DOCSLIB.ORG

A Volcano Erupts: Semantically Mediated Integration of Heterogeneous Volcanic and Atmospheric Data

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Volcano Erupts: Semantically Mediated Integration of Heterogeneous Volcanic and Atmospheric Data A Volcano Erupts: Semantically Mediated Integration of Heterogeneous Volcanic and Atmospheric Data Peter Fox Deborah McGuinness High Altitude Observatory, Knowledge Systems & AI Lab, ESSL/NCAR Stanford University PO Box 3000 353 Serra Mall Boulder CO 80307-3000 Stanford, CA 94305 [email protected] McGuinness Associates 20 Peter Coutts Circle Stanford, CA 94305 Robert Raskin Krishna Sinha JPL/NASA Virginia Polytechnic Institute, Wilson Blvd., Pasadena, CA Department of Geology Blacksburg, VA ABSTRACT tologies implemented within existing distributed technology We present a research effort into the application of seman- frameworks are providing essential, re-useable, and robust, tic web methods and technologies to address the challeng- support necessary for interdisciplinary scientific research ac- ing problem of integrating heterogeneous volcanic and atmo- tivities. spheric data in support of assessing the atmospheric effects Categories and Subject Descriptors: H.2.5 Heteroge- of a volcanic eruption. neous Databases: Data translation, I.2.4 Knowledge Rep- This exemplary volcano eruption scenario highlights what resentation Formalisms and Methods: Frames and scripts; is true for the vast majority of data intensive Earth system Representation languages; Semantic networks investigations which have limited ability to explore impor- General Terms: Design tant and difficult problems. This is because they are forced Keywords: informatics, knowledge representation, ontolo- to find and use data representing an event or phemenonon of gies, semantic data integration, semantic mediation interest through data collections at the data-element, or syn- tactic, level rather than at a higher scientific, or semantic, level. Even if relevant data is found in one collection, it may 1. INTRODUCTION not be easy or possible to find similar, related data in an- When a volcano erupts, there is sequence of events and other collection. In many cases, syntax-only interoperability impacts that is diverse and complex. The characteristics of IS the state-of-the-art and at best, there are some instances an eruption; size, type and duration all influence the effect of hard-wired but simple semantic enhancements (e.g. a on the local, regional, and global environment. These effects special purpose web service wrapper around the data). Sci- range from diminished air quality, hazards for human health entists and non-scientists are forced to learn details of the and ground and air transportation to effects on atmospheric data schema, other people’s naming schemes and syntax de- composition and radiative blanketing. The contributions cisions and details of differing web site interfaces. These come from the smoke and ash, ejected gases, scattering and constraints are limiting even when researchers are looking numerous other processes. The location of the volcano (lati- for information in their own discipline, but they present even tude and longitude) as well as its tectonic setting on land or greater challenges when researchers are looking for informa- undersea also are factors. There are an increasing number tion spanning multiple disciplines, including some in which of online repositories of scientific data information related they are not extensively trained. The volcano eruption sce- to volcanoes, their present and past activity and both direct nario exemplifies many of these challenges. In this paper we and proxy measurements of the nature of their impact. present research progress on how semantic enablement for While numerous sources of monitoring and retrospective scientific data integration is achieved. We present how on- data are available which represent measurements of the above- mentioned quantities they are presently stored in heteroge- nous and highly distributed repositories. To realize the goal of integration of many of these diverse sources of data to Permission to make digital or hard copies of all or part of this work for address specific aspects of the volcano eruption scenarios personal or classroom use is granted without fee provided that copies are we need to address many factors concerning access to and not made or distributed for profit or commercial advantage and that copies interoperability of the online scientific data. bear this notice and the full citation on the first page. To copy otherwise, to This work is aimed at providing scientists with the op- republish, to post on servers or to redistribute to lists, requires prior specific tion of describing what they are looking for in terms that permission and/or a fee. CIMS’07, November 9, 2007, Lisboa, Portugal. are meaningful and natural to them, instead of in a syn- Copyright 2007 ACM 978-1-59593-831-2/07/0011 ...