The ontology engineering field has been strengthened by the adoption of. This book, motivated by the ontology 101 tutorial given for many years at what was originally the semantic technology conference semtech and then later from a semesterlong university class, is designed to provide the foundations for ontology engineering. These videos were produced through the dedicated effort of john myers, a senior industrial and systems engineering student at wright state university. So, searching for javaon a system with an ontology might expand tha. An algorithm for merging two ontologies research india. A multi ontology synthetic benchmark for the semantic web yingjie li, yang yu and je. Ontology learning for the semantic web university of georgia. One important use case for the semantic web is the inte. The development process of the semantic web and web ontology. This site introduces ontologies and semantic web, with the emphasis on how ontologies are defined and used for semantic web applications today more about this site background is here. Hein department of computer science and engineering, lehigh university 19 memorial dr. Ontology engineering for the semantic web and beyond youtube.
A comparative study of ontology building tools in semantic. Ontology mapping and merging aspects in semantic web medcrave. Abstract your logo the semantic web is the second generation of the web, which helps sharing and reusing data across application, enterprise, and community boundaries. Web content consists mainly of distributed hypertext and hypermedia, and is accessed via a combination of keyword based search and link navigation. Ontology engineering for the semantic web comp60421 sean bechhofer university of manchester sean. In computer science and information science, an ontology formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts. The semantic web brings a set of new emerging technologies and models that need to be found and executed.
Ontology engineering for the sw knowledge representation and ontologies increasing role in applications w3cs owl and skos established standards key technologies in realising the semantic web and web of data module provides foundations and practice of understanding, developing and using owl ontologies. A multiontology synthetic benchmark 3 2 related work as mentioned before, except our previous work in 2, there is seldom related work similar to our multiontology semantic web benchmark system. Ontologies have become a popular research topic in many communities. Ontological engineering ontology support activities. A semantic search ontology is a static list used to, in a semiautomatic fashion, expand the meaning of a particular concept. Closely associated with data publication is the notion of the semantic web. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains.
Specialization of a general ontology engineering platform. In this paper i explore an alternate approach the possibility of using a readily available ontology engineering platform for the purposes of semantic information integration. Ontology learning for the semantic web article pdf available in intelligent systems, ieee 162. As shown previously ontology design contains the activity of knowledge acquisition. Introduction to semantic technology, ontologies and the. An introduction to ontology engineering university of cape town. Rdfs should not be merged due to their different data models, but that certain. Like any other dependable component of a system, ontology has to go through a repetitive process of refinement and evaluation during its development lifecycle before its. There is a lot to be said about how ontology, ontologies,and natural language interact from a philosophical perspective up to the pointthat different commitments lead to different features and, moreover,limitations of a semantic web application 36.
Ontology management semantic web, semantic web services. What is semantic search ontology and what is it used for. It will provide students with experience using a set of established patterns for developing owl ontologies and help them to learn to avoid the major pitfalls in using owl. It will introduce students to the w3c standard web ontology language, owl, and its underlying description logics.
This book is intended for undergraduate engineering students who are interested in exploring the technology of semantic web. Ontology engineering offers a direction towards solving the interoperability problems brought about by semantic obstacles, i. Introduction to ontology engineering, with emphasis on. Ontology engineering in a networked world, springer, 2012. Hence semantic web is not an application but an infrastructure where applications can be developed. Pdf ontology merging in the context of a semantic web expert. A multiontology synthetic benchmark for the semantic web yingjie li, yang yu and je. In recent years, researchers have been developing algorithms for the automatic mapping and merging of ontologies to meet the demands of interoperability between heterogeneous and distributed information systems. Mechanical engineering information and virtual product development mivp, vienna university of technology, 1060 getreidemarkt 9307 vienna, austria zeeshan. Common algebraic specification language is a general logicbased specification language developed within the ifip working group 1.
