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.     

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.     

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。     

Measuring design complexity of semantic web ontologies

Ontology languages such as OWL are being widely used as the Semantic Web movement gains momentum. With the proliferation of the Semantic Web, more and more large-scale ontologies are being developed in real-world applications to represent and integrate knowledge and data. There is an increasing need for measuring the complexity of these ontologies in order for people to better understand, maintain, reuse and integrate them. In this paper, inspired by the concept of software metrics, we propose a suite of ontology metrics, at both the ontology-level and class-level, to measure the design complexity of ontologies. The proposed metrics are analytically evaluated against Weyuker’s criteria. We have also performed empirical analysis on public domain ontologies to show the characteristics and usefulness of the metrics. We point out possible applications of the proposed metrics to ontology quality control. We believe that the proposed metric suite is useful for managing ontology development projects.     

Towards an algebraic theory of information integration

Information integration systems provide uniform interfaces to varieties of heterogeneous information sources. For query answering in such systems, the current generation of query answering algorithms in local-as-view (source-centric) information integration systems all produce what has been thought of as “the best obtainable” answer, given the circumstances that the source-centric approach introduces incomplete information into the virtual global relations. However, this “best obtainable” answer does not include all information that can be extracted from the sources because it does not allow partial information. Neither does the “best obtainable” answer allow for composition of queries, meaning that querying a result of a previous query will not be equivalentto the composition of the two queries. In this paper, we provide a foundation for information integration, based on the algebraic theory of incomplete information. Our framework allows us to define the semantics of partial facts and introduce the notion of the exact answer—that is the answer that includes partial facts. We show that querying under the exact answer semantics is compositional. We also present two methods for actually computing the exact answer. The first method is tableau-based, and it is a generalization of the “inverse-rules” approach. The second, much more efficient method, is a generalization of the rewriting approach, and it is based on partial containment mappings introduced in the paper.     

Feature-based ontological framework for semantic interoperability in product development

An essential requirement in integrating tasks in product development is to have a seamless exchange of product information through the entire product lifecycle. A key challenge in the integration is the exchange of shape semantics in terms of understandable labels and representations. A unified taxonomy is proposed to represent, classify, and extract shape features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model as the representation of features. All the shape features in a product model are classified under three main classes, namely, volumetric features, deformation features and free-form surface features. Shape feature ontology is developed using the unified taxonomy, which brings the shape features under a single reasoning framework. One-to-many reasoning framework is presented for mapping semantically equivalent information (label and representation) of the feature to be exchanged to target applications, and the reconstruction of the shape model automatically in that target application. An algorithm has been developed to extract the semantics of shape features and construct the model in the target application. The algorithm developed has been tested for shape models taken from literature and test cases are selected based on variations of topology and geometry. Results of exchanging product information are presented and discussed. Finally, the limitations of the proposed method for exchanging product information are explained.     

Semantic information alignment of BIMs to computer-interpretable regulations using ontologies and deep learning

A semantic information alignment method is proposed to align the representations used in building information models (BIMs) to the representations used in energy regulations. Compared to existing alignment efforts, which are either manual or semi-automated, the proposed method aims to automate the alignment process for supporting fully automated energy compliance checking. A first-level simple alignment method is proposed to align single design information instances to single regulatory concepts, in which (1) domain knowledge is used for interpreting the meaning of concepts to recognize candidate instances, and (2) deep learning is used for capturing the semantics behind the words to measure semantic similarity and select the matches. A final complex alignment method is proposed to recognize the instance groups belonging to a regulatory requirement, in which (1) supervised and unsupervised searching algorithms are used to identify the instance pairs, and (2) network modeling is used to group and link the instance pairs to the requirement. The proposed method showed 93.4% recall and 94.7% precision on the testing data.     

Aondê: An ontology Web service for interoperability across biodiversity applications

Biodiversity research requires associating data about living beings and their habitats, constructing sophisticated models and correlating all kinds of information. Data handled are inherently heterogeneous, being provided by distinct (and distributed) research groups, which collect these data using different vocabularies, assumptions, methodologies and goals, and under varying spatio-temporal frames. Ontologies are being adopted as one of the means to alleviate these heterogeneity problems, thus helping cooperation among researchers. While ontology toolkits offer a wide range of operations, they are self-contained and cannot be accessed by external applications. Thus, the many proposals for adopting ontologies to enhance interoperability in application development are either based on the use of ontology servers or of ontology frameworks. The latter support many functions, but impose application recoding whenever ontologies change, whereas the first supports ontology evolution, but for a limited set of functions.This paper presents Aondê—a Web service geared towards the biodiversity domain that combines the advantages of frameworks and servers, supporting ontology sharing and management on the Web. By clearly separating storage concerns from semantic issues, the service provides independence between ontology evolution and the applications that need them. The service provides a wide range of basic operations to create, store, manage, analyze and integrate multiple ontologies. These operations can be repeatedly invoked by client applications to construct more complex manipulations. Aondê has been validated for real biodiversity case studies.     

