Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Combining open and closed world reasoning for the semantic web

Dissertação para obtenção do Grau de Doutor em InformáticaOne important problem in the ongoing standardization of knowledge representation languages for the Semantic Web is combining open world ontology languages, such as the OWL-based ones, and closed world rule-based languages. The main difficulty of such a combination is that both formalisms are quite orthogonal w.r.t. expressiveness and how decidability is achieved. Combining non-monotonic rules and ontologies is thus a challenging task that requires careful balancing between expressiveness of the knowledge representation language and the computational complexity of reasoning. In this thesis, we will argue in favor of a combination of ontologies and nonmonotonic rules that tightly integrates the two formalisms involved, that has a computational complexity that is as low as possible, and that allows us to query for information instead of calculating the whole model. As our starting point we choose the mature approach of hybrid MKNF knowledge bases, which is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. We extend the two-valued framework of MKNF logics to a three-valued logics, and we propose a well-founded semantics for non-disjunctive hybrid MKNF knowledge bases. This new semantics promises to provide better efficiency of reasoning,and it is faithful w.r.t. the original two-valued MKNF semantics and compatible with both the OWL-based semantics and the traditional Well- Founded Semantics for logic programs. We provide an algorithm based on operators to compute the unique model, and we extend SLG resolution with tabling to a general framework that allows us to query a combination of non-monotonic rules and any given ontology language. Finally, we investigate concrete instances of that procedure w.r.t. three tractable ontology languages, namely the three description logics underlying the OWL 2 pro les.Fundação para a Ciência e Tecnologia - grant contract SFRH/BD/28745/200

Query Rewriting and Optimization for Ontological Databases

Ontological queries are evaluated against a knowledge base consisting of an extensional database and an ontology (i.e., a set of logical assertions and constraints which derive new intensional knowledge from the extensional database), rather than directly on the extensional database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper, we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent first-order query against the underlying extensional database. We present a novel query rewriting algorithm for rather general types of ontological constraints which is well-suited for practical implementations. In particular, we show how a conjunctive query against a knowledge base, expressed using linear and sticky existential rules, that is, members of the recently introduced Datalog+/- family of ontology languages, can be compiled into a union of conjunctive queries (UCQ) against the underlying database. Ontological query optimization, in this context, attempts to improve this rewriting process so to produce possibly small and cost-effective UCQ rewritings for an input query.Comment: arXiv admin note: text overlap with arXiv:1312.5914 by other author

Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

Integrating and querying linked datasets through ontological rules

The Web of Linked Open Data has developed from a few datasets in 2007 into a large data space containing billions of RDF triples published and stored in hundreds of independent datasets, so as to form the so called Linked Open Data Cloud. This information cloud, ranging over a wide set of data domains, poses a challenge when it comes to reconciling heterogeneous schemas or vocabularies adopted by data publishers. Motivated by this challenge, in this thesis was address the problem of integrating and querying multiple heterogeneous Linked Data sets through ontological rules. Firstly, we propose a formalisation of the notion of a peer-to-peer Linked Data integration system, where the mappings between peers comprise schema-level mappings and equality constraints between different IRIs; we call this formalism an RDF Peer System(RPS). We show that the semantics of the mappings preserve tractability of answering Basic Graph Pattern (BGP) SPARQL queries against the data stored in the RDF sources and the set of constraints given by the RPS mappings. Then, we address the problem of SPARQL query rewriting under RPSs and we show that it is not possible to rewrite an input BGP SPARQL query into a SPARQL 1.0 query under general RPSs, as the RPS peer mappings are not first-order-rewritable rules; this is a major drawback of general RPSs since data materialisation is required to exploit their full semantics. With the adoption of the more recent standard SPARQL 1.1 and its property paths we are able to extend the expressivity of the target language beyond first-order by including regular expressions in the body of the target SPARQL queries, that is, by expressing conjunctive two-way regular path queries (C2RPQs). Following this idea, in the second part of the thesis we step away from the language of RPSs to conduct a study on C2RPQ-rewritability under a broader ontology language. We define [ELHI`inh] (harmless linear ELHI), an ontology language that generalises both the DL-Lite[R] and linear ELH description logics. We prove the rewritability of instance queries (queries with a single atom in their body) under [ELHI`inh] knowledge bases with C2RPQs as the target language, presenting a query rewriting algorithm that makes use of non-deterministic finite-state automata. Following from that, we propose a query rewriting algorithm for answering conjunctive queries under [ELHI`inh] knowledge bases, with C2RPQs as the target language. Since C2RPQs can be straightforwardly expressed in SPARQL 1.1 by means of property paths, we believe that our approach is directly applicable to real-world querying settings. Lastly, we undertake a complexity analysis for query answering under [ELHI`inh]. We analyse the computational cost of query answering in terms of both data complexity (where the ontology and the query are fixed and the data alone is a variable input)and combined complexity (where query, ontology and data all constitute the variable input). We show that answering instance queries under [ELHI`inh] is NLogSpace-complete for data complexity and in PTime for combined complexity; we also show that answering CQs under [ELHI`inh] is NLogSpace-complete for data complexity and NP-complete for combined complexity

Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic