Ontology Evaluation
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UNIVERSITY of CALGARY Concept-Learning Supported
UNIVERSITY OF CALGARY Concept-Learning Supported Semantic Search using Multi-Agent System by Cheng Zhong A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING CALGARY, ALBERTA April, 2009 © Cheng Zhong 2009 ISBN: 978-0-494-51171-8 UNIVERSITY OF CALGARY FACULTY OF GRADUATE STUDIES The undersigned certify that they have read, and recommend to the Faculty of Graduate Studies for acceptance, a thesis entitled "Concept-Learning Supported Semantic Search using Multi-Agent System" submitted by Cheng Zhong in partial fulfilment of the requirements of the degree of Master of Science. Supervisor, Dr. B. H. Far Department of Electrical and Computer Engineering Dr. M. Moussavi Department of Electrical and Computer Engineering Dr. D. Krishnamurthy Department of Electrical and Computer Engineering Dr. Y. Hu Department of Electrical and Computer Engineering Dr. M. Ghaderi Department of Computer Science Date ii Abstract Currently, the mainstream of semantic search is based on both centralized networking that could be barrier to access trillions of dynamically generated bytes on individual websites, and group commitment to a common ontology that is often too strong or unrealistic. In real world, it is preferred to enable stakeholders of knowledge to exchange information freely while they keep their own individual ontology. While this assumption makes stakeholders represent their knowledge more independently and gives them more flexibility, it brings complexity to the communication among them. To solve this communication complexity, in this thesis, we present (1) a method for semantic search supported by ontological concept learning, and (2) a prototype multi-agent system that can handle semantic search and encapsulate the complexity of such process from the users. -
Deep Semantics in the Geosciences: Semantic Building Blocks for a Complete Geoscience Infrastructure
Deep Semantics in the Geosciences: semantic building blocks for a complete geoscience infrastructure Brandon Whitehead,1,2 Mark Gahegan1 1Centre for eResearch 2 Institute of Earth Science and Engineering The University of Auckland, Private Bag 92019, Auckland, New Zealand {b.whitehead, m.gahegan}@auckland.ac.nz Abstract. In the geosciences, the semantic models, or ontologies, available are typically narrowly focused structures fit for single purpose use. In this paper we discuss why this might be, with the conclusion that it is not sufficient to use semantics simply to provide categorical labels for instances—because of the interpretive and uncertain nature of geoscience, researchers need to understand how a conclusion has been reached in order to have any confidence in adopting it. Thus ontologies must address the epistemological questions of how (and possibly why) something is ‘known’. We provide a longer justification for this argument, make a case for capturing and representing these deep semantics, provide examples in specific geoscience domains and briefly touch on a visualisation program called Alfred that we have developed to allow researchers to explore the different facets of ontology that can support them applying value judgements to the interpretation of geological entities. Keywords: geoscience, deep semantics, ontology-based information retrieval 1 Introduction From deep drilling programs and large-scale seismic surveys to satellite imagery and field excursions, geoscience observations have traditionally been expensive to capture. As such, many disciplines related to the geosciences have relied heavily on inferential methods, probability, and—most importantly—individual experience to help construct a continuous (or, more complete) description of what lies between two data values [1]. -
A Logical Framework for Modularity of Ontologies∗
A Logical Framework for Modularity of Ontologies∗ Bernardo Cuenca Grau, Ian Horrocks, Yevgeny Kazakov and Ulrike Sattler The University of Manchester School of Computer Science Manchester, M13 9PL, UK {bcg, horrocks, ykazakov, sattler }@cs.man.ac.uk Abstract ontology itself by possibly reusing the meaning of external symbols. Hence by merging an ontology with external on- Modularity is a key requirement for collaborative tologies we import the meaning of its external symbols to de- ontology engineering and for distributed ontology fine the meaning of its local symbols. reuse on the Web. Modern ontology languages, To make this idea work, we need to impose certain con- such as OWL, are logic-based, and thus a useful straints on the usage of the external signature: in particular, notion of modularity needs to take the semantics of merging ontologies should be “safe” in the sense that they ontologies and their implications into account. We do not produce unexpected results such as new inconsisten- propose a