Tutkimusdatahallinta

Tutkimusdatahallinta, or research data management (RDM), refers to the systematic organization, storage, documentation, and preservation of data generated during research activities. It encompasses the entire lifecycle of research data, from its creation and collection to its analysis, sharing, and long-term archiving. Effective RDM ensures that data is reliable, accessible, and reusable, thereby enhancing the integrity and reproducibility of research.

Key components of research data management include data planning, data collection, data organization and documentation, data storage and backup, data sharing, and data archiving. Researchers are increasingly expected to develop data management plans (DMPs) that outline how data will be handled throughout the research project. This includes specifying data formats, metadata standards, security measures, and plans for data sharing and preservation.

Properly managed research data facilitates collaboration among researchers, supports the validation of research findings, and enables data reuse for new research questions, potentially leading to further discoveries. Many research funding agencies and academic institutions now mandate or strongly encourage robust RDM practices as a condition of funding and publication. Adherence to RDM principles contributes to transparency, accountability, and the overall advancement of scientific knowledge.