Frame-based ontological view for semantic integration

Semantic integration is crucial for successful collaboration between heterogeneous information systems in an open environment. Traditional ontology-driven approaches rely on the availability of explicit ontologies. However, in many domains, this prerequisite cannot be met. In order to address this issue, this paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to an ontological view concept. To explicitly and formally specify the ontological views, a Frame-based Ontological view Specification Language (FOSL) is proposed. This language is based on the Frame knowledge representation paradigm and uses XML as the encoding. A prototype environment that supports semantic integration based on ontological views specified with FOSL is introduced.

PurposeThe purpose of this paper is to explore useful Semantic Web technologies and ontology-based applications for digital libraries. It also investigates the perceptions of university librarians and academicians in Pakistan about Semantic Web technologies and their use in digital libraries.Design/methodology/approachAn exploratory research design based on Delphi research strategy was conducted to answer the research questions. Interviews were conducted with a purposive sample of 50 key informants including university librarians and academicians to explore their perceptions about Semantic Web technologies and their use in digital libraries. Thematic analysis of interview data was conducted to obtain results.FindingsThe results of this paper showed that DuraCloud, Semantic information mashup, OntoEdit and resource description framework (RDF) are the various Semantic Web applications which are useful for digital libraries to develop semantic relationships among digital contents and increase their accessibility in the web environment. Findings revealed that Semantic Web provides precise results and meets user information needs in an effective way. Results also showed that next-generation digital libraries use context-awareness technology, intelligent agent software and detecting sensors to analyze user information needs and provide dynamic information services. This paper recommended that librarians should embrace the use of emerging web technologies in libraries and offer library services through the medium of the web.Practical implicationsThis paper envisaged the future of digital library services and Semantic Web applications that can be used to re-structure metadata of digital library. This paper has practical implications for librarians to consider the useful applications of Semantic Web for digital library and enhance the interoperability of metadata among heterogeneous information systems. Practically, results obtained from this paper are highly useful for library schools and LIS teachers to up-date their curriculum by incorporating new contents related to web languages and Semantic Web applications for digital libraries.Originality/valueThis paper identifies various Semantic Web applications which are useful for developing Semantic Digital Libraries.

One fundamental issue for semantic web application is how to define the mapping between relational model and RDF model, so that the legacy data in relational databases can be integrated into semantic web. In this paper, we propose an view-based approach to mediate relational schema using RDF-based ontology. We formally define the Ontology View, and precisely define the semantics of answering queries using ontology view. With our approach, we highlight the important role played by RDF Blank Node in defining semantic mappings and representing the incomplete part of relational schema.

This paper presents a novel ontological view-based semantic transformation method to address the semantic heterogeneity design issue of open distributed information systems. After carefully reviewing the traditional ontology definitions, this work extends the ontological view concept to represent the partial knowledge about the same business domain in an open environment where common ontology does not exist or is not explicitly represented. Solutions in mathematical formulation and corresponding application algorithms, based on the definition of an ontological view, are proposed. By dealing with structural constant and predicate heterogeneity, respectively, the solution enables the ontological views to be transformed, one to another, automatically.

The emergence of Semantic Web (SW) and the related technologies promise to make the Web a meaningful experience. Conversely, success of SW and its applications depends largely on utilization and interoperability of well-formulated ontology bases in an automated heterogeneous environment. This creates a need to investigate utilization of an (materialized) ontology view as an alternative version of an ontology. However, high level modeling, design and querying techniques still proves to be a challenging task for SW paradigm, as, unlike classical database systems, ontology view definitions and querying have to be done at high-level abstraction. In order to address such an issue, in this chapter, we describe an abstract view formalism forSW (SW-view) with conceptual and logical extensions. SW-views provides the needed conceptual and logical semantics to engineer ontology bases using three levels of abstraction, namely (1) conceptual, (2) logical/schema and (3) instance levels. We first provide the view model and it formal properties including a set of conceptual operators, which enable us to do ontology extraction at the conceptual level. Later, we provide a schemata transformation methodology to materialize SW-views under the Ontology Extraction Methodology (OEM) framework.