$5.00. tax that is not. The goal is not simply to facilitate search and retrieval, but also to provide an underlying framework that contains information about the semantics of the scien- tific terms used. These capabilities are expected to be used by scientists who want to do processing on the results of the integrated data, thus the system must provide access to how integration is done and what definitions it is using. The missing elements in previous systems in enabling the higher-level semantic interconnections is the technology of ontologies, ontology-equipped tools, semantically aware in- terfaces between science components, and explanations of knowledge provenance. We present the initial results of a project entitled: Semantically-Enabled Science Data Inte- gration (SESDI) [1] which uses semantic technologies to in- tegrate data between these two discipline areas to assist in establishing causal connections as well as exploring as yet unknown relationships. We use as starting points, many elements of semantic web methodologies and technologies which are based on our developments for the Virtual Solar-Terrestrial Observatory (VSTO) [2]. This work created a scalable environment for Figure 1: Schematic of the events and processes be- searching, integrating, and analyzing databases distributed ginning with a volcanic eruption and leading to the over the Internet required a high level of semantic interop- climate/atmospheric response. erability and has implemented a semantic data framework built on OWL-DL [3] ontologies, using the Pellet [4] reasoner experts in the areas. Prior to a workshop, we identify a within a Java-Tomcat servlet engine and made available via small set of subject matter experts. We also provide some a Spring-based web portal and SOAP/WSDL [5] web ser- background material for reading about ontology basics. Ad- vices. ditionally, prior to our face to face meetings with experts, We also have significant experience with ontology pack- we identify foundational terms in the discipline and provide ages and data registration from the Geosciences Network a simple starting point for organizing the basic terminol- (GEON) [6]. Our present ontology develop involved some ogy. While we do not want to influence the domain experts new developments as well as iterations and augmentations of on their terminology, we find that we make more progress the background domain ontology: Semantic Web for Earth if we provide simple starting points using well agreed upon and Environmental Terminology (SWEET) [7]. We lever- terminology. We then bring together a small group of the age the precise formal definitions of the terms in supporting chosen domain experts and science ontology experts with a semantic search and interoperability. goal of generating an initial ontology containing the terms and phrases typically used by these experts. We use our task 2. USE CASES of researching the impact of volcanoes and global climate to We have developed several underlying use cases [8] for the focus the discussions to help determine scope and level of volcano-atmosphere data integration and in this section we granularity. will present the first of these which addresses the signature We held a meeting with volcano experts and generated an of an eruption in the terrestrial lower atmosphere. This use initial ontology containing terms and phrases used to classify case is: “determine the statistical signatures of both volcanic volcanoes, volcanic activities, and eruption phenomena. We and solar forcings on the height of the tropopause”. use a graphical concept mapping tool [9] for capturing the This specific science template is motivated by the more terms and their relationships. general research direction of looking for indicators of the fall out of volcanic eruptions that may create changes in the 3.1 Volcanic and Plate Tectonic Semantics atmosphere. The statistical signatures are such indicators, Volcanoes can be classified by composition, tectonic set- and the tropopause is at the edge of the atmosphere so it is ting, environmental setting, eruption type, activity, geologic a sensitive signature area to examine. setting, and landform. The ontology currently contains up- A schematic of the use case is shown in Fig. 1 which indi- per level terms in these areas and is being expanded accord- cates some of the important terms, concepts, processes (and ing to the needs of the project and is being reviewed by eventually underlying data) we need to represent. additional domain experts. The initial focus is on gathering terms, putting them into a generalization hierarchy (using isa links in the diagram) and connecting the terms through 3. METHODOLOGY properties (using has links in the diagram) as well as sameas Our effort depends on machine processable specifications and ispartof. of the science terms that are used in the disciplines
Load more

Recommended publications
  • Description Logics Emerge from Ivory Towers Deborah L
