by the jury composed by SCOSS, then according to the exemplary criteria of the Committee for the Open Science, which notably guarantee transparency and the participation of the scientific communities in their governance”.
Since 2020, the FNSO has acknowledged OpenCitations as an infrastructure worth its financial support, thanks to its mission of disseminating bibliographic and citation metadata in open access with a level of quality and coverage, thus providing a workable, free and open alternative to the academic community’s current dependency on proprietary tools. OpenCitations’ work therefore frees up citation analysis, promotes the evolution of bibliometric indicators and the broadening knowledge of science.
The FNSO is now contributing to OpenCitations with recurring funding for 2023, 2024 and 2025 for an annual amount of €75,000. This generous support will be crucial in sustaining the maintenance and development of OpenCitations’ technical infrastructure, and in supporting the future activities of the OpenCitations team, that are publicly displayed in the OpenCitations Roadmap.
We are extremely honoured and grateful to the French National Fund for Open Science for renewing the pledge of such a portion of its open science budget to support our work.
We’re happy to announcePOCI, the OpenCitations Index of PubMed open PMID-to-PMID citations, an RDF dataset containing details of all the citations from publications bearing PubMed Identifiers (PMIDs) to other PMID-identified publications, harvested from the National Institutes of Health Open Citations Collection (NIH-OCC). The citations available in POCI are treated as first-class data entities, with accompanying properties including the citations timespan, modelled according to the OpenCitations Data Model.
Each citation (i.e. an individual of the class cito:Citation) is identified by an URL structured as follows:
https://w3id.org/oc/index/poci/ci/[[OCI]].
Open Citation Identifiers
Each Open Citation Identifier [[OCI]] has a simple structure: the lower-case letters “oci” followed by a colon, followed by two numbers separated by a dash (e.g. https://w3id.org/oc/index/poci/ci/01600102060800080706-016002060909030401), in which the first number identifies the citing work and the second number identifies the cited work.
For citations in which the citing and cited works are identified by PMIDs, which includes all the POCI citations, the OCI is created in the following manner, as explained more fully here. Each converted numeral part of OCI is prefixed by a 0160, which indicates that NIH is the supplier of the original metadata of the citation (as indicated at http://opencitations.net/oci).
are available as dumps on Figshare in CSV, N-Triples and Scholix.
What is an Open Citation Index?
A citation index is a bibliographic index recording citations between publications, allowing the user to establish which later documents cite earlier documents. The current indexes available in OpenCitations are:
This blog post is the first of a series dedicated to the description and promotion of OpenCitations Meta.
In addition to OpenCitations’ Citation Indexes, OpenCitations is pleased to announce a new service: OpenCitations Meta, a database which stores and delivers bibliographic metadata for all publications involved in the OpenCitations citation indexes.
For each publication, the metadata exposed by OpenCitations Meta includes the publication’s title, type, venue (e.g. journal name), volume number, issue number, page numbers, publication date, and identifiers such as Digital Object Identifiers (DOIs) and PubMed Identifiers (PMIDs). In addition, OpenCitations Meta includes details of the main actors involved in the publication of the document, i.e., the names of the authors, editor, and publisher, each with its own additional metadata and identifier (e.g. ORCID).
Why OpenCitations Meta?
OpenCitations Meta represents a major infrastructural advance for OpenCitations, since it addresses and overcomes some of the limitations previously experienced, providing three major benefits:
1. It permits OpenCitations to respond more quickly to user requests for information.
The OpenCitations Citation Indexes contain citation-related metadata, such as the identifiers for the citing and cited publications, the citation timespan, and other citation-specific metadata, for example whether or not the citation is a self-citation. However, metadata for the citing and cited publications were hitherto not stored by OpenCitations, but rather obtained by on-the-fly API calls to external services such as Crossref, Datacite and ORCID. This dependence on responses from external services significantly slowed the delivery of the required information to users. Since OpenCitations Meta stores in-house the same bibliographic metadata for the citing and cited publications as was previously obtained by those external API calls, the former temporal limitation is now alleviated, thereby accelerating response times for requests made to the OpenCitations REST API services, and thus better supporting our users.
