RDFtex in-depth: knowledge exchange between LATEX-based research publications and Scientific Knowledge Graphs

Author:

Martin LeonORCID,Henrich AndreasORCID

Abstract

AbstractFor populating Scientific Knowledge Graphs (SciKGs), research publications pose a central information source. However, typical forms of research publications like traditional papers do not provide means of integrating contributions into SciKGs. Furthermore, they do not support making direct use of the rich information SciKGs provide. To tackle this, the present paper proposes RDFtex, a framework enabling (1) the import of contributions represented in SciKGs to facilitate the preparation of "Equation missing"-based research publications and (2) the export of original contributions from papers to facilitate their integration into SciKGs. The framework’s functionality is demonstrated using the present paper itself since it was prepared with our proof-of-concept implementation of RDFtex. The runtime of the implementation’s preprocessor was evaluated based on three "Equation missing" projects with different numbers of imports and exports. A small user study ($$N=10$$ N = 10 ) was conducted to obtain initial user feedback. The concept and the process of preparing a "Equation missing"-based research publication using RDFtex are discussed thoroughly. RDFtex’s import functionality takes considerably more time than its export functionality. Nevertheless, the entire preprocessing takes only a fraction of the time required to compile the PDF. The users were able to solve all predefined tasks but preferred the import functionality over the export functionality because of its general simplicity. RDFtex is a promising approach to facilitate the move toward knowledge graph augmented research since it only introduces minor differences compared to the preparation of traditional "Equation missing"-based publications while narrowing the gap between papers and SciKGs.

Funder

Otto-Friedrich-Universität Bamberg

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences

Reference23 articles.

1. White, K.: Publications output: US trends and international comparisons. Science & Engineering Indicators 2020. nsb-2020-6. National Science Foundation (2019). https://ncses.nsf.gov/pubs/nsb20206. Accessed 08 Mar 2023

2. Auer, S., Kovtun, V., Prinz, M., Kasprzik, A., Stocker, M., Vidal, M.: Towards a knowledge graph for science. In: Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics, WIMS 2018, pp. 1–116. ACM, Novi Sad, Serbia (2018). https://doi.org/10.1145/3227609.3227689

3. Jaradeh, M.Y., Oelen, A., Farfar, K.E., Prinz, M., D’Souza, J., Kismihók, G., Stocker, M., Auer, S.: Open research knowledge graph: next generation infrastructure for semantic scholarly knowledge. In: Proceedings of the 10th International Conference on Knowledge Capture, K-CAP 2019, November 19-21, 2019, pp. 243–246. ACM, Marina Del Rey, CA, USA (2019). https://doi.org/10.1145/3360901.3364435

4. Luan, Y., He, L., Ostendorf, M., Hajishirzi, H.: Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3219–3232. Association for Computational Linguistics, Brussels, Belgium (2018). https://doi.org/10.18653/v1/d18-1360

5. Martin, L., Jegan, R., Henrich, A.: On the form of research publications for use in scientific knowledge graphs. In: Wissensorganisation 2021: 16. Tagung der Deutschen Sektion der Internationalen Gesellschaft Für Wissensorganisation (ISKO) (WissOrg’21), Online (accepted for publication 2021)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3