Recognise, cite and acknowledge contributions

This interactive on-line course prepared by the Social Science Research Council and the Qualitative Data Repository contains four modules about different aspects of RDM of qualitative data in Social Sciences. Each module is composed by multiple lessons and can also function as a stand-alone resource to be completed individually. Most lessons include associated readings, resources, exercises, and activities.

This Open Source tool developed by the Institute of Formal and Applied Linguistics of Charles University guides the user through a decision tree approach to select a license for their research output. The tool considers scenarios where the user does not own copyright or similar rights in some of all of the constitutive parts of the dataset and provides further guidance based on whether those elements are clearly licensed or not.