2. It permits OpenCitations to index citations involving publications that lack DOIs.
The second problem that OpenCitations Meta addresses goes beyond the OpenCitations infrastructure and addresses a more general issue of digital publishing, particularly in the Humanities, namely that many scholarly publications lack persistent identifiers such as DOIs and PMIDs. The citations indexed by OpenCitations are themselves treated as first-class data entities, each bearing a unique persistent Open Citation Identifier. According to the Open Citation Identifier definition [1], the entities linked by an indexed citation need to be identified by a persistent identifier (PID) from a recognised scheme such as the Digital Object Identifier scheme. For example, COCI [2] records the DOIs of the citing and cited entities. However, the association of DOIs with published documents is not uniformly spread across all scholarly fields. Indeed, in Scopus and the Web of Science Core Collection, only 50% of the current publications in the Art and Humanities are associated with a DOI [3]. In addition, in many fields, particularly in the Humanities, references are required to pre-digital historical primary sources that lack PIDs. OpenCitations Meta solves this problem by assigning a unique OpenCitations Meta Identifier (OMID) to each document. In this way, it can record the metadata of publications lacking an external identifier and store the citations involving them in one of the OpenCitations Indexes.
3. Use of the OpenCitations Meta Identifier permits de-duplication of records of bibliographic resources having more than one external identifier, such as a DOI and a PMID.
While many scholarly publications lack external PIDs, many others will have more than one external PID, for example a DOI for the record of that publication in Crossref, and a PMID for the record of that same publication in PubMed. This is perfectly legitimate. Since OpenCitations Meta assigns a unique OpenCitations Meta Identifier (OMID) to every entry, and in addition records all external identifiers already assigned to that publication, for example its DOI and its PMID, this permits the automatic de-duplication of such publications within OpenCitations Meta.
The data model
OpenCitations uses Semantic Web technologies to encode all its data, including the bibliographic metadata now stored in OpenCitations Meta. For this purpose, the OpenCitations Data Model (OCDM) [4] uses classes and properties defined in the SPAR Ontologies to represent:
bibliographic entities (fabio:Expression), e.g. a journal article
identifiers (datacite:Identifier), e.g. a DOI
agent roles (pro:RoleInTime), e.g. an author
responsible agents (foaf:Agent), e.g. a person
publication format details (fabio:Manifestation), e.g. first and last pages
Figure 1 depicts relationships between some of the various entities.
Figure 1. A small subset of the OCDM used in OC Meta. Yellow rectangles represent classes, green polygons represent data types, while blue and green arrows represent object properties and data properties, respectively
In addition to storing data, great importance is given to recording provenance and change-tracking of OpenCitations Meta entries, including the agent who processed a specific entity, i.e. creating, deleting, modifying or merging it, the date and time on which this action was performed, and the primary source of the data.
The data
At the release date, 20th December 2022, OpenCitations Meta is using Crossref as its primary source, with the purpose of hosting the metadata describing all citing and cited publications involved in the 1,392,036,835 citations within COCI [2]. From a quantitative point of view, OpenCitations Meta presently contains metadata describing 87,321,593 bibliographic entities, 277,750,235 authors, 2,359,301 editors, 17,268 publishers, and 710,226 publication venues (e.g. journal names). Editors and authors have been counted by their roles, without at this stage disambiguating individuals with the same name. Conversely, bibliographic entities, publishers, and publication venues were counted by their OMIDs. In total, the OpenCitations Meta triplestore presently contains 3,298,335,581 triples.
In the following days, OpenCitations Meta will be expanded to include bibliographic metadata for all citing and cited publications involved in the 169,822,752 citations from DataCite within DOCI, released on 13th December 2022.
