SmartReviews: Towards Human- and Machine-Actionable Representation of Review Articles

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Oelen, A.; Stocker, M.; Auer, S.: SmartReviews: Towards Human- and Machine-Actionable Representation of Review Articles. In: Ke, H.R.; Lee, C.S.; Sugiyama, K. (Eds.): Towards Open and Trustworthy Digital Societies. ICADL 2021. New York, NY : Springer, 2021 (Lecture notes in computer science ; 13133), S. 105-114. DOI: https://doi.org/10.1007/978-3-030-91669-5_9

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/16801

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Sum total of downloads: 13




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Abstract: 
Review articles are a means to structure state-of-the-art literature and to organize the growing number of scholarly publications. However, review articles are suffering from numerous limitations, weakening the impact the articles could potentially have. A key limitation is the inability of machines to access and process knowledge presented within review articles. In this work, we present SmartReviews, a review authoring and publishing tool, specifically addressing the limitations of review articles. The tool enables community-based authoring of living articles, leveraging a scholarly knowledge graph to provide machine-actionable knowledge. We evaluate the approach and tool by means of a SmartReview use case. The results indicate that the evaluated article is successfully addressing the weaknesses of the current review practices.
License of this version: This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed on other websites via the internet or passed on to external parties.
Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht auf anderen Webseiten im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: BookPart
Publishing status: acceptedVersion
Issue Date: 2021
Appears in Collections:Forschungszentren

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pos. country downloads
total perc.
1 image of flag of Germany Germany 6 46.15%
2 image of flag of United States United States 4 30.77%
3 image of flag of China China 2 15.38%
4 image of flag of Romania Romania 1 7.69%

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