logic-based notion of modularity that al- cies or subsumptions between imported symbols. To achieve lows the modeler to specify the external signature this kind of safety, we use the notion of conservative exten- of their ontology, whose symbols are assumed to sions to define modularity of ontologies, and then prove that be defined in some other ontology. We define two a property of some ontologies, called locality, can be used restrictions on the usage of the external signature, to achieve modularity. More precisely, we define two no- a syntactic and a slightly less restrictive, seman- tions of locality for SHIQ TBoxes: (i) a tractable syntac- tic one, each of which is decidable and guarantees tic one which can be used to provide guidance in ontology a certain kind of “black-box” behavior, which en- editing tools, and (ii) a more general semantic one which can ables the controlled merging of ontologies. -
Bridging the Gap Between User Generated Spatial Content and the Semantic Web
Gianfranco Gliozzo Msc GIMA Master thesis Bridging the gap between user generated spatial content and the semantic web Bridging the gap between user generated spatial content and the semantic web Master of Science Thesis Gianfranco Gliozzo December 10 th 2010 Professor: Prof. Dr. M.J. (Menno-Jan) Kraak, Department of Geoinformation Processing Faculty of Geoinformation Science and Earth Observation University of Twente Supervisor: Dr. Ir. Rob Lemmens Department of Geoinformation Processing Faculty of Geo-Information Science and Earth Observation University of Twente Supervisor: Aldo Gangemi Senior Researcher Semantic Technology Lab (STLab) Institute for Cognitive Science and Technology, Italian National Research Council (ISTC-CNR) Reviewer: Mw. drs. M.E. (Marian) de Vries OTB Research Institute for the Built Environment Delft University of technology i Gianfranco Gliozzo Msc GIMA Master thesis Bridging the gap between user generated spatial content and the semantic web ii Gianfranco Gliozzo Msc GIMA Master thesis Bridging the gap between user generated spatial content and the semantic web Acknowledgments The present work could not have been completed without the loving support of my parents and my sister, old and new friends made on the occasion of the thesis. Let me quote my cousin, Alfio, always ready to stimulate and to suggest visions from a different perspective, he is the “guilty”, who suggested me the way of the semantic web and introduced me to Aldo Gangemi. Aldo Gangemi I will always be grateful for his generous support. The fantastic community of OpenStreetMap with in particular I want to thank simone (Simone Cortesi) for our long and pleasant conversations on OpenStreetMap story and perspectives and for his kind suggestions, tosky as well (Luigi Toscano) and David Paleino for their generous and tireless support in the struggle with open source applications and operating systems. -
Deciding Semantic Matching of Stateless Services∗
Deciding Semantic Matching of Stateless Services∗ Duncan Hull†, Evgeny Zolin†, Andrey Bovykin‡, Ian Horrocks†, Ulrike Sattler†, and Robert Stevens† School of Computer Science, Department of Computer Science, † ‡ University of Manchester, UK University of Liverpool, UK Abstract specifying automated reasoning algorithms for such stateful service descriptions is basically impossible in the presence We present a novel approach to describe and reason about stateless information processing services. It can of any expressive ontology (Baader et al. 2005). Stateless- be seen as an extension of standard descriptions which ness implies that we do not need to formulate pre- and post- makes explicit the relationship between inputs and out- conditions since our services do not change the world. puts and takes into account OWL ontologies to fix the The question we are interested in here is how to help the meaning of the terms used in a service description. This biologist to find a service he or she is looking for, i.e., a allows us to define a notion of matching between ser- service that works with inputs and outputs the biologist can vices which yields high precision and recall for service provide/accept, and that provides the required functionality. location. We explain why matching is decidable, and The growing number of publicly available biomedical web provide biomedical example services to illustrate the utility of our approach. services, 3000 as of February 2006, required better match- ing techniques to locate services. Thus, we are concerned with the question of how to describe a service request Q Introduction and service advertisements Si such that the notion of a ser- Understanding the data generated from genome sequenc- vice S matching the request Q can be defined in a “useful” ing projects like the Human Genome Project is recognised way. -
Ontology-Based Methods for Analyzing Life Science Data
