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Ontologies in Motion: A BFO-Based Approach to Knowledge Graph Construction for Motor Performance Research Data in Sports Science

arXiv 2510.15983 ↗First posted 13 Oct 2025cs.AIcited by 0

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Abstract (arXiv)

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).

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References · 5

  1. 2023Knowledge Graphs: Opportunities and Challengescited by 70
  2. 2021Is preprint the future of science? A thirty year journey of online preprint servicescited by 4
  3. 2022The Rise of GitHub in Scholarly Publicationscited by 4
  4. 2024Toward FAIR Semantic Publishing of Research Dataset Metadata in the Open Research Knowledge Graphcited by 2
  5. 2024NFDIcore 2.0: A BFO-Compliant Ontology for Multi-Domain Research Infrastructurescited by 2

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