## **IDCC18** #### **Barcelona, Spain | 19 February 2018** --- #### **Curating for Reproducibility: Producing High Quality Data and Code for Transparent and Reproducible Research** ##### **Florio Arguillas, Cornell Institute for Social and Economic Research (CISER), Cornell University** ##### **Thu-Mai Christian, Odum Institute, University of North Carolina at Chapel Hill** ##### **Limor Peer, Institution for Social And Policy Studies (ISPS), Yale University** The imperative of scientific reproducibility provides a common purpose and language for data professionals and researchers. For data professionals, reproducibility can be a framework to hone and justify curation actions and decisions, and for researchers it offers a rationale for inserting best practices early into the research lifecycle. We consider activities that ensure that statistical and analytic claims about given data can be reproduced with that data, curating for reproducibility (CURE). This half day workshop will teach participants practical strategies for curating research materials for reproducibility. The workshop will be based on the data quality review, a framework for helping ensure that research data are usable, that code executes properly and reproduces analytic results, and that all digital scholarly objects are well documented. The workshop will introduce models for putting this framework into practice. Participants will learn about the basic components of the CURE workflow using examples and hands-on activities. The workshop will also demonstrate a tool that structures the CURE workflow. **[Workshop Agenda][1]** **[Workshop Slides][2]** [1]: https://osf.io/3e652/ [2]: https://osf.io/spjbk/3e652/