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A Framework for Comparing the Use of a Linguistic Ontology in an Application
A Framework for Comparing the use of a Linguistic Ontology in an Application Julieanne van Zyl1 and Dan Corbett2 Abstract. A framework recently developed for understanding and “a body of knowledge about the world (or a domain) that a) is classifying ontology applications provides opportunities to review a repository of primitive symbols used in meaning the state of the art, and to provide guidelines for application b) organises these symbols in a tangled subsumption developers from different communities [1]. The framework hierarchy; and identifies four main categories of ontology applications: neutral c) further interconnects these symbols using a rich system of authoring, ontology as specification, common access to semantic and discourse-pragmatic relations defined among information, and ontology-based search. Specific scenarios are the concepts” [2]. described for each category and a number of features have been identified to highlight the similarities and differences between There has been some work on comparing ontology applications, them. In this paper we identify additional scenarios, describing the which refer to “the application that makes use of or benefits from use of a linguistic ontology in an application. We populate the the ontology (possibly directly)” [1]. A framework [3] was scenarios with a number of prominent research and industrial developed for comparing various projects in ontology design, applications from diverse communities such as knowledge-based which considered the differences and similarities in the way the machine translation, medical databases, heterogenous information projects treat some basic knowledge representation aspects. The systems integration, multilingual text generation, Web-based projects compared include three natural language ontologies, two applications, and information retrieval. -
A Translation Approach to Portable Ontology Specifications
Knowledge Systems Laboratory September 1992 Technical Report KSL 92-71 Revised April 1993 A Translation Approach to Portable Ontology Specifications by Thomas R. Gruber Appeared in Knowledge Acquisition, 5(2):199-220, 1993. KNOWLEDGE SYSTEMS LABORATORY Computer Science Department Stanford University Stanford, California 94305 A Translation Approach to Portable Ontology Specifications Thomas R. Gruber Knowledge System Laboratory Stanford University 701 Welch Road, Building C Palo Alto, CA 94304 [email protected] Abstract To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how -
Semantic Gadgets: Pervasive Computing Meets the Semantic Web
Semantic Gadgets: Pervasive Computing Meets the Semantic Web Ora Lassila Research Fellow Agent Technology Group, Nokia Research Center October 2002 1 © NOKIA 2002-10-01 - Ora Lassila Mobility Makes Things Different • Device location is a new dimension • more information about the user and the usage context available • new applications & services are possible • Devices are different • reduced capabilities: smaller screens, slow input devices, lower bandwidth, higher latency, worse reliability, … • trusted device: always with you & has access to your private data • Usage contexts and needs are different • awkward usage situations (e.g., in the car while driving) • specific needs (“surfing” unlikely) • you are always “on” (= connected) • Dilemma: • the Internet - by design - represents a departure from physical reality but mobility grounds services & users to the physical world 2 © NOKIA 2002-10-01 - Ora Lassila 1 Some Enablers of Mobile Internet • Access to services from handheld terminals • Dynamic synthesis of content • Context-sensitivity • location is one dimension of a “context”, but there are others • New Technologies • Artificial Intelligence • machine learning: automatic customization and adaptation • automated planning: autonomous operation • “Semantic Web” • intelligent synthesis of content from multiple sources (ad hoc & on demand) • explicit representation of semantics of data & services • Ubiquitous (aka Pervasive) Computing • (a paradigm shift in personal computing) 3 © NOKIA 2002-10-01 - Ora Lassila Semantic Web: Motivation -
Browsing the Semantic Web