Reusing ontology mappings for query routing in semantic peer-to-peer environment

To efficiently support automated interoperability between ontology-based information systems in distributed environments, the semantic heterogeneity problem has to be dealt with. To do so, traditional approaches have acquired and employed explicit mappings between the corresponding ontologies. Usually these mappings can be only obtained from human domain experts. However, it is too expensive and time-consuming to collect all possible mapping results on distributed information systems. More seriously, as the number of systems in a large-scale peer-to-peer (P2P) network increases, the efficiency of the ontology mapping is exponentially decreased. Thereby, in this paper, we propose a novel semantic P2P system, which is capable of (i) sharing and exchanging existing mappings among peers, and (ii) composing shared mappings to build a certain path between two systems. Given two arbitrary peers (i.e., source and destination), the proposed system can provide indirect ontology mappings to make them interoperable. In particular, we have focused on query-based communication for evaluating the proposed ontology mapping composition system. Once direct ontology mappings are collected from candidate peers, a given query can be (i) segmented into a set of sub-queries, and (ii) transformed to another query. With respect to the precision performance, our experimentation has shown an improvement of about 42.5% compared to the keyword-based query searching method.     

A RESTful and semantic framework for data integration

Companies have to deal with huge amounts of heterogeneous information, usually stored in distributed datasets that make use of different data schemas. This topic is especially crucial for enterprises that deal with new and different kinds of business data as new services are provided; they need to be able to dynamically add new datasets with new schemas to their information systems. However, even though research efforts have been applied to deal with this integration problem, there is still a lack of practical approaches ready to be implemented for industrial cases. We present a web‐based architecture and system built upon ontologies and other semantic web techniques to cope with federation of business data in real time. The scenario used to demonstrate the utility of the architecture is composed of actual data of a telecom company. Results show that our solution is more suitable, efficient and practical than other works. Copyright © 2014 John Wiley & Sons, Ltd.     

A semantic interoperability framework for software as a service systems in cloud computing environments

In cloud computing environments in software as a service (SaaS) level, interoperability refers to the ability of SaaS systems on one cloud provider to communicate with SaaS systems on another cloud provider. One of the most important barriers to the adoption of SaaS systems in cloud computing environments is interoperability. A common tactic for enabling interoperability is the use of an interoperability framework or model. During the past few years, in cloud SaaS level, various interoperability frameworks and models have been developed to provide interoperability between systems. The syntactic interoperability of SaaS systems have already been intensively researched. However, not enough consideration has been given to semantic interoperability issues. Achieving semantic interoperability is a challenge within the world of SaaS in cloud computing environments. Therefore, a semantic interoperability framework for SaaS systems in cloud computing environments is needed. We develop a semantic interoperability framework for cloud SaaS systems. The capabilities and value of service oriented architecture for semantic interoperability within cloud SaaS systems have been studied and demonstrated. This paper is accomplished through a number of steps (research methodology). It begins with a study on related works in the literature. Then, problem statement and research objectives are explained. In the next step, semantic interoperability requirements for SaaS systems in cloud computing environments that are needed to support are analyzed. The details of the proposed semantic interoperability framework for SaaS systems in cloud computing environments are presented. It includes the design of the proposed semantic interoperability framework. Finally, the evaluation methods of the semantic interoperability framework are elaborated. In order to evaluate the effectiveness of the proposed semantic interoperability framework for SaaS systems in cloud computing environments, extensive experimentation and statistical analysis have been performed. The experiments and statistical analysis specify that the proposed semantic interoperability framework for cloud SaaS systems is able to establish semantic interoperability between cloud SaaS systems in a more efficient way. It is concluded that using the proposed framework, there is a significant improvement in the effectiveness of semantic interoperability of SaaS systems in cloud computing environments.     

Axiomatizing the Logical Core of XPath 2.0

The first aim of this paper is to present the logical core of XPath 2.0: a logically clean, decidable fragment, which includes most navigational features of XPath 2.0 (complex counting conditions and data joins are not supported, as they lead to undecidability). The second aim is to provide a list of equations completely axiomatizing query equivalence in this language (i.e., all other query equivalences can be derived from these). A preliminary version of this paper was published in the proceedings of ICDT 2007. We would like to thank Jan Hidders for pointing us to the interesting question of stronger forms of completeness (cf. Sect. 4.3). We would also like to thank the anonymous reviewers for their extensive comments, which have greatly improved the quality of the paper. The first author is supported by NWO grant 639.021.508.     