Table 1 lists the various types of bibliographic resource represented in OpenCitations Meta. The current dataset contains mostly journal articles (60,683,841), which exceed the number of book chapters (6,288,351) by about ten times and the number of conference proceedings articles (4,917,568) by about twelve times.
OpenCitations Meta allows the users to explore the contained metadata either via SPARQL (https://opencitations.net/meta/sparql) or via the OpenCitations Meta REST API (https://opencitations.net/meta/api/v1). In particular, the API will retrieve a list of bibliographic resources and related metadata starting from one or more identifiers including an OpenCitations Meta Identifier (OMID), an author’s ORCID, or an editor’s ORCID.
Finally, all the metadata and provenance information present in OpenCitations Meta are available as dumps in RDF (JSON-LD) or CSV format under a CC0 licence. Every time a citation index is updated, we will update OpenCitations Meta.
Conclusion
OpenCitations Meta makes search operations on the metadata of scholarly publications involved in the citations indexed in the OpenCitations Citation Indexes faster, since the metadata are now held in-house. The use of OpenCitations Meta Identifiers (OMIDs) permits OpenCitations Meta to act as a mapping hub to disambiguate and unify information on single publications identified by more than one external identifier, and makes it possible to characterise citations involving resources lacking an external identifier.
In the future, we will introduce a new API operation to perform text searches. Moreover, OpenCitations Meta will incorporate metadata from other sources in addition to Crossref. As mentioned above, work is already under way to ingest bibliographic metadata from Datacite for the publications involved in the citations newly indexed in DOCI. This will soon be followed with similar OpenCitations Meta entries relating to a new citation index, POCI, containing citations from PubMed, to be released later this year. PubMed metadata will be made available by February 2023.
Heibi, I., Peroni, S. & Shotton, D. Software review: COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations. Scientometrics 121, 1213–1228 (2019). https://doi.org/10.1007/s11192-019-03217-6
Gorraiz, J., Melero-Fuentes, D., Gumpenberger, C., & Valderrama-Zurián, J.-C. (2016). Availability of digital object identifiers (DOIs) in Web of Science and Scopus. Journal of Informetrics, 10 (1), 98–10. https://doi.org/10.1016/j.joi.2015.11.008
We’re excited to introduce DOCI, the OpenCitations Index of Datacite open DOI-to-DOI citations, a new tool containing citations derived from publications bearing DataCite DOIs to other DOI-identified publications, harvested from DataCite. The citations available in DOCI are treated as first-class data entities, with accompanying properties including the citations timespan, modelled according to the OpenCitations Data Model.
For citations in which the citing and cited works are identified by DOIs, which includes all the DOCI citations, the OCI is created in the following manner, as explained more fully here. 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. Finally, each converted numeral is prefixes by a 080, which indicates that DataCite is the supplier of the original metadata of the citation (as indicated at http://opencitations.net/oci).
A citation index is a bibliographic index recording citations between publications, allowing the user to establish which later documents cite earlier documents. The current indexes available in OpenCitations are:
OpenCitations has happily joined the open-source social media platform joinmastodon.org.
Mastodon is “a free and open-source software developed by a non-profit organization”, with the aim of favouring interoperability and bringing social media interaction “back in the hands of the people”.
We look forward to recreating there our wide network of connections, and getting in touch with new people, projects and institutions in a different virtual environment.
Blog post by Ivan Heibi (Universiy of Bologna) and Arcangelo Massari (University of Bologna).
OpenCitations publishes the COCI dataset after each new release in three main formats: CSV, N-Triples, and Scholix (see https://opencitations.net/download#coci). The CSV format is the most popular and downloaded one due to its comprehensive data organization (i.e. tabular format) and smaller size (compared to the other formats provided). Therefore, this is also the format we suggest using for a local process of the entire COCI dataset.
