Regular path query languages for data graphs are essentially . The lack of type information greatly limits the optimization opportunities for query engines and makes application development more complex. In this paper we discuss a simple, yet expressive, schema language for edge-labelled data graphs. This schema language is, then, used to define a query type inference approach with good precision properties.
SheX @cite_11 is a schema language for RDF data. As in TSL, in SheX it is possible to describe complex node structures, and, unlike in TSL, outgoing edges can be defined by using regular expressions. However, just as in TSL, there is no way to specify constraints on incoming edges. This means that, for instance, in a schema describing cars and car owners, one can impose the constraint that a single person can own at most @math cars, but not the constraint that a car can have one single owner at a time. This makes impossible to define empty SheX schemas, but it limits the expressivity of the language.
@cite_11
2167961018 1983077505 2741223254 2013096722
We study the expressiveness and complexity of Shape Expression Schema (ShEx), a novel schema formalism for RDF currently under development by W3C. ShEx assigns types to the nodes of an RDF graph and allows to constrain the admissible neighborhoods of nodes of a given type with regular bag expressions (RBEs). We formalize and investigate two alternative semantics, multi-and single-type, depending on whether or not a node may have more than one type. We study the expressive power of ShEx and study the complexity of the validation problem. We show that the single-type semantics is strictly more expressive than the multi-type semantics, single-type validation is generally intractable and multi-type validation is feasible for a small (yet practical) subclass of RBEs. To curb the high computational complexity of validation, we propose a natural notion of determinism and show that multi-type validation for the class of deterministic schemas using single-occurrence regular bag expressions (SORBEs) is tractable. We prove that entailment for RDF Schema (RDFS) is decidable, NP-complete, and in P if the target graph does not contain blank nodes. We show that the standard set of entailment rules for RDFS is incomplete and that this can be corrected by allowing blank nodes in predicate position. We define semantic extensions of RDFS that involve datatypes and a subset of the OWL vocabulary that includes the property-related vocabulary (e.g. FunctionalProperty), the comparisons (e.g. sameAs and differentFrom) and the value restrictions (e.g. allValuesFrom). These semantic extensions are in line with the 'if-semantics' of RDFS and weaker than the 'iff-semantics' of D-entailment and OWL (DL or Full). For these semantic extensions we present entailment rules, prove completeness results, prove that consistency is in P and that, just as for RDFS, entailment is NP-complete, and in P if the target graph does not contain blank nodes. There are no restrictions on use to obtain decidability: classes can be used as instances. Semi-structured data models like the Resource Description Framework (RDF), naturally allow for modeling the same real-world entity in various ways. For example, different RDF vocabularies enable the definition of various RDF graphs representing the same drug in Bio2RDF or Drugbank. Albeit semantically equivalent, these RDF graphs may be syntactically different, i.e., they have distinctive graph structure or entity identifiers and properties. Existing data-driven integration approaches only consider syntactic matching criteria or similarity measures to solve the problem of integrating RDF graphs. However, syntactic-based approaches are unable to semantically integrate heterogeneous RDF graphs. We devise SJoin, a semantic similarity join operator to solve the problem of matching semantically equivalent RDF graphs, i.e., syntactically different graphs corresponding to the same real-world entity. Two physical implementations are proposed for SJoin which follow blocking or non-blocking data processing strategies, i.e., RDF graphs can be merged in a batch or incrementally. We empirically evaluate the effectiveness and efficiency of the SJoin physical operators with respect to baseline similarity join algorithms. Experimental results suggest that SJoin outperforms baseline approaches, i.e., non-blocking SJoin incrementally produces results faster, while the blocking SJoin accurately matches all semantically equivalent RDF graphs. Data-Exchange is the problem of creating new databases according to a high-level specification called a schema-mapping while preserving the information encoded in a source database. This paper introduces a notion of generalized schema-mapping that enriches the standard schema-mappings (as defined by ) with more expressive power. It then proposes a more general and arguably more intuitive notion of semantics that rely on three criteria: Soundness, Completeness and Laconicity (non-redundancy and minimal size). These semantics are shown to coincide precisely with the notion of cores of universal solutions in the framework of Fagin, Kolaitis and Popa. It is also well-defined and of interest for larger classes of schema-mappings and more expressive source databases (with null-values and equality constraints). After an investigation of the key properties of generalized schema-mappings and their semantics, a criterion called Termination of the Oblivious Chase (TOC) is identified that ensures polynomial data-complexity. This criterion strictly generalizes the previously known criterion of Weak-Acyclicity. To prove the tractability of TOC schema-mappings, a new polynomial time algorithm is provided that, unlike the algorithm of Gottlob and Nash from which it is inspired, does not rely on the syntactic property of Weak-Acyclicity. As the problem of deciding whether a Schema-mapping satisfies the TOC criterion is only recursively enumerable, a more restrictive criterion called Super-weak Acylicity (SwA) is identified that can be decided in Polynomial-time while generalizing substantially the notion of Weak-Acyclicity.