  The increasing volumes of data produced by high-throughput instruments
coupled with advanced computational infrastructures for scientific computing
have enabled what is often called a {\em Fourth Paradigm} for scientific
research based on the exploration of large datasets. Current scientific
research is often interdisciplinary, making data integration a critical
technique for combining data from different scientific domains. Research data
management is a critical part of this paradigm, through the proposition and
development of methods, techniques, and practices for managing scientific data
through their life cycle. Research on microbial communities follows the same
pattern of production of large amounts of data obtained, for instance, from
sequencing organisms present in environmental samples. Data on microbial
communities can come from a multitude of sources and can be stored in different
formats. For example, data from metagenomics, metatranscriptomics,
metabolomics, and biological imaging are often combined in studies. In this
article, we describe the design and current state of implementation of an
integrative research data management framework for the Cluster of Excellence
Balance of the Microverse aiming to allow for data on microbial communities to
be more easily discovered, accessed, combined, and reused. This framework is
based on research data repositories and best practices for managing workflows
used in the analysis of microbial communities, which includes recording
provenance information for tracking data derivation.