Habilitation a` Diriger des Recherches pr´esent´ee par Olivier Dameron Ontology-based methods for analyzing life science data Soutenue publiquement le 11 janvier 2016 devant le jury compos´ede Anita Burgun Professeur, Universit´eRen´eDescartes Paris Examinatrice Marie-Dominique Devignes Charg´eede recherches CNRS, LORIA Nancy Examinatrice Michel Dumontier Associate professor, Stanford University USA Rapporteur Christine Froidevaux Professeur, Universit´eParis Sud Rapporteure Fabien Gandon Directeur de recherches, Inria Sophia-Antipolis Rapporteur Anne Siegel Directrice de recherches CNRS, IRISA Rennes Examinatrice Alexandre Termier Professeur, Universit´ede Rennes 1 Examinateur 2 Contents 1 Introduction 9 1.1 Context ......................................... 10 1.2 Challenges . 11 1.3 Summary of the contributions . 14 1.4 Organization of the manuscript . 18 2 Reasoning based on hierarchies 21 2.1 Principle......................................... 21 2.1.1 RDF for describing data . 21 2.1.2 RDFS for describing types . 24 2.1.3 RDFS entailments . 26 2.1.4 Typical uses of RDFS entailments in life science . 26 2.1.5 Synthesis . 30 2.2 Case study: integrating diseases and pathways . 31 2.2.1 Context . 31 2.2.2 Objective . 32 2.2.3 Linking pathways and diseases using GO, KO and SNOMED-CT . 32 2.2.4 Querying associated diseases and pathways . 33 2.3 Methodology: Web services composition . 39 2.3.1 Context . 39 2.3.2 Objective . 40 2.3.3 Semantic compatibility of services parameters . 40 2.3.4 Algorithm for pairing services parameters . 40 2.4 Application: ontology-based query expansion with GO2PUB . 43 2.4.1 Context . 43 2.4.2 Objective . -
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]. -
Proceedings of the 11Th International Workshop on Ontology
Proceedings of the 11th International Workshop on Ontology Matching (OM-2016) Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Ryutaro Ichise To cite this version: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, et al.. Proceedings of the 11th International Workshop on Ontology Matching (OM-2016). Ontology matching workshop, Kobe, Japan. No commercial editor., pp.1-252, 2016. hal-01421835 HAL Id: hal-01421835 https://hal.inria.fr/hal-01421835 Submitted on 15 Jul 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Ontology Matching OM-2016 Proceedings of the ISWC Workshop Introduction Ontology matching1 is a key interoperability enabler for the semantic web, as well as a useful tactic in some classical data integration tasks dealing with the semantic hetero- geneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those on- tologies. These correspondences can be used for various tasks, such as ontology merg- ing, data translation, query answering or navigation on the web of data. Thus, matching ontologies enables the knowledge and data expressed in the matched ontologies to in- teroperate. -
HA-Bio New 2010
Howard Alden- Jazz Guitarist “He may be the best of his generation,” writes Owen Cordle in JAZZ TIMES. George Kanzler of the NEWARK STAR LEDGER proclaims that he is “the most impressive and creative member of a new generation of jazz guitarists.” And Chip Deffaa of the NEW YORK POST observes that he is “ ...one of the very finest young guitarists working today.” It seems that the only thing regarding Howard Alden on which the critics have debate is whether the remarkable jazz guitarist is one of the best or simply the best. Born in Newport Beach, California, in 1958, Howard began playing at age ten, inspired by recordings of Louis Armstrong, Count Basie and Benny Goodman, as well as those by guitarists Barney Kessel, Charlie Christian, Django Reinhardt and George Van Eps. Soon he was working professionally around Los Angeles playing in groups ranging from traditional to mainstream to modern jazz. In 1979, Alden went east, for a summer in Atlantic City with vibraphone legend Red Norvo, and continued to perform with him frequently for several years. Upon moving to New York City in 1982, Aldenʼs skills, both as soloist and accompanist, were quickly recognized and sought-out for appearances and recordings with such artists as Joe Bushkin, Ruby Braff, Joe Williams, Warren Vache` and Woody Herman. He has continued to win accolades from critics and musicians alike, adding Benny Carter, Flip Phillips, Mel Powell, Bud Freeman, Kenny Davern, Clark Terry, Dizzy Gillespie and George Van Eps, as well as notable contemporaries such as Scott Hamilton and Ken Peplowski to his list of impressive credits. -
Introduction to Ontologies Part I
