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Centralized project-specific metadata platforms: toolkit provides new perspectives on open data management within
Andrew Wright Child1, Jennifer Hinds2, Lucas Sheneman2
1Institute for Interdisciplinary Data Science, Research Computing and Data Services, University of Idaho, Moscow, ID, 83844-2358, USA. awchild@uidaho.edu.
BMC Research Notes
|March 19, 2022
Summary
Open science requires robust data management. A centralized platform can improve data findability, accessibility, and reproducibility for multidisciplinary research, supporting FAIR principles.
Area of Science:
- Scholarly research and data science.
- Information management and scientific collaboration.
Background:
- Open science and open data are increasingly mandated by funding agencies and publishers.
- Effective data management, including metadata, workflow, and source code, is crucial for FAIR (Findable, Accessible, Interoperable, Reusable) principles.
- Discipline-specific metadata standards hinder the cataloging of multidisciplinary data.
Discussion:
- Scattered and incompatible metadata impede scientific innovation by making it difficult to locate and link datasets.
- A centralized, integrated data management platform offers a solution for multi-institutional and interdisciplinary projects.
- Such a platform enhances data findability, accessibility, interoperability, reproducibility, and integrity.
Key Insights:
- Standardized metadata and accessible data are essential for open science.
- Interoperable data management platforms are vital for collaborative, multidisciplinary research.
- Addressing metadata incompatibility is key to overcoming barriers in scientific data sharing.
Outlook:
- Centralized platforms can foster reproducible open science and facilitate public dissemination.
- Future research should focus on developing and implementing interoperable data management frameworks.
- Adoption of integrated platforms will streamline data access and utilization across scientific domains.
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