Publication:
An open science model for research data management at the Malaysia National Institutes of Health

Date

2024

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Kuala Lumpur : Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2024

Subject LCSH

National Institutes of Health -- Malaysia
Research -- Data processing
Electronic information resources -- Management

Subject ICSI

Call Number

et Q 180.55 E4 M21O 2024

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Abstract

This research develops an open science model for research data management at the Malaysia National Institutes of Health (NIH), a leading health research organization in the country. It addresses the challenge of low researcher participation observed during the initial implementation of the NIH-Data Repository System (NIH-DaRS). Recognizing the importance of open science in promoting collaboration, transparency, and accessibility of research, this research aimed at investigating the readiness of the researchers and institute to embrace open science practices. Several factors, spanning technical, motivational, economic, political, legal, and ethical realms, have been recognized as impediments to data sharing in advancing open science participation. However, these factors have been identified based on diverse institutions and organizations, prompting a need to recognize factors applicable to the Malaysian NIH context. To address this gap, an exploratory sequential mixed-method approach was employed. This approach consisted of qualitative data collection through semi-structured interviews with NIH management staff and quantitative data collected through an online survey from researchers working with the institute. Lastly, the developed model was presented to the NIH management for validation. The qualitative phase identified all possible factors influencing participation in open science through research data sharing and reuse, alongside the benefits and challenges of integrating the FAIR principles (Findable, Accessible, Interoperable, and Reusable) into research data management. On the other hand, the quantitative phase was used to test and confirm the research hypotheses derived from the qualitative findings using SEM (Structural Equation Modelling). Both findings were then triangulated to enhance the research's validity and credibility and provide a more comprehensive understanding of the phenomenon under study. The main contributions of this research are: (1) Providing an empirical understanding of the current practices and perceptions of open science among NIH researchers. (2) Proposing a comprehensive and evidence-based open science model for research data management that incorporates the FAIR principles, rewards and incentives, awareness and capacity building, policies and regulations, available platforms and repositories, trust and confidence, efforts and sacrifices, and data characteristics. (3) Recommending a set of guidelines and best practices for implementing open science at the NIH. (4) By meticulously developing a detailed and precise interview guide and questionnaire, this research not only advances practical, theoretical, and methodological knowledge on open science in the context of health research data management, but also sets a strong foundation for future research in this domain. The research concludes with implications for stakeholders, limitations, and directions for future research.

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