Recommendation of: Bridging Interdisciplinary Research Data Management and Data Science through Modular Research Processes. Round#2

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Key Points

The aim is to recommend methods for integrating interdisciplinary research data management with data science effectively.
Development of modular research processes to facilitate better collaboration.
In-depth analysis of existing research data management frameworks.
Engagement with various stakeholders in research data management and data science.
Identified key areas where data management and data science can work together more efficiently.
Proposed specific strategies for bridging gaps in research processes.
Highlighted the importance of interdisciplinary collaboration in enhancing research outcomes.

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Recommendation proposes improved integration of data management and science through modular processes, indicating impactful research collaboration.

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George Pavlidis (2026) studied this question.

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