Browsing the Semantic Web Ora Lassila Nokia Research Center Cambridge Cambridge, MA 02142, USA Abstract lution. Enabling browsing is further encouraged by the fact that, despite its simple data model, users and developers are Presenting RDF graphs to the end user as hypertext enables often put off by RDF’s cryptic XML-based syntax. interactive exploration and inquiry of “semantic” data. In Many tools have been constructed for searching, ex- this paper we present a tool that allows users to “see” their ploring and querying complex information spaces such as RDF data, without having to decipher syntactic represen- semistructured data representations or collections with rich tations that are typically not human-friendly. The tool is metadata. These tools often offer a mixture of features such part of a broader architecture designed for viewing many as faceted search, clustering of search results, etc. Exam- different types of data in Semantic Web formalisms, for ples of such systems include Lore [7, 8], Flamenco [26], experimenting with the caching of dynamically changing and others. More specifically, recent years have also seen a data, and for exploring the possible ad hoc integration of number of “Semantic Web browsers” emerge; examples of data from multiple sources. Additionally, this tool enables this type of software include mSpace [16], Haystack [18], browsing of semantic data on a mobile device, by adapting Magnet [23], DBin [25], semantExplorer [21], and others. the hypertext generation to better suit small screens. These systems allow the browsing of Semantic Web data and provide various ways of searching and visualizing this data. Many of them combine semantic data with “classi- 1. -
Boeing Position Paper
Frameworks for Semantics in Web Services: A position paper for the W3C Workshop Janet L Jones Boeing Phantom Works IDeAS May 6, 2005 This position paper proposes directions for the development of a framework for Semantic Web Services, with particular emphasis on automating tasks based on semantic descriptions. Abstract Boeing examines the application of Semantic Web Services in a net centric environment. Boeing envisions a wide range of possible benefits in this context. The key functionality needed is the automated and dynamic composability of services in an ad hoc environment. Net-Centric Environment: Use of Dynamically Composable Semantic Web Services “The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”1 “There’s a revolution occurring and it’s all about making the Web meaningful, understandable, and machine-processable, whether it’s based in an intranet, extranet, or Internet. This is called the Semantic Web, and it will transition us towards a knowledge- centric viewpoint of everything.”2 A net-centric environment is characterized by seamless interoperation between systems. As more networks and nodes are introduced, the environment becomes more robust, increasing its combined capabilities. Completion of the net-centric environment vision requires mobile ad hoc collaboration of disparate systems. Systems will be interacting in new ways, supporting each other through a wide variety of advertised services. In the ad hoc environment, not all of the desired capabilities can be known in advance. These capabilities will be used by communities of interest (COIs) which form in an ad hoc manner. -
Formalizing Knowledge by Ontologies: OWL and KIF
Formalizing Knowledge by Ontologies: OWL and KIF Marchetti Andrea, Ronzano Francesco, Tesconi Maurizio, Minutoli Salvatore CNR, IIT Department, Via Moruzzi 1, I-56124, Pisa, Italy (andrea.marchetti, francesco.ronzano, maurizio.tesconi, salvatore.minutoli)@iit.cnr.it 2 I Abstract. During the last years, the activities of knowledge formaliza- tion and sharing useful to allow for semantically enabled management of information have been attracting growing attention, expecially in dis- tributed environments like the Web. In this report, after a general introduction about the basis of knowledge abstraction and its formalization through ontologies, we briefly present a list of relevant formal languages used to represent knowledge: CycL, F- Logic, LOOM, KIF, Ontolingua, RDF(S) and OWL. Then we focus our attention on the Web Ontology Language (OWL) and the Knowledge Interchange Format (KIF). OWL is the main language used to describe and share ontologies over the Web: there are three OWL sublanguages with a growing degree of expressiveness. We describe its structure as well as the way it is used in order to reasons over asserted knowledge. Moreover we briefly present three relevant OWL ontology editors: Prot´eg´e, SWOOP and Ontotrack and two important OWL reasoners: Pellet and FACT++. KIF is mainly a standard to describe knowledge among different com- puter systems so as to facilitate its exchange. We describe the main elements of KIF syntax; we also consider Sigma, an environment for cre- ating, testing, modifying, and performing inference with KIF ontologies. We comment some meaningful example of both OWL and KIF ontologies and, in conclusion, we compare their main expresive features. -
Representing and Using Ontologies
USC-CIT Technical Report 98-01 1 Representing and Using Ontologies Kuhanandha Mahalingam and Michael N. Huhns January 1998 Center for Information Technology Department of Electrical and Computer Engineering University of South Carolina Columbia, SC, U.S.A. 29208 (803) 777-5921 or [email protected] (803) 777-8045 FAX Keywords: Ontology, Java, Distributed Information Systems Abstract This paper discusses the representation of large ontologies, especially in a graphical format. It describes a tool, developed using Java, that incorporates several abstraction mechanisms that can help manage such ontologies. Furthermore, it briefly analyzes possible point-and-click approaches that can be used to form queries on these ontologies. 1 This research was partially done under a cooperative agreement between the National Institute of Standards and Technology Advanced Technology Program (under the HIIT contract, number 70NANB5H1011) and the Healthcare Open Systems and Trials, Inc. consortium. 1. Introduction The introduction of the World Wide Web (Web) and the consequent growth of other supporting technologies that, without doubt, have driven the Internet’s widespread usage have created many new problems. The most notable problem is how to manage efficiently the volume and heterogeneity of information produced on the Web each day. Further, most of the data produced is no longer just simple text, but also consists of multimedia objects. Multimedia objects require different policies, procedures, and conventions. They originate from and reside on a variety of different operating systems, and, most importantly, are large and complex. There are many approaches for coping with these problems. One of these approaches is to use ontologies for capturing the knowledge represented by the information sources, so that it can be viewed and manipulated declaratively. -
An Introduction to the Semantic Web
An Introduction To The Semantic Web Fernando de Souza 1 “The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” Tim Berners-Lee, James Hendler and Ora Lassila, The Semantic Web, Scientific American, May 2001 2 1 An Introduction To The Semantic Web …extension of the current web… “. .information on the web needs to be in a form that machines can ‘understand’ rather than simply display. The concept of machine-understandable documents does not imply some magical artificial intelligence allowing machines to comprehend human mumblings. It relies solely on a machine’s ability to solve well-defined problems by performing well- defined operations on well-defined data.” From Berners-Lee, Hendler; Nature, 2001 3 http://www.nature.com/nature/debates/e-access/Articles/bernerslee.htm …extension of the current web… “Most of the Web's content today is designed for humans to read, not for computer programs to manipulate meaningfully.” Tim Berners-Lee, James Hendler and Ora Lassila, The Semantic Web, Scientific American, May 2001 4 2 An Introduction To The Semantic Web …well-defined meaning… There are lots of ways in which our machines can use our web content when they can understand it. •When my personal digital assistant's calendar program understands dates, it can alert me when an appointment is coming up. •When my email program's address book understands that something is a phone number or an email address, it can set up communication with that person with a click. -
Ontology and Information Systems
Ontology and Information Systems 1 Barry Smith Philosophical Ontology Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ is often used by philosophers as a synonym for ‘metaphysics’ (literally: ‘what comes after the Physics’), a term which was used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’.2 The term ‘ontology’ (or ontologia) was itself coined in 1613, independently, by two philosophers, Rudolf Göckel (Goclenius), in his Lexicon philosophicum and Jacob Lorhard (Lorhardus), in his Theatrum philosophicum. The first occurrence in English recorded by the OED appears in Bailey’s dictionary of 1721, which defines ontology as ‘an Account of being in the Abstract’. Methods and Goals of Philosophical Ontology The methods of philosophical ontology are the methods of philosophy in general. They include the development of theories of wider or narrower scope and the testing and refinement of such theories by measuring them up, either against difficult 1 This paper is based upon work supported by the National Science Foundation under Grant No. BCS-9975557 (“Ontology and Geographic Categories”) and by the Alexander von Humboldt Foundation under the auspices of its Wolfgang Paul Program. Thanks go to Thomas Bittner, Olivier Bodenreider, Anita Burgun, Charles Dement, Andrew Frank, Angelika Franzke, Wolfgang Grassl, Pierre Grenon, Nicola Guarino, Patrick Hayes, Kathleen Hornsby, Ingvar Johansson, Fritz Lehmann, Chris Menzel, Kevin Mulligan, Chris Partridge, David W. Smith, William Rapaport, Daniel von Wachter, Chris Welty and Graham White for helpful comments. -
The RDF Layer