    Description Logics Emerge from Ivory Towers Deborah L. McGuinness Stanford University, Stanford, CA, 94305 [email protected] Abstract: Description logic (DL) has existed as a field for a few decades yet somewhat recently have appeared to transform from an area of academic interest to an area of broad interest. This paper provides a brief historical perspective of description logic developments that have impacted their usability beyond just in universities and research labs and provides one perspective on the topic. Description logics (previously called terminological logics and KL-ONE-like systems) started with a motivation of providing a formal foundation for semantic networks. The first implemented DL system – KL-ONE – grew out of Brachman’s thesis [Brachman, 1977]. This work was influenced by the work on frame systems but was focused on providing a foundation for building term meanings in a semantically meaningful and unambiguous manner. It rejected the notion of maintaining an ever growing (seemingly adhoc) vocabulary of link and node names seen in semantic networks and instead embraced the notion of a fixed set of domain-independent “epistemological primitives” that could be used to construct complex, structured object descriptions. It included constructs such as “defines-an-attribute-of” as a built-in construct and expected terms like “has-employee” to be higher-level terms built up from the epistemological primitives. Higher level terms such as “has-employee” and “has-part-time-employee” could be related automatically based on term definitions instead of requiring a user to place links between them. In its original incarnation, this led to maintaining the motivation of semantic networks of providing broad expressive capabilities (since people wanted to be able to represent natural language applications) coupled with the motivation of providing a foundation of building blocks that could be used in a principled and well-defined manner.
    [Show full text]
  • Description Logics
    Description Logics Franz Baader1, Ian Horrocks2, and Ulrike Sattler2 1 Institut f¨urTheoretische Informatik, TU Dresden, Germany [email protected] 2 Department of Computer Science, University of Manchester, UK {horrocks,sattler}@cs.man.ac.uk Summary. In this chapter, we explain what description logics are and why they make good ontology languages. In particular, we introduce the description logic SHIQ, which has formed the basis of several well-known ontology languages, in- cluding OWL. We argue that, without the last decade of basic research in description logics, this family of knowledge representation languages could not have played such an important rˆolein this context. Description logic reasoning can be used both during the design phase, in order to improve the quality of ontologies, and in the deployment phase, in order to exploit the rich structure of ontologies and ontology based information. We discuss the extensions to SHIQ that are required for languages such as OWL and, finally, we sketch how novel reasoning services can support building DL knowledge bases. 1 Introduction The aim of this section is to give a brief introduction to description logics, and to argue why they are well-suited as ontology languages. In the remainder of the chapter we will put some flesh on this skeleton by providing more technical details with respect to the theory of description logics, and their relationship to state of the art ontology languages. More detail on these and other matters related to description logics can be found in [6]. Ontologies There have been many attempts to define what constitutes an ontology, per- haps the best known (at least amongst computer scientists) being due to Gruber: “an ontology is an explicit specification of a conceptualisation” [47].3 In this context, a conceptualisation means an abstract model of some aspect of the world, taking the form of a definition of the properties of important 3 This was later elaborated to “a formal specification of a shared conceptualisation” [21].
    [Show full text]
  • Semantic Web: a Review of the Field Pascal Hitzler [email protected] Kansas State University Manhattan, Kansas, USA
    Semantic Web: A Review Of The Field Pascal Hitzler [email protected] Kansas State University Manhattan, Kansas, USA ABSTRACT which would probably produce a rather different narrative of the We review two decades of Semantic Web research and applica- history and the current state of the art of the field. I therefore do tions, discuss relationships to some other disciplines, and current not strive to achieve the impossible task of presenting something challenges in the field. close to a consensus – such a thing seems still elusive. However I do point out here, and sometimes within the narrative, that there CCS CONCEPTS are a good number of alternative perspectives. The review is also necessarily very selective, because Semantic • Information systems → Graph-based database models; In- Web is a rich field of diverse research and applications, borrowing formation integration; Semantic web description languages; from many disciplines within or adjacent to computer science, Ontologies; • Computing methodologies → Description log- and a brief review like this one cannot possibly be exhaustive or ics; Ontology engineering. give due credit to all important individual contributions. I do hope KEYWORDS that I have captured what many would consider key areas of the Semantic Web field. For the reader interested in obtaining amore Semantic Web, ontology, knowledge graph, linked data detailed overview, I recommend perusing the major publication ACM Reference Format: outlets in the field: The Semantic Web journal,1 the Journal of Pascal Hitzler. 2020. Semantic Web: A Review Of The Field. In Proceedings Web Semantics,2 and the proceedings of the annual International of . ACM, New York, NY, USA, 7 pages.
