Research Data Management (RDM)
Research Data Management (RDM) is a multifaceted set of processes involving collection, treatment, annotation, preservation and diffusion of research data, and has become a integral part in the administration of research projects.
RDM revolves around concepts and practices carried out for the entire data lifecycle, from the conception of research projects and after their completion.
The Research Data Manager operates within the USI Research and Transfer Service and supports researchers at all levels and from all disciplines in the management of data within their activities/projects:
- Access to research databases
- Data handling and storage
- Drafting a Data Management Plan (DMP)
- Open Research Data (ORD) and FAIR data practices
- Long-term preservation and online repositories
- Calls for projects
- Training sessions
- Workshops, seminars and conferences (institutional and/or external)
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Research Data and its lifecycle
Research data goes through a structured lifecycle that includes various stages from its creation to its eventual archiving or disposal. Understanding the data lifecycle is essential for successful research data management.
The data lifecycle typically involves the following stages:
- Planning
data collection and data management - Generating
data according to the research plan and ensure data quality - Processing
the acquired data and prepare it for sharing - Analysis
of the processed data to generate the verified research results - Archiving
data for long-term preservation - Publication
of the processed research data in a suitable form - Reusability
ensuring reusability of the research data through appropriate licensing
Throughout the research data lifecycle, researchers must also adhere to ethical standards, legal requirements, and institutional policies regarding data management and sharing. Effective data management practices contribute to the reproducibility and transparency of research, fostering collaboration and innovation in the scientific community.
- Planning
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Data Management Plan (DMP)
Many funding agencies such as the Swiss National Science Foundation and the European Research Council are embracing the Open Science principle according to which research funded by the public should be freely and publicly accessible as far as possible. Researchers who are granted public funds are expected to share research data in appropriate digital repositories under the motto “as open as possible, as closed as necessary”.
Hence, those who apply for public funds are requested to present a Data Management Plan (DMP) that outlines the entire lifecycle and the management of the data produced in the scope of the research project. The DMP describes how the data will be (or has been) produced, collected, documented, published and archived during a project. Some important principles must be born in mind when drafting a DMP:
- the DMP is a living document that has to be amended and extended while the project progresses
- the DMP has to assess the data management practices during the project (production, collection, documentation, storage, protection, analysis) and after the project has been completed (publishing, archival, long-term preservation)
- the DMP describes discipline-specific practices and standards, hence it must be tailored from project to project.
