{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T21:44:02Z","timestamp":1776980642212,"version":"3.51.4"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T00:00:00Z","timestamp":1707091200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T00:00:00Z","timestamp":1707091200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100012957","name":"Friedrich-Schiller-Universit\u00e4t Jena","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100012957","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Datenbank Spektrum"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Knowledge Graphs (KGs) present factual information about domains of interest. They are used in a\u00a0wide variety of applications and in different domains, serving as powerful backbones for organizing and extracting knowledge from complex data. In both industry and academia, a\u00a0variety of platforms have been proposed for managing Knowledge Graphs. To use the full potential of KGs within these platforms, it is essential to have proper provenance management to understand where certain information in a\u00a0KG stems from. This plays an important role in increasing trust and supporting open science principles. It enables reproducibility and updatability of KGs. In this paper, we propose a\u00a0framework for provenance management of KG generation within a\u00a0web portal. We present how our framework captures, stores, and retrieves provenance information. Our provenance representation is aligned with the standardized W3C Provenance Ontology. Through our framework, we can rerun the KG generation process over the same or different source data. With this, we support four applications: reproducibility, altered rerun, undo operation, and provenance retrieval. In summary, our framework aligns with the core principles of open science. By promoting transparency and reproducibility, it enhances the reliability and trustworthiness of research outcomes.<\/jats:p>","DOI":"10.1007\/s13222-023-00463-0","type":"journal-article","created":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T15:04:52Z","timestamp":1707145492000},"page":"43-52","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Managing Provenance Data in Knowledge Graph Management Platforms"],"prefix":"10.1007","volume":"24","author":[{"given":"Erik","family":"Kleinsteuber","sequence":"first","affiliation":[]},{"given":"Tarek","family":"Al Mustafa","sequence":"additional","affiliation":[]},{"given":"Franziska","family":"Zander","sequence":"additional","affiliation":[]},{"given":"Birgitta","family":"K\u00f6nig-Ries","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4203-1329","authenticated-orcid":false,"given":"Samira","family":"Babalou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,5]]},"reference":[{"issue":"1","key":"463_CR1","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/JPROC.2015.2483592","volume":"104","author":"M Nickel","year":"2015","unstructured":"Nickel M, Murphy K, Tresp V, Gabrilovich E (2015) A\u00a0review of relational machine learning for knowledge graphs. IEEE 104(1):11\u201333","journal-title":"IEEE"},{"key":"463_CR2","doi-asserted-by":"crossref","unstructured":"Page RD (2019) Ozymandias: a biodiversity knowledge graph. PeerJ 7 (2019): e6739.","DOI":"10.7717\/peerj.6739"},{"issue":"1","key":"463_CR3","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1186\/s12859-022-04932-3","volume":"23","author":"E Wood","year":"2022","unstructured":"Wood E, Glen AK, Kvarfordt LG, Womack F, Acevedo L, Yoon TS, Ma C, Flores V, Sinha M, Chodpathumwan Y et al (2022) Rtx-kg2: a\u00a0system for building a\u00a0semantically standardized knowledge graph for translational biomedicine. BMC Bioinform 23(1):400","journal-title":"BMC Bioinform"},{"key":"463_CR4","first-page":"3","volume-title":"KSEM","author":"J Wu","year":"2020","unstructured":"Wu J, Zhu X, Zhang C, Hu Z (2020) Event-centric tourism knowledge graph\u2014 a\u00a0case study of hainan. In: KSEM. 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