How can we create efficient workflows and facilitate optimal collaboration in teams? How can we ensure that our research processes, our data collection, and our complex (Big) Data analyses can be re-traced by ourselves and other researchers, both in the near and distant future? How can we build our analyses in a way that they can be run reliably and stably on other researchers' computers, regardless of the hardware and software environment? Efficient and reproducible workflows are essential to keep up with the increasing amount of data and complexity of analyses. In recent years, exciting new tools have emerged that enable effective data management and research collaboration. Not only do these new tools help us streamline our workflows, but they also make our research outputs more visible, citable, and sustainable. From the first day we begin adapting our research practices, we benefit from greater efficiency, ease of tracing our research progress, and smoother collaboration with other researchers. In the long run, these practices help us maintain a high quality of research outputs and meet the replicability and transparency standards that an increasing number of journals require for publication. This course provides participants with the skills to harness the potential of new tools that help create efficient workflows and optimize research outputs. It equips them with a toolkit to conduct research that is well organized and documented, and can be readily disseminated and reproduced, both when working on independent projects and in collaborations with others.

 

For additional details on the course and a day-to-day schedule, please download the full-length syllabus.

By the end of the course participants will:

 

Participants will also need to register for free online accounts with GitHub and DockerHub. Course participants will receive

 

Participants should bring their own laptops. More information on software/packages will be provided before the course.