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Oelen2020, Postprint, Generate FAIR Literature Surveys.pdf1,37 MBAdobe PDFAnzeigen/Öffnen
Titel: Generate FAIR Literature Surveys with Scholarly Knowledge Graphs
Autor(en): Oelen, AllardJaradeh, Mohamad YaserStocker, MarkusAuer, Sören
Verlagsversion: https://doi.org/10.1145/3383583.3398520
Erscheinungsjahr: 2020
Verlag: New York City, NY : Association for Computing Machinery
Abstract: Reviewing scientific literature is a cumbersome, time consuming but crucial activity in research. Leveraging a scholarly knowledge graph, we present a methodology and a system for comparing scholarly literature, in particular research contributions describing the addressed problem, utilized materials, employed methods and yielded results. The system can be used by researchers to quickly get familiar with existing work in a specific research domain (e.g., a concrete research question or hypothesis). Additionally, it can be used to publish literature surveys following the FAIR Data Principles. The methodology to create a research contribution comparison consists of multiple tasks, specifically: (a) finding similar contributions, (b) aligning contribution descriptions, (c) visualizing and finally (d) publishing the comparison. The methodology is implemented within the Open Research Knowledge Graph (ORKG), a scholarly infrastructure that enables researchers to collaboratively describe, find and compare research contributions. We evaluate the implementation using data extracted from published review articles. The evaluation also addresses the FAIRness of comparisons published with the ORKG.
Schlagwörter: Scholarly Knowledge Comparison; Scholarly Information Systems; Comparison User Interface; Digital Libraries; Scholarly Communication; FAIR Data Principles
DDC: 020
Lizenz: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
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