Using DDI as the metadata language for research data

At GESIS - Leibniz Institute for the Social Sciences, we have used DDI from the beginning. Mainly for data archiving, but recently, for more stages in the research data lifecycle, the DDI-Codebook and DDI-Lifecycle standards have become the language for documenting and re-using survey questionnaires and datasets for the social sciences. DDI is also being considered for documenting other data sources beyond the traditional surveys, such as digital behavioural data and web tracking data. The data archiving is currently in the process of migrating documentation from applications which were developed in-house to the Colectica software components. After introducing the process for data documentation and publication with Colectica for new studies, older studies were migrated to the new software. Several tools accomplish different functions, e.g., study-level documentation, PID registration, data file management, and question and variable documentation. During the change of workflows, older and newer tools are used in parallel, which results in the need for clear interfaces. DDI has become the language used to define the metadata needs and specify the integration of these tools. Metadata production is more complicated and challenging during the time of transition, but will be more stable and reliable in the future. This presentation will show the current workstate and highlight challenges and improvements for managing metadata across different lifecycle steps at GESIS.