Published April 29, 2005 by Wiley .
Written in EnglishRead online
|Contributions||Vladimir Alexiev (Editor), Michael Breu (Editor), Jos de Bruijn (Editor), Dieter Fensel (Editor), Ruben Lara (Editor), Holger Lausen (Editor)|
|The Physical Object|
|Number of Pages||196|
Download Information Integration with Ontologies
Information Integration with Ontologies will be of interest to IT technicians needing advice and examples on the successful integration of heterogeneous information and the application of ontology technology.
It will also appeal to technical decision makers involved in real-world applications.4/5(1). Get this from a library.
Information integration with ontologies: experiences from an industrial showcase. [Vladimir Alexiev;] -- "Information Integration with Ontologies will be of interest to IT technicians needing advice and examples on the successful integration of heterogeneous information and the.
Overview. What ontologies in both information science and philosophy have in common is the attempt to represent entities, ideas and events, with all their interdependent properties and relations, according to a system of categories.
In both fields, there is considerable work on problems of ontology engineering (e.g., Quine and Kripke in philosophy, Sowa and Guarino in computer science), and. Ontology-based data integration involves the use of ontology(s) to effectively combine data or information from multiple heterogeneous sources.
It is one of the multiple data integration approaches and may be classified as Global-As-View (GAV). The effectiveness of ontology based data integration is closely tied to the consistency and expressivity of the ontology used in the integration process.
Ontologies. Ontologies, in the sense of formal semantic theories for datasets (not the sense of academic philosophy), are increasingly being proposed, and even used, to support the integration of information that is stored in heterogeneous formats, especially in connection with the world wide web, but also for other, less chaotic, forms of distributed database.
Lambrix P., Strömbäck L., Tan H. () Information Integration in Bioinformatics with Ontologies and Standards. In: Bry F., Małuszyński J. (eds) Semantic Techniques for the Web. Lecture Notes in Computer Science, vol Cited by: What are Ontologies. An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them.
To enable such a description, we need to formally specify components such as individuals (instances of objects), classes, attributes and relations as well as restrictions, rules and axioms.
3 Ontologies for Data Integration Ontologies have been extensively used in data integration systems because they provide an explicit and machine-understandable conceptualization of a domain. They have been used in one of the three following ways : Single ontology approach.
All source schemas are directly related to a. This paper proposes an overview of formal ontologies and how they can be used for geographical information integration. A description of an intelligent architecture for semantic-based information. Information Integration with Ontologies: Ontology based Information Integration in an Industrial Setting is ideal for technical experts and computer researchers in the IT-area looking to achieve.
Formal Ontology in Information Systems: Proceedings of the 1st information integration, object-oriented analysis, information retrieval and extraction, knowledge management and organization, agent-based systems design.
() Resolution of Semantic Heterogeneity in Database Schema Integration Using Formal Ontologies, Information. Ontologies have been developed and investigated for some time in artificial intelligence to facilitate knowledge sharing and reuse.
More recently, the notion of ontologies has attracted attention from fields such as databases, intelligent information integration, cooperative information systems, information retrieval, electronic commerce, enterprise application integration, and knowledge Cited by: M.
Eugenia Alvarez, José L. De la Mata, in Computer Aided Chemical Engineering, 1 Introduction. Information integration and exchange has been and still is a very important topic (see ISO standards like –, or AP). In the past decades ontologies have got an important role in information representation, some of them have been developed for process systems, as OntoCape.
Enterprise information integration (EII) is the ability to support an unified view of data and information for an entire a data virtualization application of EII, a process of information integration, using data abstraction to provide a unified interface (known as uniform data access) for viewing all the data within an organization, and a single set of structures and naming.
" Reusable ontologies are becoming increasingly important for tasks such as information integration, knowledge-level interoperation, and knowledge-base development. We have developed a set of tools and services to support the process of achieving consensus on common shared ontologies by geographically distributed groups.
Abstract. Ontologies were developed in Artificial Intelligence to facilitate knowledge sharing and the beginning of the nineties ontologies have become a popular research topic investigated by several Artificial Intelligence research communities, including Knowledge Engineering, natural-language processing and knowledge representation.
Information Integration with Ontologies: Ontology based Information Integration in an Industrial Setting is ideal for technical experts and computer researchers in the IT-area looking to achieve integration of heterogeneous information and apply ontology technologies and techniques in practice.
It will also be of great benefit to technical. Ontology Mapping Techniques in Information Integration: /ch The semantic Web suggests to annotate Web resources with machine-processable metadata; and ontologies, as means to conceptualize and structure knowledge, areCited by: 6.
USING ONTOLOGIES FOR GEOGRAPHIC INFORMATION INTEGRATION Frederico Torres Fonseca The Pennsylvania State University, USA Keywords: ontologies, GIS, geographic information integration, interoperability Contents 1.
Introduction 2. Ontologies and Interoperability GIS Interoperability Ontology and Interoperation Ontology Levels 3. Practical Ontologies for Information Professionals provides an accessible introduction and exploration of ontologies and demonstrates their value to information professionals.
More data and information is being created than ever before. Ontologies, formal representations of knowledge with rich semantic relationships, have become increasingly important in the context of today’s information. Ontologies tend to be found everywhere.
They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies.
