Generate FAIR Literature Surveys with Scholarly Knowledge Graphs

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Allard Oelen
  • Mohamad Yaser Jaradeh
  • Markus Stocker
  • Soren Auer

Research Organisations

External Research Organisations

  • German National Library of Science and Technology (TIB)
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Details

Original languageEnglish
Title of host publicationJCDL 2020
Subtitle of host publicationProceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages97-106
Number of pages10
ISBN (electronic)9781450375856
Publication statusPublished - 1 Aug 2020
Event2020 ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2020 - Virtual, Online, China
Duration: 1 Aug 20205 Aug 2020

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.

Keywords

    Comparison user interface, Digital libraries, Fair data principles, Scholarly communication, Scholarly information systems, Scholarly knowledge comparison

ASJC Scopus subject areas

Cite this

Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. / Oelen, Allard; Jaradeh, Mohamad Yaser; Stocker, Markus et al.
JCDL 2020 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 97-106 3398520.

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Oelen, A, Jaradeh, MY, Stocker, M & Auer, S 2020, Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. in JCDL 2020 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020., 3398520, Institute of Electrical and Electronics Engineers Inc., pp. 97-106, 2020 ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2020, Virtual, Online, China, 1 Aug 2020. https://doi.org/10.1145/3383583.3398520
Oelen, A., Jaradeh, M. Y., Stocker, M., & Auer, S. (2020). Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. In JCDL 2020 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020 (pp. 97-106). Article 3398520 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3383583.3398520
Oelen A, Jaradeh MY, Stocker M, Auer S. Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. In JCDL 2020 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 97-106. 3398520 doi: 10.1145/3383583.3398520
Oelen, Allard ; Jaradeh, Mohamad Yaser ; Stocker, Markus et al. / Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. JCDL 2020 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 97-106
Download
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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.",
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