TY - CHAP A1 - Störl, Uta A1 - Müller, Daniel A1 - Tekleab, Alexander A1 - Tolale, Stephane A1 - Stenzel, Julian A1 - Klettke, Meike A1 - Scherzinger, Stefanie A1 - Storl, Uta A1 - Muller, Daniel T1 - Curating Variational Data in Application Development T2 - 2018 IEEE 34th International Conference on Data Engineering, 16-19 April 2018, Paris, France N2 - Building applications for processing data lakes is a software engineering challenge. We present Darwin, a middleware for applications that operate on variational data. This concerns data with heterogeneous structure, usually stored within a schema-flexible NoSQL database. Darwin assists application developers in essential data and schema curation tasks: Upon request, Darwin extracts a schema description, discovers the history of schema versions, and proposes mappings between these versions. Users of Darwin may interactively choose which mappings are most realistic. Darwin is further capable of rewriting queries at runtime, to ensure that queries also comply with legacy data. Alternatively, Darwin can migrate legacy data to reduce the structural heterogeneity. Using Darwin, developers may thus evolve their data in sync with their code. In our hands-on demo, we curate synthetic as well as real-life datasets. KW - data migration KW - Data mining KW - Evolution (biology) KW - history KW - NoSQL databases KW - query rewriting KW - schema evolution KW - schema management KW - Software KW - Task analysis KW - variational data Y1 - 2018 U6 - https://doi.org/10.1109/ICDE.2018.00187 SP - 1605 EP - 1608 PB - IEEE ER -