The CSV dumps of COCI are uploaded on Figshare. You can check and download the last dump released from https://doi.org/10.6084/m9.figshare.6741422. The dump consists of one main ZIP file, including other smaller ZIP archives (one for each release) containing the actual CSV files (Figure 1).
Figure 1. The contents of the COCI CSV dataset (after the August 2022 release)
It is possible to process this data without unzipping the internal archives, thus saving a lot of disk space. In this tutorial, we will see how to achieve this in Python. Same process could be done in other programming languages.
Processing the COCI dump using Python
Step 1) Downloading the COCI dump
First, you need to download the last CSV dump release of COCI from https://doi.org/10.6084/m9.figshare.6741422 and decompress only the external archive. After this operation, you should have a folder containing the internal ZIP files such as in Figure 1.
Note: It is beneficial to decompress the external archive because doing so does not increase the space occupied on the disk (compressing archives results in a compression rate of 0%) and because working on nested archives would significantly increase RAM requirements.
Step 2) Working with the ZIP files
Python provides the built-in zipfile module, whose ZipFile class allows you to create, read, write, edit and list the contents of a ZIP file. Given as input the path of the root directory containing all the ZIP files (FOLDER_PATH), the process elaborates each of these files on a different iteration. Each cycle initializes a ZipFile object by specifying the path to the ZIP file (archive_path).
from zipfile import ZipFile
import os
for archive_name in os.listdir(FOLDER_PATH): archive_path = os.path.join(FOLDER_PATH, archive_name) with ZipFile(archive_path) as archive:
# ...
Step 3) Accessing the ZIP files
Use the namelist() method to return the list of CSV files contained in each archive. Then to open the inner CSV files, simply cycle through the list of names and feed them to the open() method of the ZipFile instance, i.e. archive in the example below.
from zipfile import ZipFile
import os
for archive_name in os.listdir(FOLDER_PATH):
archive_path = os.path.join(FOLDER_PATH, archive_name)
with ZipFile(archive_path) as archive:
for csv_name in archive.namelist(): with archive.open(csv_name) as csv_file:
# ...
Step 4) Reading the CSVs
The .open() method returns a buffer. To read the CSV file as a list of dictionaries (i.e. represent each row of the CSV in dictionary format, e.g., {“column1″:”val1”, “column2″:”val2”}) we need to transform the buffer using the TextIOWrapper class and read it using the DictReader class of csv. Then we convert the result of DictReader into a list.
from io import TextIOWrapper
from zipfile import ZipFile
import os
for archive_name in os.listdir(FOLDER_PATH):
archive_path = os.path.join(FOLDER_PATH, archive_name)
with ZipFile(archive_path) as archive:
for csv_name in archive.namelist(): with archive.open(csv_name) as csv_file: reader = csv.DictReader(io.TextIOWrapper(csv_file)) rows = list(reader) # ...
Step 5) Processing the CSVs content
Now you can go through each row of the list and process the citation data as you want. The following example prints the citing and cited entity of each citation in the dump.
from io import TextIOWrapper
from zipfile import ZipFile
import os
for archive_name in os.listdir(FOLDER_PATH):
archive_path = os.path.join(FOLDER_PATH, archive_name)
with ZipFile(archive_path) as archive:
for csv_name in archive.namelist(): with archive.open(csv_name) as csv_file: reader = csv.DictReader(io.TextIOWrapper(csv_file)) rows = list(reader) # Process the CSV here for r in rows: print("Citing entity:",r["citing"]) print("Cited entity:",r["cited"])
We announce the August 2022 release of COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations, which is based on open references to works with DOIs within the Crossref dump dated August 2022. This new release extends COCI with more than 48 million additional citations, giving a total number of more than 1.36 billion DOI-to-DOI citation links.
This release includes citations from the articles published over the last four years by IEEE, whose bibliographic references were opened in June 2022.
A fundamental role in pushing the commercial publishers to open their citation data was played by Crossref’s recent announcement to change its reference distribution policy, by making all its metadata open.