The produced result is explored and transformed to the merged ontology by the ontology engineer. Description framework rdf and ontology vocabularies, meaning is added to the. We consider alternative approaches to engineer ontologies, discuss current and emerging standards in this area, look at approaches to integrate data through ontology mapping, and outline a set of skills necessary to develop. Ontology and the semantic web university of washington. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and. Tools for virtual merging of ecoin applications and. Prominent semantic web standards include rdf, which is used to describe relationships between entities, and owl, the ontology web language. Semantic technology an overview sciencedirect topics. Semantic intelligent web, ontologies, ontology building tools, protege 3. Explorers guide to the semantic web, p 4 the semantic web is a vision of the next generation web, which. Ontology is a body of knowledge describing some domain, typically common sense knowledge domain. These agents cant communicate and successfully process information without interpreting that. The architecture of the web depends on agreed standards and, recognising that an ontology language standard would be a prerequisite for the development of the semantic web, the world wide web consortium w3c set up a standardisation working group to develop a standard for a web ontology language.
The book simplifies the tough concepts associated with semantic web and hence it can be considered as the base to build the knowledge about web 3. Introduction semantic web 1 is intended to guide the current web to a place where it is more useful for human consumption. Specialization of a general ontology engineering platform for. This tutorial is extracted from the introductory chapter of the dissertation that deals with the applications of ontologies in multiagent systems marek obitko advisor vladimir marik. Semantic web is a platform that integrates data sources using semantic rules, ontologies, web services and web processes8. In fact, ontology is a main component of this research. Thus, the proliferation of ontologies factors largely in the semantic webs success. It proposes to use rdf as a flexible data model and use ontology to represent data semantics. Applications of ontologies in software engineering 3 generality. Semantic web aims to make web content more accessible to automated processes adds semantic annotations to web resources ontologies provide vocabulary for annotations terms have well defined meaning owl ontology language based on description logic exploits results of basic research on complexity, reasoning, etc. Semantic web semantic web ontology information science. Detection and resolution of semantic inconsistency and.
A multiontology synthetic benchmark for the semantic web. Initiatives on linked open data for collaborative maintenance and evolution of community knowledge based on ontologies emerge, and the first semantic applications of webbased ontology technology are successfully positioned in areas like semantic search, information integration, or web community portals. Ontology merging for federated ontologies on the semantic web. Building ontology networks by localizing ontologies or ontology introduction to the semantic web tutorial. In this lecture, however, more emphasis will be put on the interaction of nlpand ontologies. Due to the emergence of the semantic web vision ontologies have been attracting much attention recently. Practitioners in industry will find this work invaluable. This paper aims at presenting an intelligent elearning system from the literature. According to the expressiveness of the formalism used, one can further distinguish lightweight and heavyweight ontologies. Ontologies and the semantic web school of informatics. Ontologies on the semantic web wiley online library. But, still stateoftheart ontology mapping and merging systems is semiautomatic that reduces the burden of manual creation and maintenance of mappings, and need.
Ontology engineering aims to make explicit the knowledge contained in software applications, and organizational procedures for a particular domain. The new system differs from other representation systems in that it is based on a more sophisticated semantic representation of information, aims to go well beyond the. Multilayer ontology warehouse for semantic search 3. This paper discusses the development of a new information representation system embodied in ontology and the semantic web. The web ontology language owl is a family of knowledge representation languages for authoring ontologies.
Modeldriven ontology engineering 38, metamodels with semantic systems 25 and metamodels for ontologies 24. Ontology engineering synthesis lectures on the semantic. Proper utilization of ontologies is very important for the semantic web vision. Pdf the purpose of this paper is to describe the process of owl web. Semantic elearn services and intelligent systems using web. Ontologybased applications in the age of the semantic web. Introduction introduction to ontologies and semantic web. Ontology defines a set of representational primitives with which a domain of knowledge is modeled. The semantic web aims to build a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries. At least for this rst version, the aim is for a semesterlong course, where each chapter can be covered in a week and does not require too much reading of core material, with the core material being the contents of the chapter. Semantic web technology may support more advanced artificial intelligence problems for knowledge retrieval 20. The definition 1 is the meaning in philosophy as we have discussed above, however it has many implications for the ai purposes.
