Unified Management Of Multi-Model Data (Vision Paper)

The variety of data is one of the most challenging issues for research and practice in data management. The so-called multi-model data are naturally organized in different and mutually interlinked data formats and logical models, including structured, semi-structured, and unstructured. In this vision paper, we discuss the so far neglected, but for correct and efficient management of multi-model data critical issues and challenges: conceptual modeling of multi-model data, inference of multi-model schemas, unified and conceptual querying, evolution management, and, last but not least, autonomous multi-model data management.