INTERDISCIPLINARY APPROACHES TO RESEARCH DATA MANAGEMENT: BRIDGING THE GAP BETWEEN HUMANITIES, SOCIAL SCIENCES AND STEM FIELDS

Interdisciplinary approaches to research data management (RDM) are crucial in addressing the growing complexities of modern research across diverse fields. While the demands for managing data in the Humanities, Social Sciences and STEM (Science, Technology, Engineering, and Mathematics) are often distinct, the integration of practices from these disciplines can foster more effective and comprehensive data stewardship. This paper explores the challenges and opportunities in bridging the gap between these fields, emphasizing the need for a unified framework that accommodates the varied nature of data types, methodologies and research outcomes. By examining the unique data practices and workflows within each domain, the paper highlights commonalities and divergences in the handling, sharing and preservation of data. The study suggests that cross-disciplinary collaboration can promote best practices, enhance data interoperability and ensure that research data is accessible and reusable across disciplines. Ultimately, this work advocates for the development of adaptable RDM strategies that support both discipline-specific needs and the overarching goal of advancing open science and knowledge sharing.

Keywords: STEM Fields, Data Stewardship, Data Integration, Research Data Framework, Data Accessibility, Data Reusability, Unified Data Management, Research Data Management.