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The DEAP-3600 detector searches for dark matter interactions on a 3.3 tonneliquid argon target. Over nearly a decade, from start of detector constructionthrough the end of the data analysis phase, well over 200 scientists will havecontributed to the project. The DEAP-3600 detector will amass in excess of 900TB of data representing more than 10$^{10}$ particle interactions, a few ofwhich could be from dark matter. At the same time, metadata exceeding 80 GBwill be generated. This metadata is crucial for organizing and interpreting thedark matter search data and contains both structured and unstructuredinformation.  The scale of the data collected, the important role of metadata ininterpreting it, the number of people involved, and the long lifetime of theproject necessitate an industrialized approach to metadata management.  We describe how the CouchDB and the PostgreSQL database systems wereintegrated into the DEAP detector operation and analysis workflows. Thisintegration provides unified, distributed access to both structured(PostgreSQL) and unstructured (CouchDB) metadata at runtime of the dataanalysis software. It also supports operational and reporting requirements.

Database support of detector operation and data analysis in the DEAP-3600 Dark Matter experiment