Thus, merely using ontologies, like using XML, does not 5/5(1). As for data integration and ontologies, there are several articles I could direct you to for a more in depth discussion of the topic.
One in particular, " Really, Really Big Data: NASA at the Forefront of Analytics " by Seth Earley details how NASA used ontologies to define the data sets in terms that could be interpreted and enable integration. The primary objective of ONTOLOGIES: A Handbook of Principles, Concepts and Applications in Information Systems is to mobilize a collective awareness in the research community to the leading and emerging developments in ODIS, and consequently, highlight the enormous potential of ODIS research to both fundamentally transform and create.
Ontologies form an indispensable basis for modeling and engineering languages for business enterprise and information systems: fostering a need for the integration of structural and behavioral aspects in domain-oriented ontologies.
The Handbook of Ontologies for Business Interaction documents high-q. So may this book find its way not only to the desks of researchers and students, but also into the offices and minds of business practitioners worldwide who are dealing with the challenge of integrating their business processes, applications and information.
This book is, in the most general sense, about understanding each other – that is. The congruence of clinical and technical ontologies is essential to facilitate semantic and syntactic integration to promote the development of more proactive and intelligent CDM systems to reduce the burden on providers while still integrating patient information to guide integrated multidisciplinary practice, research and by: ontologies through specialization and combination.
It also appears that the emerging paradigms such as web services and the semantic web will enable the large-scale development, deployment, and sharing of ontologies and ontology-driven information systems.
Some of the key research questions in. different tourism ontologies and related instance data. This paper focuses on the state of the arts analysis on the existing tourism ontologies and the requirement analysis of ontology management tools for tourism domain.
We present several existing tourism ontologies which are suitable to serve as a basis for problem specific by: Leveraging Ontologies and Application Integration. Ontologies: A Deeper Dive. Finding the Information. Ontology Treatment. Web-Based Standards and Ontologies.
Types of Vertical Ontologies. Value of Ontologies. Application Integration Manifesto. Mandatory. Connectivity. Support for Information-Oriented Connections. Get this from a library. Ontologies-based business integration.
[Michael Rebstock; Janina Fengel; Heiko Paulheim] -- "This book shows what ontology management can do for process, information and application integration under dynamic e-business conditions.
The authors not only discuss research results and develop. Read "Information Search, Integration, and Personalization International Workshop, ISIPBangkok, Thailand, SeptemberRevised Selected Papers" by available from Rakuten Kobo. This book constitutes the refereed post-proceedings of the International Workshop on Brand: Springer International Publishing.
the chapters in a di erent order (see ‘how to use the book’). As to how comprehensive an introduction to ontology engineering should be, there is no good answer. At least for this rst version, the aim is for a semester-long course, where each chapter can be covered in a week and does not require too much.
Enterprise Information Integration: The Need and Benefits “Enterprise Information Integration is an approach to integration that has arisen out of the need for organizations to identify and correlate related, but separate data,” according to JP Morganthal, author of the seminar book on EII entitled Enterprise Information Integration: A.
An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies.4/5(3).
Ontology-driven information integration and delivery leverage rich extensible domain ontologies found in the oil & gas industry, and combine them with industry standard definitions and controlled vocabularies. This results in meaningful metadata that reflects the concepts relevant to the domain.
A Resource-Bounded Interpretation-Centric Approach to Information Gathering / Victor Lesser, Bryan Horling, Frank Klassner, Anita Raja, Thomas Wagner, Shelley Zhang.
Knowledge Base and Database Integration / Alun Preece. Squeal: SQL Access to Information on the Web / Ellen Spertus. Handling Inconsistency for Multi-Source Integration. Data integration is the problem of combining data residing at different sources, and providing the user with a uniﬁed view of these data .
It is relevant to a number of applications including data warehousing, enterprise information integration, geographic information systems, and e-commerce applications. Data integration systems are usu.
We present the first prototype of INDUS (Intelligent Data Understanding System), a federated, query-centric system for information integration and knowledge acquisition from distributed, semantically heterogeneous data sources that can be viewed (conceptually) as by: When used in computer and information science, the term ontology refers to relationship-based hierarchical descriptions of concepts within a particular domain, such as biomedicine.
Ontologies are used within the semantic web to capture a common language for reuse and reapplication in computer systems, improving efficiency and flexibility between systems, and aiding in natural language : Marisa Conte.
Information integration and interoperability among information sources are related problems that have received significant attention since early days of computer information processing. The objective of Web information integration system is to promote Web information collection, sharing and retrieval in distributed and heterogeneous environment.
This paper puts forward an ontology-based. A solution to this problem is the use of taxonomies or ontologies of manufacturing concepts and terms, because ontologies provide a way to make explicit the semantics (i.e., the meaning) for the concepts used, rather than relying just on the syntax used to encode those by: Information integration in bioinformatics with ontologies and standards.
Lambrix, Patrick. Springer Berlin/Heidelberg,1, p. Chapter in book (Refereed) Abstract [en] Other kinds of resources that are not so well-known or commonly used yet are the ontologies and the standards.
Ontologies aim to define a common terminology. While ontologies provide a conceptual basis for the information exchange, standards create consistency in the information exchange between different systems and allow interoperability between systems.
The main standard for the interoperability in the SW is the Resource Description Framework (RDF).Cited by: 1.