Logics for Data and Knowledge Representation: midterm Exam 2013
|
|
- Garry Brooks
- 5 years ago
- Views:
Transcription
1 1. [6 PT] Say (mark with an X) whether the following statements are true (T) or false (F). a) In a lightweight ontology there are is-a and part-of relations T F b) Semantic matching is a technique to compute a mapping between T F nodes whose labels have similar meaning in two ontologies c) DERA is a methodology based on the faceted approach for the T F development of classification ontologies d) The Semantic Web infrastructure provides a data model supporting T F a single entity can be distributed over the Web e) RDF allows relationship propagation through rdfs:subclassof T F f) OWL 2 RL (profile) was developed to be implemented using rule based technologies such as rule extended DBMSs T F 2. [6 PT] Translate the following natural language sentences in the DL language with lowest expressiveness possible (e.g. AL, ALC, FL0 ) and say which of the languages you used: a. A parent is a person having at least one child b. Birds have 2 wings c. Male and Female are disjoint d. Germans do not have Italian friends and friends having Italian friends e. The color of a banana can be only yellow or red f. Facebook users can only post photos about their friends PARENT PERSON haschild. (AL) BIRD 2 WING 2 WING (ALN) MALE FEMALE (AL) GERMAN FRIEND-OF. ( ITALIAN FRIEND-OF.ITALIAN) (ALCE) BANANA COLOR.{yellow, red} (FL0) FACEBOOK-USER USER POST.FRIEND-PHOTO (FL0)
2 3. [2 PT] Formally explain the separation of duties RelBAC rule with an example in Description Logic See slides 4. [3 PT] List and provide a brief description of the four basic ABox reasoning services See slides
3 5. [4 PT] Using the tableau calculus, say whether the DL formula below is satisfiable: person ( person eats. plant) eats.(plant dairy) Motivate your answer with a proof. If satisfiable, provide a possible ABox. By -rule we put into the ABox: person(z), ( person eats. plant)(z), eats.(plant dairy)(z), (1) person(z) is already an ABox assertion. (2) ( person eats. plant)(z) by -rule has to be split into: (2.1) person(z) that is clearly in contradiction with (1), therefore we backtrack; (2.2) eats. plant(z) by -rule we add into the ABox: eats(z, y), plant(y) (3) eats.(plant dairy) (z) by -rule we add into the ABox: eats(z, plant(x) dairy(x)) (in fact person(z) is already in the ABox), that by -rule has to be split into: (3.1) plant(y) given that eats(z, y) is in the ABox because of (2.2), that is clearly in contradiction with plant(y) (2.2) (3.2) dairy(x) Thus, there is at least a path which proves the satisfiability of the formula, for instance: (1) (2) (2.1) (3) (3.2) This path generates the ABox A = { person(z), eats(z, y), plant(y), dairy(x) }
4 6. [4 PT] Represent the following statements in RDF: a) If Einstein is a researcher, he is also an investigator, a manofscience and a scientist. b) If John is either an experimenter or a fieldworker or a postdoc, he is also a researcher. Consult RDF modeling in slide 21 of the Resource Description Framework lecture 7. [4 PT] Suppose that in a family tree, relations such as the following ones are functional. a) :haspaternalgrandfather b) :haspaternalgrandmother Represent them in a suitable Semantic Web language and demonstrate their use with necessary entity-entity axioms. See functional property in slide 8 of the OWL lecture