What is ontology introduction to ontologies and semantic. In the semantic web environment, it is hypothesized that software agents will be able to retrieve, process, and act upon data in an intelligent manner. Ontology engineering in the age of the semantic web the availability of large scale semantics millions of docs and tens of thousands of ontologies opens up the following opportunities to make costeffective the develoment of large scale semantic applications out of reusable resources. Semantic elearn services and intelligent systems using. Proceedings of the 2nd international workshop on ontology department of computer and information science ida. Present journals at least in science, technology, and medicine make considerable use of semantic technologies to enrich content, but the formal concept of the semantic web remains complex, expensive, and elusive. Semantic web and linked data corresponds to the topdown ai family of approaches and includes an introduction and practical tutorial on the rdfbased semantic annotation of web resources and services for the semantic web, linked data and ontology engineering. The semantic web ontology learning for the semantic web alexander maedche and steffen staab, university of karlsruhe the semantic web relies heavily on formal ontologies to structure data for comprehensive and transportable machine understanding. Ontology engineering for the semantic web and beyond.
Ontology engineering is a set of tasks related to the development of ontologies for a particular domain. Present journals at least in science, technology, and medicine make considerable use of semantic technologies to enrich content, but the formal concept of the. I also describe an abstract solution for how such an environment can be. Aug 08, 2016 these videos were produced through the dedicated effort of john myers, a senior industrial and systems engineering student at wright state university. An efficient ontology comparison tool for semantic web. Ontology management is designed as a reference or secondary text for researchers and advancedlevel students interested in the semantic web, semantic web services swsand web services, information systems, data and knowledge engineering, ontologies, or other aspects of semantic systems. Much ontology exists in every domain at various level of.
Ontology engineering requires significant subject domain expertise and knowledge engineering skills. An introduction to ontologies and ontology engineering. World wide web www is the most popular global information sharing and. Ontology is an explicit specification of conceptualization.
As to how comprehensive an introduction to ontology engineering should be, there is no good answer. The widespread adoption of semantic web and other ontology based applications in the intelligence community and indeed the wider web is that quality ontologies are difficult to build, maintain, and exploit. Machine learning methods of mapping semantic web ontologies. The role of vocabularies on the semantic web are to help data integration when, for example, ambiguities may exist on the terms used in the different data sets, or when a bit of extra knowledge may lead to the discovery of new relationships. Ontology learning greatly facilitates the construction of ontologies by the ontology engineer. Journal of computing, volume 2, issue 6, june 2010, issn 2151.
The vision of the semantic web is to let computer software relieve us of much of the burden of locating resources on the web that are relevant to our needs and extracting, integrating and indexing the information contained within. The extrac tion of instances from text documents circumvents. In computer science and information science, an ontology encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities that substantiate one, many or all domains of discourse. Currently, relational models and xml tree models are widely used to represent structured and. The development process of the semantic web and web. Combining semantic search and ontology learning for. International journal of applied engineering research issn 09734562 volume, number 12. The software engineering master program can benefit from the semantic technology, semantic programming, semantic applications, selfmanaged systems engineering, and the open world assumption in software design originated from the semantic web vision and based on appropriate standards. Introduction in the vision of semantic web ontologies play a very crucial role. It contributes several mechanisms that can be used to classify information and characterize. Journal of computing, volume 2, issue 6, june 2010, issn.
Ontology engineering offers a direction towards solving the interoperability problems brought about by semantic obstacles, such as the obstacles related to the definitions of business terms and software classes. There are a number of such languages for ontologies, both proprietary and standardsbased. An ontology language is a formal language used to encode the ontology. The book can serve as a course textbook or a primer for all those interested in ontologies. The main purpose of the semantic web and ontology is to integrate heterogeneous data and. The lubm 7 is an example of a benchmark for semantic web knowledge. Ontology engineering offers a direction for overcoming semantic obstacles, such as those related to the definitions of business terms and software classes.
505 1109 1103 791 277 1480 1257 34 175 1069 1200 93 877 80 1228 933 810 1213 1159 52 778 158 861 1013 1355 747 53 342 799 827 1314 1493 352 608 180 463