One important research challenge of current Semantic Web is resolving the interoperability issue across ontologies. The issue is directly related to identifying semantics of resources residing in different domain ontologies. That is, the semantics of a concept in an ontology differs from others according to the modeling style and intuition of the knowledge expert even though they are the same forms of a concept in each respective ontology. In this paper, we propose a similarity measure to resolve the interoperability issue by using a similarity graph. The strong point of this paper is that we provide a precise mapping technique and similarity properties to derive the similarity. The novel contribution of this paper is that we provide a core technique of computing similarity across ontologies of Semantic Web.

An article tries to see a group of semantic web representation and communication means like description logics, semantic networks, RDF model and language, OWL language, RDF CFL etc. taking a part at the development of formal ontologies from a slightly higher (meta) level. A focus has been oriented towards properties that semantic web language ought to have to fulfill according to a semantic web idea. Consequently the article tries to draw by the help of the means above the trip towards a proper semantic-web ontology language fulfilling the main demands of expressivity and also easy-to-use conditions. Even if the development of a semantic web language was until now much more complicated with a taking part of a lot of people or companies the authors of the article try to contribute to an analyzing of the actual state by drawing it as a cloud of demands, streams, events or condition’s fulfilling that at the end would have brought into the world an easy-to-usable semantic web ontology language having all the demands fulfilled. The article moreover shows that a language RDF CFL belongs nowadays to the semantic web family as a unique well usable tool of reasoning within semantic web knowledge bases.

Web Ontology Language (OWL), Semantic Web Rule Language (SWRL) and Model-Driven Engineering (MDE) are technologies being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far stressed this problem and have proposed several solutions. The result of these efforts is the recent OMG’s initiative for defining an ontology development platform. However, the problem of transformation between Semantic Web ontology and rule languages and MDE-based languages has been solved using rather partial and ad hoc solutions, most often by XSLT. In this paper, we relations between the Semantic Web languages and MDE-compliant languages as separate technical spaces. In order to achieve a synergy between these technical spaces, we present ontology and rule languages in terms of MDE standards, recognize relations between the OWL and SWRL langauges and MDE-based ontology languages, and propose mapping techniques. In order to illustrate the approach, we use an MDE-defined architecture that includes the ontology and rule metamodels and ontology UML Profile. We also show how MDE techniques, such as model transformations, can be used to enable sharing rules and ontologies by using REWERSE Rule Markup Language (R2ML), a proposal for a general rule language. The main benefit of this approach is that it keeps the focus on the language concepts (i.e., languages’ abstract syntax - metamodels) rather than on technical issues caused by different concrete syntax. Yet, we also provide transformations that bridge between both languages’ concrete (XML) and abstract (MOF) syntax.

Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

The capability to provide a platform for flexible business services in the Air Traffic Management (ATM) domain is both a major success factor for the ATM industry and a challenge to integrate a large number of complex and heterogeneous information systems. Most of the system knowledge needed for integration is not available explicitly in machine-understandable form, resulting in time-consuming and error-prone human tasks.In this paper we propose a knowledge-based ap-proach, Semantically-Enabled Externalization of Knowledge for the ATM domain (SEEK-ATM), which explicitly models a) expert knowledge on specific heterogeneous systems and integration requirements; and b) allows mapping of the specific knowledge to the general ATM problem domain knowledge for semantic integration. The domain-specific modeling enables a) to verify the integration knowledge base as requirements specification for later design of technical systems integration and b) to provide an API to the prob-lem space knowledge to facilitate tool support for efficient and effective systems integration. Based on an industry case study, we evaluate effects of the proposed SEEK-ATM approach in comparison to traditional system integration approaches in the ATM domain.

