In this paper we present the 2nd edition of the Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2022) workshop. Sci-K aims to explore innovative solutions and ideas for the generation of approaches, data models, and infrastructures (e.g., knowledge graphs) for supporting, directing, monitoring and assessing the scientific knowledge and progress. This edition is also a reflection point as the community is seeking alternative solutions to the now-defunct Microsoft Academic Graph (MAG).

Manghi, P., Mannocci, A., Osborne, F., Sacharidis, D., Salatino, A., Vergoulis, T. (2022). Sci-K 2022 - International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment. In WWW ’22: Companion Proceedings of the ACM Web Conference 2022 (pp. 735-738). New York : Association for Computing Machinery, Inc [10.1145/3487553.3524883].

Sci-K 2022 - International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment

Osborne, F;
2022

Abstract

In this paper we present the 2nd edition of the Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2022) workshop. Sci-K aims to explore innovative solutions and ideas for the generation of approaches, data models, and infrastructures (e.g., knowledge graphs) for supporting, directing, monitoring and assessing the scientific knowledge and progress. This edition is also a reflection point as the community is seeking alternative solutions to the now-defunct Microsoft Academic Graph (MAG).
Capitolo o saggio
Knowledge Discovery; Knowledge Graphs; Research Assessment; Research Impact; Scholarly Data; Science Of Science
English
WWW ’22: Companion Proceedings of the ACM Web Conference 2022
2022
9781450391306
Association for Computing Machinery, Inc
735
738
Manghi, P., Mannocci, A., Osborne, F., Sacharidis, D., Salatino, A., Vergoulis, T. (2022). Sci-K 2022 - International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment. In WWW ’22: Companion Proceedings of the ACM Web Conference 2022 (pp. 735-738). New York : Association for Computing Machinery, Inc [10.1145/3487553.3524883].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/412257
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