5 8. [4 PT] Suppose that an RDF model represents information about various entities including books. The model is created using standard vocabularies (e.g., Dublic Core). Write a SPARQL query that separates information about books i.e. title, author, date of publication and publisher (if any) and creates another RDF model that is a subset of the original one. PREFIX dc: <dc namespace> CONSTRUCT {?book dc:creator?author.?book dc:title?booktitle.?book dc:date?dateofpublication.?book dc:publisher?pub } WHERE {?book dc:creator?author.?book dc:title?booktitle.?book dc:date?dateofpublication. OPTIONAL {?book dc:publisher?pub} }
Description Logic. Eva Mráková,
Description Logic Eva Mráková, glum@fi.muni.cz Motivation: ontology individuals/objects/instances ElizabethII Philip Philip, Anne constants in FOPL concepts/classes/types Charles Anne Andrew Edward Male,
More informationDescription Logics and OWL
Description Logics and OWL Based on slides from Ian Horrocks University of Manchester (now in Oxford) Where are we? OWL Reasoning DL Extensions Scalability OWL OWL in practice PL/FOL XML RDF(S)/SPARQL
More informationLogik für Informatiker Logic for computer scientists. Ontologies: Description Logics
Logik für Informatiker for computer scientists Ontologies: Description s WiSe 2009/10 Ontology languages description logics (efficiently decidable fragments of first-order logic) used for domain ontologies
More informationOWL a glimpse. OWL a glimpse (2) requirements for ontology languages. requirements for ontology languages
OWL a glimpse OWL Web Ontology Language describes classes, properties and relations among conceptual objects lecture 7: owl - introduction of#27# ece#720,#winter# 12# 2# of#27# OWL a glimpse (2) requirements
More informationSemantic Web Test
Semantic Web Test 24.01.2017 Group 1 No. A B C D 1 X X X 2 X X 3 X X 4 X X 5 X X 6 X X X X 7 X X 8 X X 9 X X X 10 X X X 11 X 12 X X X 13 X X 14 X X 15 X X 16 X X 17 X 18 X X 19 X 20 X X 1. Which statements
More informationINF3580/4580 Semantic Technologies Spring 2017
INF3580/4580 Semantic Technologies Spring 2017 Lecture 9: Model Semantics & Reasoning Martin Giese 13th March 2017 Department of Informatics University of Oslo Today s Plan 1 Repetition: RDF semantics
More informationDescription Logic: A Formal Foundation for Ontology Languages and Tools
Description Logic: A Formal Foundation for Ontology Languages and Tools Part 2: Tools Ian Horrocks Information Systems Group Oxford University Computing Laboratory Contents
More informationOWL DL / Full Compatability
Peter F. Patel-Schneider, Bell Labs Research Copyright 2007 Bell Labs Model-Theoretic Semantics OWL DL and OWL Full Model Theories Differences Betwen the Two Semantics Forward to OWL 1.1 Model-Theoretic
More informationA faceted lightweight ontology for Earthquake Engineering Research Projects and Experiments
Eng. Md. Rashedul Hasan email: md.hasan@unitn.it Phone: +39-0461-282571 Fax: +39-0461-282521 SERIES Concluding Workshop - Joint with US-NEES JRC, Ispra, May 28-30, 2013 A faceted lightweight ontology for
More informationSimplified Approach for Representing Part-Whole Relations in OWL-DL Ontologies
Simplified Approach for Representing Part-Whole Relations in OWL-DL Ontologies Pace University IEEE BigDataSecurity, 2015 Aug. 24, 2015 Outline Ontology and Knowledge Representation 1 Ontology and Knowledge
More informationSemantics. Matthew J. Graham CACR. Methods of Computational Science Caltech, 2011 May 10. matthew graham
Semantics Matthew J. Graham CACR Methods of Computational Science Caltech, 2011 May 10 semantic web The future of the Internet (Web 3.0) Decentralized platform for distributed knowledge A web of databases
More informationKnowledge Representations. How else can we represent knowledge in addition to formal logic?
