Bridging the Scientific Knowledge Gap and Reproducibility: A Survey of Provenance, Assertion and Evidence Ontologies

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Chhetri, Tek Raj; Halchenko, Yaroslav; Jarecka, Dorota; Trivedi, Puja; Ghosh, Satrajit; ... Show more
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Abstract
The rapid growth of scientific publications and evolving experimental paradigms create significant challenges in staying up-to-date with current advances. Assertions are often unstructured and have limited provenance, which hinders reproducibility. Ontologies and knowledge graphs (KGs) offer structured solutions by capturing assertions, evidence, and provenance to support reproducibility. This paper reviews 23 ontologies -- 13 focused on assertions and evidence and 10 on provenance -- providing an overview of the current landscape while highlighting key challenges and opportunities for improvement.
Description
WWW Companion ’25, Sydney, NSW, Australia
Date issued
2025-05-23
URI
https://hdl.handle.net/1721.1/162576
Department
McGovern Institute for Brain Research at MIT
Publisher
ACM|Companion Proceedings of the ACM Web Conference 2025
Citation
Tek Raj Chhetri, Yaroslav O. Halchenko, Dorota Jarecka, Puja Trivedi, Satrajit S. Ghosh, Patrick Ray, and Lydia Ng. 2025. Bridging the Scientific Knowledge Gap and Reproducibility: A Survey of Provenance, Assertion and Evidence Ontologies. In Companion Proceedings of the ACM on Web Conference 2025 (WWW '25). Association for Computing Machinery, New York, NY, USA, 924–928.
Version: Final published version
ISBN
979-8-4007-1331-6
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