A methodology for the semi-automatic creation of data-driven detailed business ontologies

In the context of technological expansion and development, companies feel the need to renew and optimize their information systems as they search for the best way to manage knowledge. Business ontologies within the semantic web are an excellent tool for managing knowledge within this space. The proposal in this article consists of a methodology for integrating information in companies. The application of this methodology results in the creation of a specific business ontology capable of semantic interoperability. The resulting ontology, developed from the information system of specific companies, represents the fundamental business concepts, thus making it a highly appropriate information integration tool. Its level of semantic expressivity improves on that of its own sources, and its solidity and consistency are guaranteed by means of checking by current reasoning tools. An ontology created in this way could drive the renewal processes of companies’ information systems. A comparison is also made with a number of well-known business ontologies, and similarities and differences are drawn, highlighting the difficulty in aligning general ontologies to specific ones, such as the one we present.     

A labeled-tree approach to semantic and structural data interoperability applied in hydrology domain

The issues of data integration and interoperability pose significant challenges in scientific hydrological and environmental studies, due largely to the inherent semantic and structural heterogeneities of massive datasets and non-uniform autonomous data sources. To address these data integration challenges, we propose a unified data integration framework, called Hydrological Integrated Data Environment (HIDE). HIDE is based on a labeled-tree data integration model referred to as DataNode tree. Using this framework, characteristics of datasets gathered from diverse data sources - with different logical and access organizations - can be extracted and classified as Time-Space-Attribute (TSA) labels and are subsequently arranged in a DataNode tree. The uniqueness of our approach is that it effectively combines the semantic aspects of the scientific domain with diverse datasets having different logical organizations to form a unified view. Further, we also adopt a metadata-based approach for specifying the TSA-DataNode tree in order to achieve flexibility and extensibility. The search engine of our HIDE prototype system evaluates a simple user query systematically on the TSA-DataNode tree, presenting integrated results in a standardized format that facilitates both effective and efficient data integration.     

Building a global normalized ontology for integrating geographic data sources

Nowadays, the proliferation of geographic information systems has caused great interest in integration. However, an integration process is not as simple as joining several systems, since any effort at information sharing runs into the problem of semantic heterogeneity, which requires the identification and representation of all semantics useful in performing schema integration. On several research lines, including research on geographic information system integration, ontologies have been introduced to facilitate knowledge sharing among various agents. Particularly, one of the aspects of ontology sharing is performing some sort of mapping between ontology constructs. Further, some research suggests that we should also be able to combine ontologies where the product of this combination will be, at the very least, the intersection of the two given ontologies. However, few approaches built integrations upon standard and normalized information, which might improve accuracy of mappings and therefore commitment and understandability of the integration. In this work, we propose a novel system (called GeoMergeP) to integrate geographic sources by formalizing their information as normalized ontologies. Our integral merging process—including structural, syntactic and semantic aspects—assists users in finding the more suitable correspondences. The system has been empirically tested in the context of projects of the Italian Institute for Environmental Protection and Research (ISPRA, ex APAT), providing a consistent and complete integration of their sources.     

Towards ubiquitous tourist service coordination and process integration: A collaborative travel agent system architecture with semantic web services

With the recent advances in Internet and mobile technologies, there are increasing demands for ubiquitous access to tourist information systems for service coordination and process integration. However, due to disparate tourist information and service resources such as airlines, hotels, tour operators, it is still difficult for tourists to use them effectively during their trips or even in the planning stage. Neither can current tourist portals assist tourists proactively. To overcome this problem, we propose a Collaborative Travel Agent System (CTAS) based on a scalable, flexible, and intelligent Multi-Agent Information System (MAIS) architecture for proactive aids to Internet and mobile users. We also employ Semantic Web technologies for effective organization of information resources and service processes. We formulate our MAIS architecture for CTAS further with agent clusters based on a case study of a large service-oriented travel agency. Agent clusters may comprise several types of agents to achieve the goals involved in the major processes of a tourist’s trip. We show how agents can make use of ontology from the Semantic Web to help tourists better plan, understand, and specify their requirements collaboratively with the CTAS. We further illustrate how this can be successfully implemented with Web service technologies to integrate disparate Internet tourist resources. To conclude, we discuss and evaluate our approach from different stakeholders’ perspectives.

Towards a framework for governance architecture management in cloud environments: A semantic perspective

This article introduces a model for cloud governance with a specific focus on its semantic aspects. It considers three dominant paradigms — the business–IT alignment paradigm, the governance paradigm, and the cloud paradigm. The model can be enhanced with specific tools to serve as a holistic framework for addressing governance of both traditional and cloud-based IT environments. The proposed consideration of semantic aspects within the model can enable a more feasible application of the model in complex architectural settings — both from the point of view of architecture assessment and architecture management.