Knowledge Representations How else can we represent knowledge in addition to formal logic? 1 Common Knowledge Representations Formal Logic Production Rules Semantic Nets Schemata and Frames 2 Production
More informationPresented By Aditya R Joshi Neha Purohit
Presented By Aditya R Joshi Neha Purohit Pellet What is Pellet? Pellet is an OWL- DL reasoner Supports nearly all of OWL 1 and OWL 2 Sound and complete reasoner Written in Java and available from http://
More informationDescription Logics as Ontology Languages for Semantic Webs
Description Logics as Ontology Languages for Semantic Webs Franz Baader, Ian Horrocks, and Ulrike Sattler Presented by:- Somya Gupta(10305011) Akshat Malu (10305012) Swapnil Ghuge (10305907) Presentation
More informationOWL and tractability. Based on slides from Ian Horrocks and Franz Baader. Combining the strengths of UMIST and The Victoria University of Manchester
OWL and tractability Based on slides from Ian Horrocks and Franz Baader Where are we? OWL Reasoning DL Extensions Scalability OWL OWL in practice PL/FOL XML RDF(S)/SPARQL Practical Topics Repetition: DL
More informationOntologies and the Web Ontology Language OWL
Chapter 7 Ontologies and the Web Ontology Language OWL vocabularies can be defined by RDFS not so much stronger than the ER Model or UML (even weaker: no cardinalities) not only a conceptual model, but
More informationH1 Spring B. Programmers need to learn the SOAP schema so as to offer and use Web services.
1. (24 points) Identify all of the following statements that are true about the basics of services. A. If you know that two parties implement SOAP, then you can safely conclude they will interoperate at
More informationKnowledge-Driven Video Information Retrieval with LOD
Knowledge-Driven Video Information Retrieval with LOD Leslie F. Sikos, Ph.D., Flinders University ESAIR 15, 23 October 2015 Melbourne, VIC, Australia Knowledge-Driven Video IR Outline Video Retrieval Challenges
More informationOntologies and OWL. Riccardo Rosati. Knowledge Representation and Semantic Technologies
Knowledge Representation and Semantic Technologies Ontologies and OWL Riccardo Rosati Corso di Laurea Magistrale in Ingegneria Informatica Sapienza Università di Roma 2016/2017 The Semantic Web Tower Ontologies
More informationl A family of logic based KR formalisms l Distinguished by: l Decidable fragments of FOL l Closely related to Propositional Modal & Dynamic Logics
What Are Description Logics? Description Logics l A family of logic based KR formalisms Descendants of semantic networks and KL-ONE Describe domain in terms of concepts (classes), roles (relationships)
More informationBryan Smith May 2010
Bryan Smith May 2010 Tool (Onto2SMem) to generate declarative knowledge base in SMem from ontology Sound (if incomplete) inference Proof of concept Baseline implementation Semantic memory (SMem) Store
More informationOWL 2 Profiles. An Introduction to Lightweight Ontology Languages. Markus Krötzsch University of Oxford. Reasoning Web 2012
University of Oxford Department of Computer Science OWL 2 Profiles An Introduction to Lightweight Ontology Languages Markus Krötzsch University of Oxford Reasoning Web 2012 Remark for the Online Version
More informationGenetic Programming. and its use for learning Concepts in Description Logics
Concepts in Description Artificial Intelligence Institute Computer Science Department Dresden Technical University May 29, 2006 Outline Outline: brief introduction to explanation of the workings of a algorithm
More informationINF3580 Semantic Technologies Spring 2012
INF3580 Semantic Technologies Spring 2012 Lecture 10: OWL, the Web Ontology Language Martin G. Skjæveland 20th March 2012 Department of Informatics University of Oslo Outline Reminder: RDFS 1 Reminder:
More informationCOMP718: Ontologies and Knowledge Bases
1/35 COMP718: Ontologies and Knowledge Bases Lecture 9: Ontology/Conceptual Model based Data Access Maria Keet email: keet@ukzn.ac.za home: http://www.meteck.org School of Mathematics, Statistics, and
More informationOWL 2 The Next Generation. Ian Horrocks Information Systems Group Oxford University Computing Laboratory
OWL 2 The Next Generation Ian Horrocks Information Systems Group Oxford University Computing Laboratory What is an Ontology? What is an Ontology? A model of (some aspect
More informationLocal Closed World Reasoning with OWL 2
