Beyond Boundaries: Data Sharing in Motor Development Research--Best Practices, Challenges, and Opportunities
Saved in:
| Title: | Beyond Boundaries: Data Sharing in Motor Development Research--Best Practices, Challenges, and Opportunities |
|---|---|
| Language: | English |
| Authors: | Claudia Niessner (ORCID |
| Source: | Journal of Motor Learning and Development. 2026 14(1). |
| Availability: | Human Kinetics, Inc. 1607 North Market Street, Champaign, IL 61820. Tel: 800-474-4457; Fax: 217-351-1549; e-mail: info@hkusa.com; Web site: https://journals.humankinetics.com/view/journals/jmld/jmld-overview.xml |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Motor Development, Best Practices, Barriers, Opportunities, Data Collection, Information Dissemination, Access to Information, Research |
| DOI: | 10.1123/jmld.2025-0052 |
| ISSN: | 2325-3193 2325-3215 |
| Abstract: | Data sharing is increasingly recognized as a critical practice in scientific research, facilitating transparency, reproducibility, and collaboration. In motor development research, the exchange of data holds particular potential for advancing knowledge and improving methodologies, especially because data collection in motor development research is resource intensive and costly, often requiring specialized equipment, standardized protocols, and longitudinal tracking. However, high data protection requirements, due to the personal nature of the data, pose significant challenges to data sharing. Many motor performance assessments involve children and adolescents, making privacy concerns even more pronounced due to ethical considerations surrounding vulnerable populations. The fragmentation of data sets, the variety of assessment tools, and inconsistencies in data collection methods further complicate large-scale data sharing in motor development research. Addressing these challenges requires the implementation of structured data-sharing frameworks, the development of technical infrastructures, and a shift toward standardized protocols. This research note outlines best practices for data sharing, highlights two prominent projects--MO-RE data (MOtor REsearch data repository) and the COMBINE Project (The Consortium for Motor Behavior in Neurodivergence)--and discusses key challenges and opportunities. The note concludes with implications for researchers aiming to implement data-sharing practices effectively. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1508589 |
| Database: | ERIC |
| Abstract: | Data sharing is increasingly recognized as a critical practice in scientific research, facilitating transparency, reproducibility, and collaboration. In motor development research, the exchange of data holds particular potential for advancing knowledge and improving methodologies, especially because data collection in motor development research is resource intensive and costly, often requiring specialized equipment, standardized protocols, and longitudinal tracking. However, high data protection requirements, due to the personal nature of the data, pose significant challenges to data sharing. Many motor performance assessments involve children and adolescents, making privacy concerns even more pronounced due to ethical considerations surrounding vulnerable populations. The fragmentation of data sets, the variety of assessment tools, and inconsistencies in data collection methods further complicate large-scale data sharing in motor development research. Addressing these challenges requires the implementation of structured data-sharing frameworks, the development of technical infrastructures, and a shift toward standardized protocols. This research note outlines best practices for data sharing, highlights two prominent projects--MO-RE data (MOtor REsearch data repository) and the COMBINE Project (The Consortium for Motor Behavior in Neurodivergence)--and discusses key challenges and opportunities. The note concludes with implications for researchers aiming to implement data-sharing practices effectively. |
|---|---|
| ISSN: | 2325-3193 2325-3215 |
| DOI: | 10.1123/jmld.2025-0052 |
