Managing Comprehensive Research Instrument Descriptions Within a Scholarly Knowledge Graph

authored by: Muhammad Haris, Sören Auer, Markus Stocker
Abstract: In research, measuring instruments play a crucial role in producing the data that underpin scientific discoveries. Information about instruments is essential in data interpretation and, thus, knowledge production. However, if at all available and accessible, such information is scattered across numerous data sources. Relating the relevant details, e.g. instrument specifications or calibrations, with associated research assets (data, but also operating infrastructures) is challenging. Moreover, understanding the (possible) use of instruments is essential for researchers in experiment design and execution. To address these challenges, we propose a Knowledge Graph (KG) based approach for representing, publishing, and using information, extracted from various data sources, about instruments and associated scholarly artefacts. The resulting KG serves as a foundation for exploring and gaining a deeper understanding of the use and role of instruments in research, discovering relations between instruments and associated artefacts (articles and datasets), and opens the possibility to quantify the impact of instruments in research.
Organisation(s): L3S Research Centre
External Organisation(s): German National Library of Science and Technology (TIB)
Type: Conference contribution
Pages: 39-53
No. of pages: 15
Publication date: 2025
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Theoretical Computer Science, General Computer Science
Electronic version(s): https://doi.org/10.1007/978-981-96-0868-3_3 (Access: Closed)

BibTeX

@inproceedings{d9e6b4713e7b41f7b49bca852caaf55f,
title = "Managing Comprehensive Research Instrument Descriptions Within a Scholarly Knowledge Graph",
abstract = "In research, measuring instruments play a crucial role in producing the data that underpin scientific discoveries. Information about instruments is essential in data interpretation and, thus, knowledge production. However, if at all available and accessible, such information is scattered across numerous data sources. Relating the relevant details, e.g. instrument specifications or calibrations, with associated research assets (data, but also operating infrastructures) is challenging. Moreover, understanding the (possible) use of instruments is essential for researchers in experiment design and execution. To address these challenges, we propose a Knowledge Graph (KG) based approach for representing, publishing, and using information, extracted from various data sources, about instruments and associated scholarly artefacts. The resulting KG serves as a foundation for exploring and gaining a deeper understanding of the use and role of instruments in research, discovering relations between instruments and associated artefacts (articles and datasets), and opens the possibility to quantify the impact of instruments in research.",
keywords = "Instruments (Meta)data, Instruments Knowledge Graph, Machine Actionability, Open Research Knowledge Graph, Scholarly Communication",
author = "Muhammad Haris and S{\"o}ren Auer and Markus Stocker",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 26th International Conference on Asia-Pacific Digital Libraries, ICADL 2024 ; Conference date: 04-12-2024 Through 06-12-2024",
year = "2025",
doi = "10.1007/978-981-96-0868-3_3",
language = "English",
isbn = "9789819608676",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "39--53",
editor = "Gillian Oliver and Viviane Frings-Hessami and Du, {Jia Tina} and Taro Tezuka",
booktitle = "Sustainability and Empowerment in the Context of Digital Libraries ",
address = "Germany",
}