1. Schema Mappings for Data Graphs
- Author
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Nadime Francis, Leonid Libkin, Laboratory for the Foundations of Computer Science [Edinburgh] (LFCS), University of Edinburgh, and Laboratory for the Foundations of Computer Science [Edinburgh] ( LFCS )
- Subjects
[ INFO ] Computer Science [cs] ,[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] ,Graph database ,Theoretical computer science ,Comparability graph ,0102 computer and information sciences ,02 engineering and technology ,computer.software_genre ,01 natural sciences ,[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB] ,010201 computation theory & mathematics ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,[INFO]Computer Science [cs] ,Graph operations ,Null graph ,Lattice graph ,Graph property ,computer ,Computer Science::Databases ,Complement graph ,Forbidden graph characterization ,Mathematics - Abstract
International audience; Schema mappings are a fundamental concept in data integration and exchange, and they have been thoroughly studied in different data models. For graph data, however, map-pings have been studied in a restricted context that, unlike real-life graph databases, completely disregards the data they store. Our main goal is to understand query answering under graph schema mappings – in particular, in exchange and integration of graph data – for graph databases that mix graph structure with data. We show that adding data querying alters the picture in a significant way. As the model, we use data graphs: a theoretical abstraction of property graphs employed by graph database implementations. We start by showing a very strong negative result: using the simplest form of nontrivial navigation in map-pings makes answering even simple queries that mix navigation and data undecidable. This result suggests that for the purposes of integration and exchange, schema mappings ought to exclude recursively defined navigation over target data. For such mappings and analogs of regular path queries that take data into account, query answering becomes de-cidable, although intractable. To restore tractability without imposing further restrictions on queries, we propose a new approach based on the use of null values that resemble usual nulls of relational DBMSs, as opposed to marked nulls one typically uses in integration and exchange tasks. If one moves away from path queries and considers more complex patterns, query answering becomes undecidable again, even for the simplest possible mappings.
- Published
- 2017
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