Managing Comprehensive Research Instrument Descriptions within a Scholarly Knowledge Graph

TL;DR

This paper introduces a Knowledge Graph approach to organize and connect detailed research instrument information across sources, enhancing understanding and impact analysis in scientific research.

Contribution

It presents a novel KG-based framework for integrating instrument data with scholarly artifacts, facilitating better exploration and impact quantification.

Findings

Improved access to instrument information across data sources

Enhanced understanding of instrument roles in research

Potential for quantifying instrument impact

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.