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Here we present CaosDB, a Research Data Management System (RDMS) designed toensure seamless integration of inhomogeneous data sources and repositories oflegacy data. Its primary purpose is the management of data from biomedicalsciences, both from simulations and experiments during the complete researchdata lifecycle. An RDMS for this domain faces particular challenges: Researchdata arise in huge amounts, from a wide variety of sources, and traverse ahighly branched path of further processing. To be accepted by its users, anRDMS must be built around workflows of the scientists and practices and thussupport changes in workflow and data structure. Nevertheless it shouldencourage and support the development and observation of standards andfurthermore facilitate the automation of data acquisition and processing withspecialized software. The storage data model of an RDMS must reflect thesecomplexities with appropriate semantics and ontologies while offering simplemethods for finding, retrieving, and understanding relevant data. We show howCaosDB responds to these challenges and give an overview of the CaosDB Server,its data model and its easy-to-learn CaosDB Query Language. We briefly discussthe status of the implementation, how we currently use CaosDB, and how we planto use and extend it.

CaosDB - Research Data Management for Complex, Changing, and Automated Research Workflows