Data management and sharing activities need to be costed into research, in terms of the time and resources needed. By planning early, costs can be significantly reduced.
There are two approaches to costing research data management and sharing in advance of a research project starting. Either can be used in a data management plan or can inform a funding application.
Approach 1: All data-related activities and resources for the entire data lifecycle – from data creation, through processing, analyses and storage, to sharing and long-term preservation – can be priced to calculate the total cost of all data generation, data sharing, data access and preservation activities.
Approach 2: Only the resources that would be needed to preserve and make research data shareable beyond the primary research team are identified. These resources may include: people, equipment, infrastructure and tools to manage, document, organise, store and provide access to data.
Data management costing tool
There is no hard and fast rule for costing research data management, as some projects will afford more attention to detailed data documentation, organisation and formatting than others as part of routine fieldwork or data preparation before analysis. However, the UK Data Service has developed a simple activity-based costing tool that can be used for approach 2 of costing data management in the social sciences.
How the costing tool was developed
The data management costing tool was developed with researchers as part of the Jisc Data Management Planning for ESRC Research Data-rich Investments project, through data management interviews with researchers in ESRC centres and programmes. Researchers were asked to estimate the time or cost needed for activities related to data collection, data entry and transcription, data validation and documentation and the cost of preparing data for archiving and re-use. Overall, researchers found it hard to cost data management activities, as many activities are an integral part of standard research activities and data analysis. The identified high cost activities were transcribing and anonymising qualitative data and cleaning and verifying quantitative data.
Information from researchers was then combined with our expertise in the measures needed to make research data shareable and reusable. Key is that when preparing data for sharing is left until the end of a project, the cost is often too high due to the competition with publishing and seeking future project funding.
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