Graph-based query rewriting for knowledge sharing between peer ontologies

Peer knowledge management systems (PKMS) offer a flexible architecture for decentralized knowledge sharing. In PKMSs, the knowledge sharing and evolution processes are based on peer ontologies. Finding an effective and efficient query rewriting algorithm for regular expression queries is vital for knowledge sharing between peers in PKMSs; and for this our solution is characterized by graph-based query rewriting. Based on the graphs for both axioms and mappings, we design a novel algorithm, regular expression rewriting algorithm, to rewrite regular expression queries along semantic paths. The simulation results show that the performance of our algorithm is better than Mork’s reformulation algorithms [P. Mork, Peer architectures for knowledge sharing, PhD thesis, University of Washington, 2005. <http://www.mitre.org/staffpages/pmork/>], and our algorithm is more effective than the naive rewriting algorithm.     

An XML query rewriting mechanism with multiple ontologies integration based on complex semantic mapping

Semantic integration, which can be divided into three parts including ontology mapping, mapping representation, and reasoning and query rewriting with mappings, plays a key role in information integration systems. This paper develops an XML query rewriting and ontology integration mechanism, which acts as a global-as-view (GAV) approach to represent and query semantic information in mediator based information integration environment. It proposes the patterns and properties of ontology mappings, discusses the procedure and algorithm of ontology integration firstly, and then proposes the ontology based XML query mechanism, especially the XML query rewriting mechanism. Finally, a mediator-based implementation of the mechanism in OBSA system is introduced.     

Contextual alignment of ontologies in the eCOIN semantic interoperability framework

The prospect of combining information from diverse sources for superior decision making is plagued by the challenge of semantic heterogeneity, as data sources often adopt different conventions and interpretations when there is no coordination. An emerging solution in information integration is to develop an ontology as a standard data model for a domain of interest, and then to define the correspondences between the data sources and this common model to eliminate their semantic heterogeneity and produce a single integrated view of the data sources. We first claim that this single integrated view approach is unnecessarily restrictive, and instead offer the view that ontologies can simultaneously accommodate multiple integrated views provided the accompaniment of contexts, a set of axioms on the interpretation of data allowing local variations in representation and nuances in meaning, and a conversion function network between contexts to reconcile contextual differences. Then, we illustrate how to achieve semantic interoperability between multiple ontology-based applications. During this process, application ontologies are aligned through the reconciliation of their context models, and a new application with a virtual merged ontology is created. We illustrate this alternative approach with the alignment of air travel and car rental domains, an actual example from our prototype implementation.

SPARQL graph pattern rewriting for OWL-DL inference queries

This paper focuses on the issue of OWL-DL ontology queries implemented in SPARQL. Currently, ontology repositories construct inference ontology models, and match SPARQL queries to the models, to derive inference results. Because an inference model uses much more storage space than the original model, and cannot be reused as inference requirements vary, this method is not suitable for large-scale deployment. To solve this problem, this paper proposes a novel method that passes rewritten SPARQL queries to the original ontology model, to retrieve inference results. We define OWL-DL inference rules and apply them to rewriting Graph Patterns in queries. The paper classifies the inference rules and discusses how these rules affect query rewriting. To illustrate the advantages of our proposal, we present a prototype system based on Jena, and address query optimization, to eliminate the disadvantages of augmented query sentences. We perform a set of query tests and compare the results with related works. The results show that the proposed method results in significantly improved query efficiency, without compromising completeness or soundness.

Determinacy and query rewriting for conjunctive queries and views

Answering queries using views is the problem which examines how to derive the answers to a query when we only have the answers to a set of views. Constructing rewritings is a widely studied technique to derive those answers. In this paper we consider the problem of the existence of rewritings in the case where the answers to the views uniquely determine the answers to the query. Specifically, we say that a view set Vdetermines a query Q if for any two databases D₁,D₂ it holds: V(D₁)=V(D₂) implies Q(D₁)=Q(D₂). We consider the case where query and views are defined by conjunctive queries and investigate the question: If a view set V determines a query Q, is there an equivalent rewriting of Q using V? We present here interesting cases where there are such rewritings in the language of conjunctive queries. Interestingly, we identify a class of conjunctive queries, CQ_path, for which a view set can produce equivalent rewritings for “almost all” queries which are determined by this view set. We introduce a problem which relates determinacy to query equivalence. We show that there are cases where restricted results can carry over to broader classes of queries.     

