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Current state of data stewardship tools in life science
Anna Aksenova1, Anoop Johny2, Tim Adams2
1Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, Bonn, Germany.
Frontiers in Big Data
|October 1, 2024
Summary
Effective data stewardship is crucial for scientific advancement. This study reviews over 300 tools and frameworks vital for modern data management in life sciences research.
Area of Science:
- Life Sciences
- Data Science
- Information Management
Background:
- The increasing volume and complexity of data in scientific research necessitate robust data stewardship practices.
- Effective data stewardship is fundamental for ensuring data integrity, accessibility, and usability, thereby accelerating scientific discovery.
- Modern research relies heavily on well-managed data for reproducibility and innovation.
Purpose of the Study:
- To provide a comprehensive overview of essential tools and frameworks for contemporary data stewardship.
- To assess the utility, relevance, and applicability of various data stewardship resources.
- To guide researchers and institutions in selecting appropriate data stewardship solutions, particularly within the life sciences.
Main Methods:
- Systematic analysis of over 300 data stewardship tools and frameworks.
- Evaluation criteria included utility, relevance to data stewardship principles, and domain-specific applicability.
- Focus on tools pertinent to the life sciences research landscape.
Main Results:
- Identification of key tools and frameworks supporting modern data stewardship.
- Assessment of the strengths and weaknesses of analyzed resources.
- Categorization of tools based on their functionality and impact on research workflows.
Conclusions:
- A curated selection of tools and frameworks can significantly enhance data stewardship practices.
- Strategic implementation of these resources is vital for maximizing research efficiency and data integrity.
- The findings offer practical guidance for optimizing data management in life sciences and beyond.
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