Besides IEEE, COCI already includes the citation data derived from Elsevier (open via Crossref since December 2020) and from the last articles published by the American Chemical Society (whose references were opened in February 2021)
You can find more information about COCI in our open-access article
Ivan Heibi, Silvio Peroni & David Shotton (2019). Software review: COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations. Scientometrics, 121 (2): 1213-1228. DOI: https://doi.org/10.1007/s11192-019-03217-6
Finally, just a reminder that the bibliographic and citation data in COCI:
can be queried using the OpenCitations Indexes SPARQL endpoint;
Posted on August 10th 2022 by Chiara Di Giambattista
More than a year ago, Ginny Hendricks, Director of Member & Community Outreach for Crossref, and a valued member of the OpenCitations International Advisory Board, published on the Crossref blog the post “The road ahead: our strategy through 2025”. In order to describe all Crossref’s principles and activities, Ginny presented the Crossref strategic planning framework as a diagram summarizing Crossref’s statements, key messages and truths. The clarity and immediacy of the diagram were such that we adapted it to present OpenCitations’ own statements and goals. The resulting poster “OpenCitations – what does the future hold?” was presented by our Director David Shotton at the OASPA2021 conference, and can be found in this blog post.
Although the poster offered a wide overview of OpenCitations values, unique traits, benefits and plans, it differed slightly from Ginny’s original diagram, in particular because it lacked a “Mission Statement”, scattering the relevant information within the “Values” and “Principles” boxes. Indeed, at that time (September 2021), we didn’t have a clearly defined Mission Statement.
Nevertheless, the creation of that poster was crucial in helping us start to articulate more clearly the purpose and meaning of OpenCitations. As David underlined in his post “From little acorns…a retrospective on OpenCitations”, since 2018 OpenCitations activities have progressively increased and, with them, the number of related journal articles, conference papers and technical definitions. OpenCitations’ involvement in international networks and collaborations (such as SCOSS and the OpenAIRE-Nexus project), together with our need of identifying and reaching out to new stakeholders to assure OpenCitations’ development and sustainability, has made it necessary to publicly define OpenCitations’ mission, unique strengths and next developmental steps.
After numerous revisions, aided by wise advice from members of the OpenCitations Advisory Board members, we’re now happy to publish the following three OpenCitations documents:
which together provide a summary of why we exist and where we are heading.
We are particularly proud of the definition of OpenCitations’ primary mission, namely
“to harvest and openly publish accurate and comprehensive metadata describing the world’s academic publications and the scholarly citations that link them, and to preserve ongoing access to this information by secure archiving.”
The Mission Statement also presents brief descriptions of the OpenCitations context, our vision, our value proposition and our relationship with the community and stakeholders.
The Uniqueness of OpenCitations provides the answer to the question ‘Why choose to use OpenCitations?’, and is a detailed presentation of OpenCitations’ benefits.
OpenCitations – Present Status and Future Plans summarizes OpenCitations’ ongoing activities, that can be quickly visualized on our public roadmap. It also introduces the OpenCitations Working Groups, served by the members of the OpenCitations International Advisory Board, which are currently working on the themes of governance evolution and community building, with the common purpose of driving OpenCitations along the path from being a ‘sustainable infrastructure’ (in POSI terms) to being an enduring community led andfinancially sustained infrastructure.
In fulfilling our mission and reaching our goals, the support and vital interest of our community members is fundamental. We request that you, as a member of our community, provide us with feedback on these documents and the ideas they contain, or indeed to ask for clarifications, to help us improving our mission and our communications to explain it. You can reach us here: contact@opencitations.net.
Fig. 1: An overview of the data ingestion workflow, starting from the data source-specific conversion and production of citations and bibliographic metadata tables, progressing through the META process and the assignation of an OMID identifier to each bibliographic record involved in a citation, and culminating with the exposition of the OpenCitations Index collection of OMID-OMID unique citations.