View-based query processing: On the relationship between rewriting,answering and losslessness

As a result of the extensive research in view-based query processing, three notions have been identified as fundamental, namely rewriting, answering, and losslessness. Answering amounts to computing the tuples satisfying the query in all databases consistent with the views. Rewriting consists in first reformulating the query in terms of the views and then evaluating the rewriting over the view extensions. Losslessness holds if we can answer the query by solely relying on the content of the views. While the mutual relationship between these three notions is easy to identify in the case of conjunctive queries, the terrain of notions gets considerably more complicated going beyond such a query class. In this paper, we revisit the notions of answering, rewriting, and losslessness and clarify their relationship in the setting of semistructured databases, and in particular for the basic query class in this setting, i.e., two-way regular path queries. Our first result is a clean explanation of the relationship between answering and rewriting, in which we characterize rewriting as a “linear approximation” of query answering. We show that applying this linear approximation to the constraint-satisfaction framework yields an elegant automata-theoretic approach to query rewriting. As for losslessness, we show that there are indeed two distinct interpretations for this notion, namely with respect to answering, and with respect to rewriting. We also show that the constraint-theoretic approach and the automata-theoretic approach can be combined to give algorithmic characterization of the various facets of losslessness. Finally, we deal with the problem of coping with loss, by considering mechanisms aimed at explaining lossiness to the user.     

A semantic metrics suite for evaluating modular ontologies

Ontologies, which are formal representations of knowledge within a domain, can be used for designing and sharing conceptual models of enterprises information for the purpose of enhancing understanding, communication and interoperability. For representing a body of knowledge, different ontologies may be designed. Recently, designing ontologies in a modular manner has emerged for achieving better reasoning performance, more efficient ontology management and change handling. One of the important challenges in the employment of ontologies and modular ontologies in modeling information within enterprises is the evaluation of the suitability of an ontology for a domain and the performance of inference operations over it. In this paper, we present a set of semantic metrics for evaluating ontologies and modular ontologies. These metrics measure cohesion and coupling of ontologies, which are two important notions in the process of assessing ontologies for enterprise modeling. The proposed metrics are based on semantic-based definitions of relativeness, and dependencies between local symbols, and also between local and external symbols of ontologies. Based on these semantic definitions, not only the explicitly asserted knowledge in ontologies but also the implied knowledge, which is derived through inference, is considered for the sake of ontology assessment. We present several empirical case studies for investigating the correlation between the proposed metrics and reasoning performance, which is an important issue in applicability of employing ontologies in real-world information systems.     

Extracting a justification for OWL ontologies by critical axioms

Extracting justifications for web ontology language (OWL) ontologies is an important mission in ontology engineering. In this paper, we focus on black-box techniques which are based on ontology reasoners. Through creating a recursive expansion procedure, all elements which are called critical axioms in the justification are explored one by one. In this detection procedure, an axiom selection function is used to avoid testing irrelevant axioms. In addition, an incremental reasoning procedure has been proposed in order to substitute series of standard reasoning tests w.r.t. satisfiability. It is implemented by employing a pseudo model to detect “obvious” satisfiability directly. The experimental results show that our proposed strategy for extracting justifications for OWL ontologies by adopting incremental expansion is superior to traditional Black-box methods in terms of efficiency and performance.     

Combining OWL ontologies using -Connections

The standardization of the Web Ontology Language (OWL) leaves (at least) two crucial issues for Web-based ontologies unsatisfactorily resolved, namely how to represent and reason with multiple distinct, but linked ontologies, and how to enable effective knowledge reuse and sharing on the Semantic Web.In this paper, we present a solution for these fundamental problems based on -Connections. We aim to use -Connections to provide modelers with suitable means for developing Web ontologies in a modular way and to provide an alternative to the owl:imports construct.With such motivation, we present in this paper a syntactic and semantic extension of the Web Ontology language that covers -Connections of OWL-DL ontologies. We show how to use such an extension as an alternative to the owl:imports construct in many modeling situations. We investigate different combinations of the logics , and for which it is possible to design and implement reasoning algorithms, well-suited for optimization.Finally, we provide support for -Connections in both an ontology editor, SWOOP, and an OWL reasoner, Pellet.     