Knowledge Representation and Semantic Technologies The RDF layer Riccardo Rosati Corso di Laurea Magistrale in Ingegneria Informatica Sapienza Università di Roma 2019/2020 The Semantic Web Tower The RDF layer 2 Syntax and semantics • Syntax: the structure of data • Semantics: the meaning of data • Two conditions necessary for interoperability: – Adopt a common syntax: this enables applications to parse the data. – Adopt a means for understanding the semantics: this enables applications to use the data. The RDF layer 3 XML • XML: eXtensible Mark-up Language • XML documents are written through a user- defined set of tags • tags are used to express the “semantics” of the various pieces of information The RDF layer 4 XML: example <course date=“2007”> <title>Seminari di Ingegneria del Software </title> <teacher> <name>Giuseppe De Giacomo</name> <email>[email protected]</email> </teacher> <prereq>none</prereq> </course> The RDF layer 5 XML • XML: document = labelled tree • node = label + attributes/values + contents <course date=“...”> <title>...</title> course <teacher> <office>...</office> <email>...</email> = title teacher prereq </teacher> <prereq>...</prereq> </course> office email The RDF layer 6 XML • XML Schema = grammar for describing legal trees and datatypes • can we use XML to represent semantics? The RDF layer 7 XML and semantics <Predator> … </Predator> • Predator: a medium-altitude, long-endurance unmanned aerial vehicle system. • Predator : one that victimizes, plunders, or destroys, especially for one's own gain. • Predator -
Semantic Gadgets - Extending the Semantic Web to Physical Devices
Semantic Gadgets - Extending the Semantic Web to Physical Devices Ora Lassila Research Fellow Agent Technology Group, Nokia Research Center November 2000 1 © NOKIA 2000-11-10 - Ora Lassila Internet & Mobility: a Future 2 © NOKIA 2000-11-10 - Ora Lassila Mobility Makes Things Different • Device location is a completely new dimension • more information about the user and the usage context available • new applications & services are possible • Devices are different • reduced capabilities: smaller screens, slow input devices, lower bandwidth, higher latency, worse reliability, … • trusted device: always with you & has access to your private data • Usage contexts and needs are different • awkward usage situations (e.g., in the car while driving) • specific needs (“surfing” unlikely) • you are always “on” (= connected) • Dilemma: • the Internet represents a departure from physical reality BUT mobility grounds services & users to the physical world 3 © NOKIA 2000-11-10 - Ora Lassila Critical Components of Mobile Internet • Access to internet-based services from small handheld terminals • first step: WAP (quick build-up of a large user base) • initial applications include personal information management and connectivity, “infotainment”, (mobile) e-commerce, vertical applications & access to corporate intranet data • Dynamic synthesis of content • first step: data in XML, transformations to suitable formats • device independence is key to long term interoperability • Context-dependence • first step: customization and personalization • adaptation -
Semantic Web – Introduction and Problem Statement
Thomas Schmidt schmidt@informatik. haw-hamburg.de Semantic Web – Introduction and Problem Statement • Initial Concepts • Meta Data + RDF • Initial Problems • Representing Meaning • Key Perspectives • Ontologies + OWL • The Role of XML • Evaluating Resources Thomas Schmidt schmidt@informatik. Semantic Web: The Idea haw-hamburg.de "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation." Tim Berners-Lee, James Hendler, Ora Lassila: “The Semantic Web“. Scientific American, May 2001 2 Thomas Schmidt schmidt@informatik. Objectives haw-hamburg.de ¾ Bring machine processable structure to the bulk of Web information ¾ Provide a layer of meaningful meta information along with Web offers to identify their semantics ¾ Provide semantic rules to the community to digest Web concurrency and allow for conclusions ¾ Offer ways to learn about the reputation of a resource 3 Thomas Schmidt schmidt@informatik. Semantic Web Layers haw-hamburg.de Source: http://www.w3.org/2001/12/semweb-fin/w3csw 4 Thomas Schmidt schmidt@informatik. Operational Concept haw-hamburg.de R I Ux R II A2 A1 R III Ai Uy Am R K R N Resources Agents Users 5 Thomas Schmidt schmidt@informatik. Resources, URIs & Links haw-hamburg.de Goal: Understand resources and their relations Resources: Anything addressable by a URI. Extend resources to carry a ‘type’ attribute Links: Relating resources. Extend links to carry ‘type’ attribute. 6 Thomas Schmidt schmidt@informatik. Fundamental Problems haw-hamburg.de Heterogeneity: Systems, encoding, structures, languages/expressiveness’, words, meanings, … Anonymity: Almost all resources in the Web unknown to recipient Context: Resources are meaningless without identification of context Scale: Peer-to-Peer view has complexity n2, with n = number of Internet resources Visions & Expectations: partly naive, partly vague, … 7 Thomas Schmidt schmidt@informatik.