How the NCCR Microbiomes uses Renku to keep data and code alive despite PhD student turnover
Five research groups in the NCCR Microbiomes are collaborating on long-term study. One of the student researchers generates data, performs analyses, and then graduates - as students do - and the project goes on. Months after her departure, a collaborator from a different research group has a question about one of the figures she generated: at which taxonomic level did she perform that ordination? A couple of years ago, he would have sent an e-mail and hoped that, despite the fact that she's been busy transitioning to a new role, she could recall or quickly find the answer. Luckily, however, he has a simpler alternative: opening their Renku project and retracing the creation of her figure. He sees the data as she left them, the steps of her analysis, and which variables she plotted. He can also easily re-run the ordination at a different taxonomic level, just to see how it compares.
This level of reproducibility is possible because the NCCR Microbiomes teamed up with the SDSC to support their active-phase research projects. Specifically, they expanded the reach of the Renku platform, to connect to data on institutional servers. This is a key feature for researchers who are required to store research data on these servers, but wish to collaborate across institutions sharing data, code and compute resources. In this post we describe a specific example of how the approach pays off.
