Simplifying schema mappings

Calvanese, Diego; Giacomo, Giuseppe De; Lenzerini, Maurizio; Vardi, Moshe Y.

doi:10.1145/1938551.1938568

Cited by 14 publications

(14 citation statements)

References 48 publications

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“…As in most data management applications, it is common that some information is missing, typically due to using data that is the result of another query or transformation [6][7][8]. For example, in a social network we may have edges a x  −→ b and a ′ x  −→ b ′ , saying that the relationship between a and b is the same as that between a ′ and b ′ .…”

Section: Introductionmentioning

confidence: 99%

On solving integral equations using Markov chain Monte Carlo methods

Doucet

Johansen

Tadic

2010

Applied Mathematics and Computation

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a b s t r a c tWe study regular expressions that use variables, or parameters, which are interpreted as alphabet letters. We consider two classes of languages denoted by such expressions: under the possibility semantics, a word belongs to the language if it is denoted by some regular expression obtained by replacing variables with letters; under the certainty semantics, the word must be denoted by every such expression. Such languages are regular, and we show that they naturally arise in several applications such as querying graph databases and program analysis. As the main contribution of the paper, we provide a complete characterization of the complexity of the main computational problems related to such languages: nonemptiness, universality, containment, membership, as well as the problem of constructing NFAs capturing such languages. We also look at the extension when domains of variables could be arbitrary regular languages, and show that under the certainty semantics, languages remain regular and the complexity of the main computational problems does not change.

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Section: Introductionmentioning

confidence: 99%

On solving integral equations using Markov chain Monte Carlo methods

Doucet

Johansen

Tadic

2010

Applied Mathematics and Computation

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“…C2RPQ-mappings have been studied in contexts different from data exchange, such as query answering using views [15], and, more recently, in terms of its optimization properties [16], but so far none of these classes has been studied from a data exchange point of view. It is worth remarking that the use of (C)NREs in mappings is important, since (C)NRE-based mappings let one express relevant graph data exchange properties that mappings based on C2RPQs cannot express (see e.g.…”

Section: Schema Mappings For Graph Datamentioning

confidence: 99%

“…Tasks such as data exchange, data integration and, more generally, schema mapping management, have so far received very little attention in the graph database context compared to its relational and XML counterparts [3]. Some remarkable exceptions can be found in the work by Calvanese et al regarding rewriting of views for graph databases [14], and more recently the study of schema mapping simplification in the same context [16].…”

Section: Introductionmentioning

confidence: 99%

Schema mappings and data exchange for graph databases

Barceló

Pérez

Reutter

2013

Proceedings of the 16th International Conference on Database Theory

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Data exchange and schema mapping management have received little attention so far in the graph database scenario, and tools developed in this context for relational databases have significant drawbacks in the context of graph-structured data. In this paper we embark on the study of interoperability issues for graph databases, including schema mappings, data exchange and certain answers computation.We start by analyzing different possibilities for specifying mappings in graph databases. Our mapping languages are based on the most typical graph databases queries, ranging from regular path queries to conjunctions of nested regular expressions. They subsume all previously considered mapping languages, and let one express many data exchange scenarios in the graph database context. We study the problems of materializing solutions and query answering, in particular, the problem of computing universal representatives and certain answers for various classes of mappings. We show that both problems are difficult with respect to combined complexity, and that for the latter problem, even data complexity is high for some very simple mappings and queries. We then identify relevant classes of mappings and queries for which the problems of materializing solutions and query answering can be solved efficiently.

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“…Partial databases -whether relational or XML -are typically viewed as patterns [Barceló et al 2010b;Björklund et al 2007;Imielinski and Lipski 1984]. For graph data, the study of schema mappings and transformations for data exchange an integration has started recently [Calvanese et al 2011;San Martín and Gutierrez 2009], but techniques for querying resulting partially specified graphs are currently lacking.…”

Section: Introductionmentioning

confidence: 99%

Querying Regular Graph Patterns

Barceló

Libkin

Reutter

2014

J. ACM

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Graph data appears in a variety of application domains, and many uses of it, such as querying, matching, and transforming data, naturally result in incompletely specified graph data, that is, graph patterns. While queries need to be posed against such data, techniques for querying patterns are generally lacking, and properties of such queries are not well understood.Our goal is to study the basics of querying graph patterns. The key features of patterns we consider here are node and label variables and edges specified by regular expressions. We provide a classification of patterns, and study standard graph queries on graph patterns. We give precise characterizations of both data and combined complexity for each class of patterns. If complexity is high, we do further analysis of features that lead to intractability, as well as lower-complexity restrictions. Since our patterns are based on regular expressions, query answering for them can be captured by a new automata model. These automata have two modes of acceptance: one captures queries returning nodes, and the other queries returning paths. We study properties of such automata, and the key computational tasks associated with them. Finally, we provide additional restrictions for tractability, and show that some intractable cases can be naturally cast as instances of constraint satisfaction problems.

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Simplifying schema mappings

Cited by 14 publications

References 48 publications

On solving integral equations using Markov chain Monte Carlo methods

On solving integral equations using Markov chain Monte Carlo methods

Schema mappings and data exchange for graph databases

Querying Regular Graph Patterns

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