Risk aware Data Management in Metagenomics

The concept of e-Science applies to science that, increasingly, is executed through distributed global collaborations where extensive data collections are processed by large scale computing resources through scientific workflows. These data can be heterogeneous, with multiple provenances, created and transformed according to different data schemas, and the processing can be distributed by multiple locations. This emerging reality brings new challenges, like the preservation of these data workflows. To address specific concerns with Data Management (DM), the concept of Data Management Plan (DMP) was established. However, we claim actual guidelines for DMP ignore achievements by the digital preservation community indicating DM should be mainly a Risk Management (RM) activity. Therefore, we propose to reanalyze the concept of DMP considering the best practices of RM, and claim the concept should be complemented by a Risk Management Plan. The motivation, requirements and validation of this proposal is the project MetaGenFRAME, focused in Meta-