EMMC The European Materials Modelling Council Introduction to Ontologies Part I Alexandra Simperler On-line 29.4.2019 https://emmc.info/ EMMC The EMMO round table Emanuele Ghedini (University of Bologna) Gerhard Goldbeck Adham Hashibon (Goldbeck Consulting) (Fraunhofer Institut) Georg J. Schmitz Jesper Friis (Access) (SINTEF) EMMC Outline • Taxonomy vs Ontology • The value of ontologies • Semantic Technologies • Representation of Ontologies What’s the difference between an EMMC ontology and a taxonomy? TAXONOMY ONTOLOGY • Like a tree with branches • Like a spiderweb • Parent – Child relation, • Manifold of relations, is_a adds non is_a relations • Generally limited to a • Not limited to a specific specific subject area subject area • Hierarchy of (simple) • Complex relations with concepts complex concepts EMMC The Value of Semantic Technologies • Natural perspective of human communication • Greater expressivity than a database • Improved logical structure • Knowledge layer is separated from data layer • Flexibility, reusability, interoperability • Hierarchies, relationships and annotation • Search patterns can be stored, share, reused • Reasoning – answers to what-if, if-then questions • Accessible to Artificial Intelligence EMMC The Value of Ontology in the Materials Field Artificial Intelligence Materials Ontology will contribute to: Semantic Web Systems Engineering • High throughput experiments Biomedical Informatics • High throughput characterization Library Science • Cost reduction Enterprise Bookmarking Information Architecture • Reliable results • Standard operation procedures (SOPs) • Design of materials with improved characteristics All these fields create Ontologies to limit • Classification of techniques and complexity and acceleration of results organize information. The Ontology can then • Uniform query interface be applied to problem solving. EMMC Examples/Use of Ontologies • Database integration – Connected data! Discover new trends – Takahashi, et al (2018). -
Ech-0205 V1.0 Linked Open Data
E-Government Standards Page 1 of 49 eCH-0205 Linked Open Data Name Linked Open Data eCH-number eCH-0205 Category Accessory Document Quality stage Defined Version 1.0 Status Approved Decision on 2018-03-06 Date of issue 2018-03-13 Replaces version - Requirements - Annexes - Languages English (original) Authors Members of the eCH Specialized Group “Open Government Data” Main Author: Beat Estermann, Berner Fachhochschule [email protected] For a list of further contributors, see Annex B. Editor / Distribution eCH registered association, Mainaustrasse 30, Postfach [P.O. Box], 8034 Zürich T 044 388 74 64, F 044 388 71 80 www.ech.ch / [email protected] eCH registered association www.ech.ch / [email protected] eCH-0205 Linked Open Data / 1.0 / Approved / 2018-03-13 E-Government Standards Page 2 of 49 Summary This document provides the Swiss Linked Data community with a shared vision of the state of linked open data publication in the public and heritage sectors in Switzerland and gives people who are new to the community a first overview of previous and ongoing activities in the area of data publication, data use, and know-how exchange. The document contains a short introduction to linked (open) data, gives a detailed account of what linked data publica- tion is about, provides an overview of the present state of linked data publication by Swiss public and heritage sector organizations, and presents a series of exemplary use cases that serve as test and study cases to tackle current challenges and demonstrate the usefulness of linked (open) data in practice. -
A Little More Than a Year After Suffering a Stroke and Undergoing Physical Therapy at Kessler Institute Buddy Terry Blows His Sax Like He Never Missed a Beat
Volume 39 • Issue 10 November 2011 Journal of the New Jersey Jazz Society Dedicated to the performance, promotion and preservation of jazz. Saxman Buddy Terry made his first appearance with Swingadelic in more than a year at The Priory in Newark on September 30. Enjoying his return are Audrey Welber and Jeff Hackworth. Photo by Tony Mottola. Back in the Band A little more than a year after suffering a stroke and undergoing physical therapy at Kessler Institute Buddy Terry blows his sax like he never missed a beat. Story and photos on page 30. New JerseyJazzSociety in this issue: NEW JERSEY JAZZ SOCIETY Prez Sez . 2 Bulletin Board . 2 NJJS Calendar . 3 Pee Wee Dance Lessons. 3 Jazz Trivia . 4 Editor’s Pick/Deadlines/NJJS Info . 6 Prez Sez September Jazz Social . 51 CD Winner . 52 By Laura Hull President, NJJS Crow’s Nest . 54 New/Renewed Members . 55 hanks to Ricky Riccardi for joining us at the ■ We invite you to mark your calendar for “The Change of Address/Support NJJS/Volunteer/JOIN NJJS . 55 TOctober Jazz Social. We enjoyed hearing Stomp” — the Pee Wee Russell Memorial Stomp about his work with the Louis Armstrong House that is — taking place Sunday, March 4, 2012 at STORIES Buddy Terry and Swingadelic . cover Museum and the effort put into his book — the Birchwood Manor in Whippany. Our Big Band in the Sky. 8 What a Wonderful World. These are the kinds of confirmed groups include The George Gee Swing Dan’s Den . 10 Orchestra, Emily Asher’s Garden Party, and Luna Stage Jazz.