Research data vary considerably, and therefore the solutions used to manage them also differ. Data management is a form of creative problem-solving and an essential component of responsible and ethical research. The aim of data management is not to apply a single model to all research projects. Rather, guidance and support services are intended to help researchers identify solutions that are appropriate for their data, research design, and research environment.
Well-designed data management supports the reliability, transparency, reproducibility, and potential reuse of research. Data management encompasses the entire lifecycle of research data, from research planning through data collection or acquisition, processing, analysis, documentation, and storage, to the sharing, archiving, or deletion of data after the completion of the research project.
Research data may vary, for example, with respect to how they are generated, their data protection and information security requirements, contractual obligations, technical solutions, and opportunities for future reuse. As a result, data management practices differ between data types. This series of data guides examines key data management issues from the perspective of different types of research data.
Not all research data can or should be made available for reuse. Data sharing may be restricted, for example, by the protection of personal data, copyright, contractual obligations, or research ethics considerations. Even when the data themselves cannot be published, metadata, documentation, analytical methods, or software code used in the research can often be made available to other researchers. This supports research transparency, the evaluation of research findings, and the broader goals of open science.
The purpose of this guide is to help researchers identify the key data management issues associated with their particular type of research data and to find practical solutions for different stages of the research process. The guide complements the organisation's general guidance on research data management, data protection, information security, and open science.
The University of Helsinki Data Support service provides researchers with
The Editorial Board of the SSH Research Data Management Handbooks: Salla-Maaria Laaksonen, Maija Paavolainen, Jaakko Hillo, Mari Siiroinen, Anna Jarske-Fransas, Antti Kanner, Mikko Ojanen, Mietta Lennes, Risto Kunelius, Hanna Remes, Liina Junna