    [Show full text]
  • Infrastructure for Web Explanations
    Infrastructure for Web Explanations Deborah L. McGuinness and Paulo Pinheiro da Silva Knowledge Systems Laboratory, Stanford University, Stanford CA 94305 {dlm,pp}@ksl.stanford.edu Abstract. The Semantic Web lacks support for explaining knowledge provenance. When web applications return answers, many users do not know what information sources were used, when they were updated, how reliable the source was, or what information was looked up ver- sus derived. The Semantic Web also lacks support for explaining rea- soning paths used to derive answers. The Inference Web (IW) aims to take opaque query answers and make the answers more transparent by providing explanations. The explanations include information concern- ing where answers came from and how they were derived (or retrieved). In this paper we describe an infrastructure for IW explanations. The infrastructure includes: an extensible web-based registry containing de- tails on information sources, reasoners, languages, and rewrite rules; a portable proof specification; and a proof and explanation browser. Source information in the IW registry is used to convey knowledge provenance. Representation and reasoning language axioms and rewrite rules in the IW registry are used to support proofs, proof combination, and semantic web agent interoperability. The IW browser is used to support navigation and presentations of proofs and their explanations. The Inference Web is in use by two Semantic Web agents using an embedded reasoning engine fully registered in the IW. Additional reasoning engine registration is underway in order to help provide input for evaluation of the adequacy, breadth, and scalability of our approach. 1 Introduction Inference Web (IW) aims to enable applications to generate portable and dis- tributed explanations for any of their answers.
    [Show full text]
  • Ecole Doctorale Environnements-Santé
    Ecole doctorale LECLA ANNEE 2021 Titre du projet de thèse : SYSTEMES INTELLIGENTS POUR LA TRANSMISSION DES HUMANITES NUMERIQUES ET POUR LA RECHERCHE EN SANTE Présentation du projet 1. Contexte scientifique et état de l’art Le déploiement du web bouleverse notre rapport au savoir et notre métier d’enseignant et de chercheur. Accompagnées d’agents intelligents capables d’effectuer des raisonnements à partir d’ontologies (représentations structurées d’un domaine), les plateformes sémantiques contribuent à construire cet espace commun de la connaissance au XXIe siècle : les « humanités numériques » (HN). Le thème des HN rassemble les travaux de chercheurs qui interrogent notre besoin de transmettre ce socle commun et des compétences de haut niveau cognitif. Ce champ a aussi besoin d’être mieux structuré, clarifié, stimulé et partagé. Sa formalisation peut permettre d’étudier les concepts et les liens entre compétences (Ageeva et al., 2019). Or, si nous savons produire des ontologies de compétences (Desmoulins, 2010), ou utiliser des ontologies dans le domaine des HN (Toyoshima, 2019), nous ne disposons ni d’ontologies, ni de plateforme de référence dans le champ « humanités numériques et éducation » (HNE). Enfin, les données structurées issues des SHS sont rarement valorisées comme objets pédagogiques. La recherche en intelligence artificielle (IA) s’est fortement développé ces dernières années (plan d’investissement français 1,5 md € en France en 2018). Le cadre d’applications ou framework Whyis1 est une solution pour construire une plateforme intelligente dédiées aux HNE. Il permet d’extraire d’une ressource une unité minimale d’information, la nanopublication, pour effectuer des inférences. Il sait traiter des sources de données hétérogènes ainsi que le langage naturel, manipuler des graphes de connaissances communes pour répondre aux questions des enseignants et des chercheurs.