The Semantic Web is based on technologies that make the content of the Web machine-understandable. In that framework, ontological knowledge representation has become an important tool for the analysis and understanding of multimedia information. Because of the distributed nature of the Semantic Web however, ontologies describing similar fields of knowledge are being developed and the data coming from similar but non-identical ontologies can be combined only if a semantic mapping between them is first established. This has lead to the development of several ontology alignment tools. We propose an automatic ontology alignment method based on the recursive neural network model that uses ontology instances to learn similarities between ontology concepts. Recursive neural networks are an extension of common neural networks, designed to process efficiently structured data. Since ontologies are a structured data representation, the model is inherently suitable for use with ontologies.

The Ontology is increasingly important for many information systems and Semantic Web, while the cost of constructing ontology is too much. In this paper, we propose an automatic approach for ontology construction to assist the knowledge engineers to construct the specific domain ontology from the documents, which are gathered from Internet. We hope to raise the automation level to make correctly and efficiently build the ontology while applying the method to different domains. For different domains, we propose an approach to extract new Chinese terms from the specific corpus automatically. And we use information retrieval, natural language processing, and soft computing techniques to find out the concepts of the ontology. In addition, we extend the concept of episode to construct an Episode Net. Using Episode Net, we can find out the static attributes, dynamic operations, and the associations between concepts of the ontology. Finally, we use object-oriented model to represent the ontology and then construct the ontology with four-layer object-oriented structure. The experimental results show that our approach can effectively assist ontology engineers to construct the domain ontology.

Many companies have been forced to quickly respond to changing user needs. To provide more convenient services to consumers, the cooperation within a company or across companies have been requested. As a result, the heterogeneous information systems are also requested to be integrated together. By utilizing the heterogeneity among systems and by cooperating between systems, it becomes possible to draw out new values from them without violating each system's characteristic. In the heterogeneous systems, such as the data generation timings or frequencies are different, the data synchronization itself should be done by each system without relying on the single coordinator, because the system configurations are always changing, and members of application group which use synchronous data combination are also changing. In this paper we propose the autonomous data synchronization technique in the heterogeneous systems. The application objects which requires the synchronous combination of the data in each system can locally judge which combination of data is most adequate as the synchronous combination by comparing the synchronous information with others. Thus all systems can use the consistent combination as the synchronous data only by collecting the data locally and exchanging the synchronous information. In addition, the cost of synchronization in each system, which is measured by the synchronization waiting time (SWT) and backward data utilization (BDU) becomes even. As this proposed method is not relying on the single coordinator, it works correctly even if the system configuration is dynamically changed, or even if members of SyncApps are changed. The simulation results show the cost fairness when three systems are interconnected in straight line.

In the era of big data, multimedia, hyper-media and social networks are emerging, and the amount of information is growing rapidly. When people participate in the process of massive data processing, they will encounter data with different structures, so data has heterogeneity. How to acquire hidden and valuable knowledge from heterogeneous data and measure its uncertainty is an important problem in artificial intelligence. This paper investigates uncertainty measurement for heterogeneous data and gives its application in attribute reduction. The concept of a heterogeneous information system (HIS) is first proposed. Then, an equivalence relation on the object set is constructed. Next, uncertainty measurement for a HIS is investigated, a numerical experiment is given, and dispersion analysis, correlation analysis, and Friedman test and Bonferroni–Dunn test in statistics are conducted. Finally, as an application of the proposed measures, attribute reduction in a HIS is studied, and the corresponding algorithms and their analysis are proposed.

Metadata is defined as data about data. In large scale distributed and heterogeneous software systems, metadata is considered as one of the most important components for the architecture and construction of information systems. Metadata is utilized to improve communication between heterogeneous information systems – for the purposes of obtaining and providing information, for communication between user client workstations and information servers, and for electronic business between information systems. Metadata management is much challenging and is a hot topic for research at present. In this paper, we review work that deals with effective indexed data for mobile service management metadata in three different points of view. Firstly, we survey some proposals about applying model management to classical metadata problems. Then we inspect how metadata can help managing multimedia data. Finally, we review some mobile service specific metadata management issues. We survey approaches that are of foundational nature as well as those that are application-oriented. We believe that combining both foundational and practical aspects is important to achieve the goal of managing metadata with the same ease as, for example, database management systems have achieved in the management of classical relational data.