Web本体语言OWL

随着对语义Web研究的深入,人们越来越关注在Web上信息内容的表示和检索问题。在语义Web的七层模型中,建立在RDF模式层之上的本体语言层用于形式化描述Web文档中词汇的含义,是建立语义Web的关键环节。该文介绍了W3C最新给出的Web本体语言OWL,给出TOWL3个子语言构造成分的含义说明,并比较了3种子语言间的差别。     

GrOWL: A tool for visualization and editing of OWL ontologies

In an effort to optimize visualization and editing of OWL ontologies we have developed GrOWL—a browser and visual editor for OWL that accurately visualizes the underlying DL semantics of OWL ontologies while avoiding the difficulties of the verbose OWL syntax. In this paper, we discuss GrOWL visualization model and the essential visualization techniques implemented in GrOWL.     

OntoTrack: A semantic approach for ontology authoring

OntoTrackis an ontology authoring tool that combines a graph-based hierarchical layout and instant reasoning feedback within one single view. Currently OntoTrack can handle ontologies with an expressivity almost comparable to OWL Lite. The graphical representation provides an animated and zoomable subsumption graph with context sensitive features such as click-able miniature branches or selective detail views, together with drag-and-drop editing. Each editing step is instantly synchronised with an external reasoner in order to provide appropriate graphical feedback about relevant modeling consequences. A recent extention of OntoTrack provides an on-demand textual explanation for subsumption relationships between classes. This paper describes the key features of the current implementation and discusses future work, as well as some development issues. OntoTrack can be downloaded at http://www.informatik.uni-ulm.de/ki/ontotrack/.     

Using provenance to debug changing ontologies

On the Semantic Web ontologies evolve and are managed in a distributed setting, e.g. in biomedical databases. Changes are contributed by multiple persons or organizations at various points in time. Often, changes differ by certainty or trustworthiness. When judging changes of automatically inferred knowledge and when debugging such evolving ontologies, the provenance of axioms (e.g. agent, trust degree and modification time) needs to be taken into account. Providing and reasoning with rich provenance data for expressive ontology languages, however, is a non-trivial task.In this paper we propose a formalization of provenance, which allows for the computation of provenance for inferences and inconsistencies. It allows us to answer questions such as “When has this inconsistency been introduced and who is responsible for this change?” as well as “Can I trust this inference?”.We propose a black box algorithm for reasoning with provenance, which is based on general pinpointing, and an optimization, which enables the use of provenance for debugging in real time even for very large and expressive ontologies, such as used in biomedical portals.     

基于本体的关系数据集成的查询处理

为实现异构关系数据库的语义集成,针对传统集成技术存在的问题,在对语义网等相关技术进行分析的基础上,研究基于本体的关系数据集成系统中的查询处理问题,提出了一种基于本体的关系数据库集成框架。设计了基于本体的关系数据的描述方法,使用本体作为集成的全局模式来描述关系模式的语义。设计了查询重写算法,该算法可以将基于全局模式的SPARQL查询重写为针对具体关系数据库的查询,从而实现对异构关系数据库的集成。实验表明,该算法具有良好的可扩展性。     

Finding an efficient rewriting of OLAP queries using materialized views in data warehouses

OLAP queries involve a lot of aggregations on a large amount of data in data warehouses. To process expensive OLAP queries efficiently, we propose a new method to rewrite a given OLAP query using various kinds of materialized views which already exist in data warehouses. We first define the normal forms of OLAP queries and materialized views based on the selection and aggregation granularities, which are derived from the lattice of dimension hierarchies. Conditions for usability of materialized views in rewriting a given query are specified by relationships between the components of their normal forms. We present a rewriting algorithm for OLAP queries that can effectively utilize materialized views having different selection granularities, selection regions, and aggregation granularities together. We also propose an algorithm to find a set of materialized views that results in a rewritten query which can be executed efficiently. We show the effectiveness and performance of the algorithm experimentally.