EXCITE – A Toolchain to Extract, Match and Publish Open Literature References

Hosseini, Azamossadat; Ghavimi, Behnam; Boukhers, Zeyd; Mayr, Philipp

doi:10.1109/jcdl.2019.00105

Cited by 17 publications

(15 citation statements)

References 3 publications

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“…In addition to the aforementioned activities, OpenCitations is currently collaborating with a number of academic projects related to the management of bibliographic and citation data, to both promote the use of the OCDM and provide a publication venue for the citation data that these projects are liberating from the scholarly literature. Among these, it is particularly worth mentioning the Venice Scholar Index (https://venicescholar.dhlab.epfl.ch), the Linked Open Citations Database (LOC-DB; https://locdb.bib.uni-mannheim.de; Lauscher et al, 2018), and the EXCITE Project (http://excite.west.uni-koblenz.de; Hosseini et al, 2019).…”

Section: Adoption Of Opencitations By the Communitymentioning

confidence: 99%

OpenCitations, an infrastructure organization for open scholarship

Peroni

Shotton

2020

Quantitative Science Studies

107

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OpenCitations is an infrastructure organization for open scholarship dedicated to the publication of open citation data as Linked Open Data using Semantic Web technologies, thereby providing a disruptive alternative to traditional proprietary citation indexes. Open citation data are valuable for bibliometric analysis, increasing the reproducibility of large-scale analyses by enabling publication of the source data. Following brief introductions to the development and benefits of open scholarship and to Semantic Web technologies, this paper describes OpenCitations and its data sets, tools, services, and activities. These include the OpenCitations Data Model; the SPAR (Semantic Publishing and Referencing) Ontologies; OpenCitations’ open software of generic applicability for searching, browsing, and providing REST APIs over resource description framework (RDF) triplestores; Open Citation Identifiers (OCIs) and the OpenCitations OCI Resolution Service; the OpenCitations Corpus (OCC), a database of open downloadable bibliographic and citation data made available in RDF under a Creative Commons public domain dedication; and the OpenCitations Indexes of open citation data, of which the first and largest is COCI, the OpenCitations Index of Crossref Open DOI-to-DOI Citations, which currently contains over 624 million bibliographic citations and is receiving considerable usage by the scholarly community.

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Section: Adoption Of Opencitations By the Communitymentioning

confidence: 99%

OpenCitations, an infrastructure organization for open scholarship

Peroni

Shotton

2020

Quantitative Science Studies

107

View full text Add to dashboard Cite

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“…Another way of acquiring bibliographic metadata is to analyze a source document, such as a PDF (or its text), directly. Tools in this category are often based on conditional random fields [Lafferty et al, 2001] and have been implemented in projects such as ParsCit [Councill et al, 2008], Cermine [Tkaczyk et al, 2014], EXCITE [Hosseini et al, 2019] or GROBID [Lopez, 2009]. The problem of citation matching is relatively simple when common, persistent identifiers are present in the data.…”

Section: Related Workmentioning

confidence: 99%

Refcat: The Internet Archive Scholar Citation Graph

Czygan,

Holzmann,

Newbold

2021

Preprint

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As part of its scholarly data efforts, the Internet Archive (IA) releases a first version of a citation graph dataset, named refcat, derived from scholarly publications and additional data sources. It is composed of data gathered by the fatcat cataloging project 1 (the catalog that underpins IA Scholar), related web-scale crawls targeting primary and secondary scholarly outputs, as well as metadata from the Open Library 2 project and Wikipedia 3 . This first version of the graph consists of over 1.3B citations. We release this dataset under a CC0 Public Domain Dedication, accessible through Internet Archive 4 . The source code used for the derivation process, including exact and fuzzy citation matching, is released under an MIT license 5 . The goal of this report is to describe briefly the current contents and the derivation of the dataset.

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“…Our keynote was given by Alberto Laender (Universidade Federal de Minas Gerais, Brazil) 5 in collaboration with Anderson A. Ferreira (Universidade Federal de Ouro Preto, Brazil) and Marcos André Gonçalves (Universidade Federal de Minas Gerais, Brazil). Alberto and his team talked about "Automatic Disambiguation of Author Names: Foundations, Methods and Open Issues" (see their recent book on AND [4]).…”

Section: Keynotementioning

confidence: 99%

BiblioDAP: The 1st Workshop on Bibliographic Data Analysis and Processing

Boukhers,

Mayr,

Peroni

2021

Preprint

Self Cite

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Automatic processing of bibliographic data becomes very important in digital libraries, data science and machine learning due to its importance in keeping pace with the significant increase of published papers every year from one side and to the inherent challenges from the other side. This processing has several aspects including but not limited to I) Automatic extraction of references from PDF documents, II) Building an accurate citation graph, III) Author name disambiguation, etc. Bibliographic data is heterogeneous by nature and occurs in both structured (e.g. citation graph) and unstructured (e.g. publications) formats. Therefore, it requires data science and machine learning techniques to be processed and analysed. Here we introduce BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing.

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EXCITE – A Toolchain to Extract, Match and Publish Open Literature References

Cited by 17 publications

References 3 publications

OpenCitations, an infrastructure organization for open scholarship

OpenCitations, an infrastructure organization for open scholarship

Refcat: The Internet Archive Scholar Citation Graph

BiblioDAP: The 1st Workshop on Bibliographic Data Analysis and Processing

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