    [Show full text]
  • Ontology for Information Systems (O4IS) Design Methodology Conceptualizing, Designing and Representing Domain Ontologies
    Ontology for Information Systems (O4IS) Design Methodology Conceptualizing, Designing and Representing Domain Ontologies Vandana Kabilan October 2007. A Dissertation submitted to The Royal Institute of Technology in partial fullfillment of the requirements for the degree of Doctor of Technology . The Royal Institute of Technology School of Information and Communication Technology Department of Computer and Systems Sciences IV DSV Report Series No. 07–013 ISBN 978–91–7178–752–1 ISSN 1101–8526 ISRN SU–KTH/DSV/R– –07/13– –SE V All knowledge that the world has ever received comes from the mind; the infinite library of the universe is in our own mind. – Swami Vivekananda. (1863 – 1902) Indian spiritual philosopher. The whole of science is nothing more than a refinement of everyday thinking. – Albert Einstein (1879 – 1955) German-Swiss-U.S. scientist. Science is a mechanism, a way of trying to improve your knowledge of na- ture. It’s a system for testing your thoughts against the universe, and seeing whether they match. – Isaac Asimov. (1920 – 1992) Russian-U.S. science-fiction author. VII Dedicated to the three KAs of my life: Kabilan, Rithika and Kavin. IX Abstract. Globalization has opened new frontiers for business enterprises and human com- munication. There is an information explosion that necessitates huge amounts of informa- tion to be speedily processed and acted upon. Information Systems aim to facilitate human decision-making by retrieving context-sensitive information, making implicit knowledge ex- plicit and to reuse the knowledge that has already been discovered. A possible answer to meet these goals is the use of Ontology.
    [Show full text]
  • Bringing Semantics to Web Services with OWL-S
    World Wide Web (2007) 10:243–277 DOI 10.1007/s11280-007-0033-x Bringing Semantics to Web Services with OWL-S David Martin & Mark Burstein & Drew McDermott & Sheila McIlraith & Massimo Paolucci & Katia Sycara & Deborah L. McGuinness & Evren Sirin & Naveen Srinivasan Received: 17 July 2005 /Revised: 2 March 2006 / Accepted: 30 March 2007 / Published online: 3 July 2007 # Springer Science + Business Media, LLC 2007 Abstract Current industry standards for describing Web Services focus on ensuring interoperability across diverse platforms, but do not provide a good foundation for automating the use of Web Services. Representational techniques being developed for the Semantic Web can be used to augment these standards. The resulting Web Service specifications enable the development of software programs that can interpret descriptions This work was performed while Paolucci was at the Robotics Institute, Carnegie Mellon University, Sirin was at the University of Maryland, College Park, and Srinivasan was at the Robotics Institute, Carnegie Mellon University. D. Martin (*) Artificial Intelligence Center, SRI International, Menlo Park, CA, USA e-mail: [email protected] M. Burstein Intelligent Distributed Computing Department, BBN Technologies, Cambridge, MA, USA D. McDermott Computer Science Department, Yale University, New Haven, CT, USA S. McIlraith Department of Computer Science, University of Toronto, Toronto, Canada M. Paolucci DoCoMo Communications Laboratories Europe, Munich, Germany K. Sycara Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA D. L. McGuinness Knowledge Systems, Artificial Intelligence Laboratory, Stanford University, Stanford, CA, USA E. Sirin Clark+Parsia, LLC, Arlington, VA, USA N. Srinivasan webMethods, Inc., Fairfax, VA, USA 244 World Wide Web (2007) 10:243–277 of unfamiliar Web Services and then employ those services to satisfy user goals.
