{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T14:52:18Z","timestamp":1787237538334,"version":"build-2736575974"},"reference-count":49,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EL"],"published-print":{"date-parts":[[2024,6,27]]},"abstract":"<jats:sec>\n                    <jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n                    <jats:p>This paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n                    <jats:p>Action research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n                    <jats:p>To extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n                    <jats:p>This approach is currently used to document \u201cfood information engineering,\u201d \u201ctabular data to knowledge graph matching\u201d and \u201cquestion answering\u201d research problems and the \u201cneurosymbolic AI\u201d domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/el-06-2023-0154","type":"journal-article","created":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T07:34:13Z","timestamp":1717400053000},"page":"413-442","source":"Crossref","is-referenced-by-count":8,"title":["An approach based on open research knowledge graph for knowledge acquisition from scientific papers"],"prefix":"10.1108","volume":"42","author":[{"given":"Azanzi","family":"Jiomekong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanju","family":"Tiwari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2024,6,5]]},"reference":[{"issue":"1","key":"key2024062511251244200_ref001","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0244918","article-title":"Extracting and modeling geographic information from scientific articles","volume":"16","year":"2021","journal-title":"Plos One"},{"key":"key2024062511251244200_ref002","doi-asserted-by":"publisher","first-page":"1847979019890771","DOI":"10.1177\/1847979019890771","article-title":"Limitations of information extraction methods and techniques for heterogeneous unstructured big data","volume":"11","year":"2019","journal-title":"International Journal of Engineering Business Management"},{"key":"key2024062511251244200_ref003","article-title":"A survey of rdf stores and sparql engines for querying knowledge graphs","year":"2021"},{"issue":"4","key":"key2024062511251244200_ref004","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1080\/14778238.2022.2041375","article-title":"Digitalising the systematic literature review process: the myslr platform","volume":"21","year":"2023","journal-title":"Knowledge Management Research and Practice"},{"key":"key2024062511251244200_ref005","doi-asserted-by":"publisher","first-page":"502","DOI":"10.18653\/v1\/2021.semeval-1.61","article-title":"Innovators at semeval-2021 task-11: a dependency parsing and bert-based model for extracting contribution knowledge from scientific papers","volume-title":"Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)","year":"2021"},{"key":"key2024062511251244200_ref006","doi-asserted-by":"publisher","DOI":"10.18452\/22049","article-title":"Improving access to scientific literature with knowledge graphs","year":"2020","journal-title":"Bibliothek - Forschung Und Praxis"},{"issue":"1","key":"key2024062511251244200_ref007","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1515\/comp-2019-0013","article-title":"Extracting ontological knowledge from java source code using hidden markov models","volume":"9","year":"2019","journal-title":"Open Computer Science"},{"key":"key2024062511251244200_ref008","doi-asserted-by":"publisher","DOI":"10.46298\/arima.9873","article-title":"Combining scrum and model driven architecture for the development of an epidemiological surveillance software","volume":"39","year":"2023","journal-title":"Revue Africaine de Recherche en Informatique et Math\u00e9matiques Appliqu\u00e9es"},{"key":"key2024062511251244200_ref009","doi-asserted-by":"publisher","first-page":"125867","DOI":"10.1109\/ACCESS.2022.3220241","article-title":"Completing scientific facts in knowledge graphs of research concepts","volume":"10","year":"2022","journal-title":"IEEE Access"},{"issue":"1","key":"key2024062511251244200_ref010","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s00799-021-00306-x","article-title":"Analysing the requirements for an open research knowledge graph: use cases, quality requirements, and construction strategies","volume":"23","year":"2022","journal-title":"International Journal on Digital Libraries"},{"key":"key2024062511251244200_ref011","unstructured":"Caroline Hayes, D.G. and Fu, M. 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