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Beyond Boundaries: Data Sharing in Motor Development Research--Best Practices, Challenges, and Opportunities

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Title: Beyond Boundaries: Data Sharing in Motor Development Research--Best Practices, Challenges, and Opportunities
Language: English
Authors: Claudia Niessner (ORCID 0000-0003-2094-0836), Nicholas E. Fears (ORCID 0000-0001-7081-0015), Katja Keller (ORCID 0000-0002-8491-2247), Tanja Eberhardt (ORCID 0009-0001-0992-060X), Hannah Zimmermann, Priscila M. Tamplain (ORCID 0000-0003-2713-5733), Haylie L. Miller (ORCID 0000-0003-4372-1206)
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
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  Data: <searchLink fieldCode="AR" term="%22Claudia+Niessner%22">Claudia Niessner</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2094-0836">0000-0003-2094-0836</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nicholas+E%2E+Fears%22">Nicholas E. Fears</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7081-0015">0000-0001-7081-0015</externalLink>)<br /><searchLink fieldCode="AR" term="%22Katja+Keller%22">Katja Keller</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8491-2247">0000-0002-8491-2247</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tanja+Eberhardt%22">Tanja Eberhardt</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0001-0992-060X">0009-0001-0992-060X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hannah+Zimmermann%22">Hannah Zimmermann</searchLink><br /><searchLink fieldCode="AR" term="%22Priscila+M%2E+Tamplain%22">Priscila M. Tamplain</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2713-5733">0000-0003-2713-5733</externalLink>)<br /><searchLink fieldCode="AR" term="%22Haylie+L%2E+Miller%22">Haylie L. Miller</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4372-1206">0000-0003-4372-1206</externalLink>)
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  Data: 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.
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