    [Show full text]
  • The Role of Frame-Based Representation on the Semantic Web
    The Role of Frame-Based Representation on the Semantic Web Ora Lassila1 & Deborah McGuinness2 1Software Technology Laboratory, Nokia Research Center 2Knowledge Systems Laboratory, Stanford University Abstract A new architecture for the World Wide Web is emerging, known as the Semantic Web. In broad terms, it encompasses efforts to populate the Web with content which has formal semantics. This will enable automated agents to reason about Web content, and produce an intelligent response to unforeseen situations. We believe that in order to build the Semantic Web, the sharing of ontological information is required. This allows agents to reach partial shared understanding and thus interoperate. We acknowledge that the World Wide Web Consortium's RDF formalism (and the DARPA Agent Markup Language as its extension) can be seen as adhering to the frame-based representation paradigm, and we will further elaborate on the suitability of this paradigm for building ontologies as well as representing and sharing knowledge on the Web. The paper will discuss required and desirable features of ontological languages, giving examples of the possible usage of frame-based representation and ontologies on the Semantic Web. Introduction: Frame-based Representation Systems The term “Semantic Web” encompasses efforts to build a new world wide web (WWW) architecture that augments content with formal semantics thereby producing content suitable for automated systems to consume, as opposed to content intended for human consumption [Berners-Lee et al 2001]. The Semantic Web will allow us to use more automated functions (reasoning, information and service discovery, autonomous agents, etc.) on the Web, easing the workload of humans.
    [Show full text]
  • James A. Hendler, Phd
    James A. Hendler, PhD Tetherless World Professor & Director, Rensselaer Institute for Data Exploration and Applications Rensselaer Polytechnic Institute [email protected] US citizen, Security Clearance (on request) 518-276-4401 phone Social Security # (on request) 518-276-4464 Fax http://www.cs.rpi.edu/~hendler Twitter: @jahendler Education May, 1986 Department of Computer Science, Brown University, Providence, Rhode Island. PhD -- Computer Science, Artificial Intelligence. Thesis title: Integrating Marker-Passing and Problem-Solving: A Spreading Activation Approach to Improved Choice in Planning. May, 1983 Department of Computer Science, Brown University, Providence, Rhode Island. ScM -- Computer Science, Artificial Intelligence. Thesis project: Implementation of a pseudo-parallel marker-passing system within a frame representation language. May, 1982 Psychology Department, Southern Methodist University, Dallas, Tx. MS -- Cognitive Psychology, Human Factors Engineering. Thesis title: The Effects of a System-Imposed Grammatical Restriction on Interactive Natural Language Dialog May, 1978 Department of Computer Science, Yale University, New Haven, Ct. BS -- Computer Science, Artificial Intelligence. Experience in Higher Education 2007–pres. Rensselaer Polytechnic University (RPI) 1/07 – pres, Tetherless World Constellation Chair (Endowed), joint positions in computer and cognitive science departments 9/10 – 7/12, Program Director, Information Technology and Web Science 7/12 – 9/13, Department Head, Computer Science 9/13 –pres, Director, Institute for Data Exploration and Applications Affiliate faculty, Experimental Media and Performing Arts Center (2009- ) Affiliate, Industrial and System Engineering (2015 - ) Affiliate faculty, Center for Materials, Devices, and Integrated Systems (2015- ) 1 1986-12/06 University of Maryland, College Park 8/99-12/06. Full Professor, 8/92-7/99. Associate Professor 1/86-8/92, Assistant Professor Director, Joint Institute for Knowledge Discovery, 1/04-12/06.
