Implementation of the floodlight e-Research technology for spatiotemporal movement data analysis in sport sciences (Phase 2)

• Applicant: Professor Dr. Daniel Memmert
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 522904388

Spatiotemporal movement data, collected at large scales for major team sports, is a novel data source that carries the potential to propel several sports science fields such as exercise physiology, biomechanics, human movement science, and sports informatics. Given sport data’s favorable combination of complexity and controllability, the analysis of spatiotemporal movement data in a sports context is a strong candidate to further provide fundamental insights into collective movement behavior and human organization. However, this potential has only partially been accessed due to the present technical requirements in team sport data analysis. The current demands for managing, loading, processing and analyzing team sport data analysis far exceed the average programming skills of well-trained sport scientists, and up to date, no suitable open or proprietary solutions exist to close this gap. Within the scientific domain, this has led to a culture where data and code sharing, conducting replication studies as well as research incorporating previous findings is largely disregarded and therefore lacking. The aim of this project is to implement e-Research technologies for the analysis of spatiotemporal movement data in sport sciences. The implementation is based on the recently released floodlight software package, which is a software framework prototype that includes functionality spanning the entire data analysis pipeline. A major part of the project consists of expanding this prototype into an sophisticated, domain-specific data analysis toolbox including external interfaces such as provider-specific data formats or public data sets; data manipulation methods such as spatial or temporal transformations, interpolation and imputation methods and data signal filters; a wide range of proven data models; an open science primary data process to allow data and code sharing as well as replication of experiments; means of visualization such as static figures and interactive graphical user interfaces. The implementation part of the project is complemented by work packages focusing on the training of aspiring scientists in usage and development of e-Research technologies, evaluation of implementations, as well as actively fostering of an open science culture within the domain. The ultimate goal of this project is to develop, establish and permanently ensure access to e-Research technologies for spatiotemporal movement data analysis. The project is expected to set a new gold standard and become a major international platform for data and code sharing. With the software prototype as a starting point, the project will feed back into the community right from the start and support the development towards an open science culture.

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)
• Co-Investigator: Dominik Raabe