JISC

Overview

The DataTrain project aims to build on findings and tools developed in the Incremental project (JISC 07/09 funding strand) by developing disciplinary focussed data management training modules for post-graduate courses in Archaeology and Social Anthropology at the University of Cambridge.

To this end, the project will develop training modules for each of the two departments, and pilot these as part of the departments’ postgraduate training provision in Spring of 2011. Beyond this, the modules would be embedded within research methods courses in each department.

Aims and Objectives

The aim of DataTrain is to improve data management training at the University of Cambridge by working with staff in two departments, Archaeology and Social Anthropology to design and pilot courses for postgraduate students. Advice will be sought from the ADS on data management practices, in particular for Archaeology.

The objectives are (1) gather and analyse discipline requirements; (2) design training modules for both disciplines; (3) pilot the courses within relevant existing training courses that the departments run; (4) embed the courses within the departments and (5) deliver resources and findings to the ADS, DCC and JISC for wider dissemination.

Project Methodology

The project will start by identifying requirements for Social Anthropology and by reviewing existing data management (DM) resources available in both disciplines. These resources will be repurposed and included in data management training modules which will be piloted in each department and revised according to feedback. The courses will then be embedded in the departments and possibly offered to other students via the University’s skills transfer programme. Outputs will also be deposited with the ADS, DCC and JISC.

Anticipated Outputs and Outcomes

DataTrain will continue developing the supportive infrastructure for research data management which the Incremental project has already started developing. Specific outputs will be the research data management training modules which will be embedded within the departments. The aim is also to establish this as a model for the University Library to work with departments developing data management training courses. Training resources developed will also be shared with a wider community via the ADS and the DCC.