Planning data management

A data management plan (DMP) is a document that describes the data a researcher will use, its origin, and how and for how long it will be stored and preserved. For many researchers, the first encounter with a DMP comes when reviewing funders’ application requirements. In practice, however, a carefully prepared DMP is often of greatest benefit to the researcher themselves. Well-defined and thoroughly considered data management procedures make it possible to focus on the research rather than on administrative issues during the project. Establishing a clear plan also helps to avoid potential errors and obstacles that might otherwise emerge unexpectedly later in the project.

Funders’ expectations

An increasing number of research funders and academic publishers require researchers to provide some form of data management plan or data management statement. As requirements vary across funders and funding schemes, it is always advisable to consult the funder’s guidance documents for their specific expectations regarding research data management and compliance with open science principles. Regardless of whether a formal data management plan is required, having one in place generally facilitates the preparation of funding applications, ethics committee submissions and research publications.

Costs related to research data management

Research data management often entails financial costs, the extent of which depends largely on the volume of data involved and the complexity of the planned data processing activities. Some funders (e.g. Horizon Europe) allow data management costs to be included in project budgets and expect applicants to provide a reasonable estimate of these expenses. In social science research projects, the most common cost categories include:

• personnel costs: staff time spent by project team members and external personnel (e.g. students) on data collection, processing and documentation;
• transcription, translation and language editing for qualitative studies;
• software licences for applications not provided centrally by the University of Tartu (MAXQDA, Stata, etc.);
• storage and infrastructure costs: data storage on the University of Tartu’s cloud services is available free of charge to university staff. However, projects involving large volumes of data or sensitive information may require the use of fee-based services and support of the University of Tartu High Performance Computing Center, for example;
• publication and archiving fees: obtaining a DataDOI is free of charge for University of Tartu researchers, but international repositories may charge fees for data deposition.