Ontologies in Motion: A BFO-Based Approach to Knowledge Graph Construction for Motor Performance Research Data in Sports Science
Abstract
An essential component for evaluating and comparing physical and cognitive capabilities between populations is the testing of various factors related to human performance. As a core part of sports science research, testing motor performance enables the analysis of the physical health of different demographic groups and makes them comparable. The Motor Research (MO|RE) data repository, developed at the Karlsruhe Institute of Technology, is an infrastructure for publishing and archiving research data in sports science, particularly in the field of motor performance research. In this paper, we present our vision for creating a knowledge graph from MO|RE data. With an ontology rooted in the Basic Formal Ontology, our approach centers on formally representing the interrelation of plan specifications, specific processes, and related measurements. Our goal is to transform how motor performance data are modeled and shared across studies, making it standardized and machine-understandable. The idea presented here is developed within the Leibniz Science Campus ``Digital Transformation of Research'' (DiTraRe).
Cite
@article{arxiv.2510.15983,
title = {Ontologies in Motion: A BFO-Based Approach to Knowledge Graph Construction for Motor Performance Research Data in Sports Science},
author = {Sarah Rebecca Ondraszek and Jörg Waitelonis and Katja Keller and Claudia Niessner and Anna M. Jacyszyn and Harald Sack},
journal= {arXiv preprint arXiv:2510.15983},
year = {2025}
}
Comments
10 pages, 2 figures. Camera-ready version. Accepted to the 5th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment; 2 November 2025 - Nara, Japan; co-located with The 24th International Semantic Web Conference, ISWC 2025. To be published in CEUR proceedings