    [Show full text]
  • September Gsat 03
    2011 Annual Meeting & Exposition poster included with this issue! VOL. 20, No. 12 A PUBLICATION OF THE GEOLOGICAL SOCIETY OF AMERICA DECEMBER 2010 Geoinformatics: Transforming data to knowledge for geosciences Inside: ▲ Call for Proposals: 2011 Geological Society of America Annual Meeting & Exposition, p. 12 ▲ Penrose Conference Report: Origin and Uplift of the Sierra Nevada, California,USA, p. 18 ▲ First Announcement and Call for Papers: 2011 GSA South-Central Section Meeting, p. 24 ▲ Second Announcement: 2011 Joint Meeting of GSA’s North-Central and Northeastern Sections, p. 26 VOLUME 20, NUMBER 12 ▲ DECEMBER 2010 SCIENCE ARTICLE GSA TODAY publishes news and information for more than 22,000 GSA members and subscribing libraries. GSA TODAY 4 Geoinformatics: Transforming data to (ISSN 1052-5173 USPS 0456-530) is published 11 times per year, monthly, with a combined April/May issue, by The knowledge for geosciences Geological Society of America®, Inc., with offices at 3300 A. Krishna Sinha, Zaki Malik, Abdelmou- Penrose Place, Boulder, Colorado. Mailing address: P.O. Box 9140, Boulder, CO 80301-9140, USA. Periodicals postage paid naam Rezgui, Calvin G. Barnes, Kai Lin, at Boulder, Colorado, and at additional mailing offices. Grant Heiken, William A. Thomas, Linda C. Postmaster: Send address changes to GSA Today, GSA Sales and Service, P.O. Box 9140, Boulder, CO 80301-9140, Gundersen, Robert Raskin, Ian Jackson, USA. GSA provides this and other forums for the presentation Peter Fox, Deborah McGuinness, Dogan of diverse opinions and positions by scientists worldwide, Seber, and Herman Zimmerman regardless of their race, citizenship, gender, religion, or political viewpoint. Opinions presented in this publication do not reflect official positions of the Society.
    [Show full text]
  • Research +Thought Leadership +Education
    REVIEW 2011 research + thought leadership + education www.webscience.org Web Science Trust The Web Science Trust is an independent charitable body. It was established in 2009 to raise awareness of Web Science, and to build contents the foundations and framework for this important new discipline. The origins of the Trust are found in the Web Science Research Initiative (WSRI) set up in 2006 between the Massachusetts Institute 04 Foreword of Technology and the University of Southampton. WSRI’s aims were to coordinate and support the study of the World Wide Web, 05 Directors and Trustees Report a role now assumed by the Web Science Trust. 06 Web Science: a new frontier The Web Science Trust’s main aim is to advance education and research in Web Science for the benefit of society. To this end, the 08 Achievements and Activities Trust promotes and encourages multidisciplinary and collaborative + Research research; provides thought leadership through a global forum of interested individuals, institutions and companies; and supports + Thought Leadership curriculum development in universities and research institutions + Influence to train future generations of Web Scientists. These activities are + Education intended to improve the visibility and understanding of Web Science, and the issues it raises, amongst key international constituencies, 16 Partners and Supporters including governments, industry, public and private sector enterprises, the media and the general public. 18 WSTNet The Web Science Trust is continuing to meet these objectives
    [Show full text]
  • From SHIQ and RDF to OWL: the Making of a Web Ontology Language
    From SHIQ and RDF to OWL: The Making of a Web Ontology Language Ian Horrocks,1 Peter F. Patel-Schneider,2 and Frank van Harmelen3 1 Department of Computer Science University of Manchester Oxford Road, Manchester M13 9PL, UK Email: [email protected] 2 Bell Labs Research Lucent Technologies 600 Mountain Avenue, Murray Hill, New Jersey 07974 U.S.A. Email: [email protected] 3 AI Department Vrije Universiteit Amsterdam de Boelelaan 1081a, 1081HV Amsterdam, The Netherlands Email: [email protected] Abstract. The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Descrip- tion Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic Web. In this paper we discuss how the philosophy and features of OWL can be traced back to these older for- malisms, with modifications driven by several other constraints on OWL. Several interesting problems have arisen where these influences on OWL have clashed. Keywords: Ontologies, Semantic Web, Description Logics, Frames, RDF. 1 Introduction OWL [10] is a new ontology language for the Semantic Web, developed by the World Wide Web Consortium (W3C) Web Ontology Working Group. OWL was primarily designed to represent information about categories of objects and how objects are interrelated—the sort of information that is often called an ontology. OWL can also represent information about the objects themselves—the sort of information that is often thought of as data. OWL was not designed in a vacuum.
    [Show full text]