Local Closed World Reasoning with OWL 2 JIST 2011 Tutorial Jeff Z. Pan Department of Computing Science University of Aberdeen, UK Agenda 1. Brief introduction to Ontology and OWL 2 (10m) 2. Open vs. Closed
More informationDescription Logics. Description Logics and Databases
1 + Description Logics Description Logics and Databases Enrico Franconi Department of Computer Science University of Manchester http://www.cs.man.ac.uk/~franconi 2 + Description Logics and Databases Queries
More informationINF3580/4580 Semantic Technologies Spring 2017
INF3580/4580 Semantic Technologies Spring 2017 Lecture 10: OWL, the Web Ontology Language Leif Harald Karlsen 20th March 2017 Department of Informatics University of Oslo Reminders Oblig. 5: First deadline
More information! model construction
Logics of Image Interpretation 1 Describing Image Interpretation in Logical Terms In 2D images (with possible occlusions) we never see the complete 3D reality.? deduction! model construction "from the
More informationFor return on 19 January 2018 (late submission: 2 February 2018)
Semantic Technologies Autumn 2017 Coursework For return on 19 January 2018 (late submission: 2 February 2018) Electronic submission:.pdf and.owl files only 1. (6%) Consider the following XML document:
More informationWeek 4. COMP62342 Sean Bechhofer, Uli Sattler
Week 4 COMP62342 Sean Bechhofer, Uli Sattler sean.bechhofer@manchester.ac.uk, uli.sattler@manchester.ac.uk Today Some clarifications from last week s coursework More on reasoning: extension of the tableau
More informationOntology mutation testing
Ontology mutation testing February 3, 2016 Cesare Bartolini Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg Outline 1 Mutation testing 2 Mutant generation 3
More informationBUILDING THE SEMANTIC WEB
BUILDING THE SEMANTIC WEB You might have come across the term Semantic Web Applications often, during talks about the future of Web apps. Check out what this is all about There are two aspects to the possible
More informationSemantic reasoning for dynamic knowledge bases. Lionel Médini M2IA Knowledge Dynamics 2018
Semantic reasoning for dynamic knowledge bases Lionel Médini M2IA Knowledge Dynamics 2018 1 Outline Summary Logics Semantic Web Languages Reasoning Web-based reasoning techniques Reasoning using SemWeb
More informationAI Fundamentals: Knowledge Representation and Reasoning. Maria Simi
AI Fundamentals: Knowledge Representation and Reasoning Maria Simi Description logics LESSON 6: SYNTAX AND SEMANTICS, DECISION PROBLEMS, INFERENCE Categories and objects [AIMA, Cap 12] Most of the reasoning
More informationOWL 2 Profiles. An Introduction to Lightweight Ontology Languages. Маркус Крёч (Markus Krötzsch) University of Oxford. KESW Summer School 2012
University of Oxford Department of Computer Science OWL 2 Profiles An Introduction to Lightweight Ontology Languages Маркус Крёч (Markus Krötzsch) University of Oxford KESW Summer School 2012 Remark for
More informationIntroduction to Protégé. Federico Chesani, 18 Febbraio 2010
Introduction to Protégé Federico Chesani, 18 Febbraio 2010 Ontologies An ontology is a formal, explicit description of a domain of interest Allows to specify: Classes (domain concepts) Semantci relation
More informationKnowledge Engineering with Semantic Web Technologies
This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0) Knowledge Engineering with Semantic Web Technologies Lecture 3 Ontologies and Logic 3.7 Description Logics
More informationSemantic Web. MPRI : Web Data Management. Antoine Amarilli Friday, January 11th 1/29
Semantic Web MPRI 2.26.2: Web Data Management Antoine Amarilli Friday, January 11th 1/29 Motivation Information on the Web is not structured 2/29 Motivation Information on the Web is not structured This
More information! Assessed assignment 1 Due 17 Feb. 3 questions Level 10 students answer Q1 and one other
! Assessed assignment 1 Due 17 Feb. 3 questions Level 10 students answer Q1 and one other! Q1 Understand an OWL ontology Install Protégé and download the clothing.owl ontology from the KMM website Answer
More informationlogic importance logic importance (2) logic importance (3) specializations of logic Horn logic specializations of logic RDF and OWL
logic importance - high-level language for expressing knowledge - high expressive power - well-understood formal semantics - precise notion of logical consequence - systems that can automatically derive
More informationReasoning with the Web Ontology Language (OWL)
Reasoning with the Web Ontology Language (OWL) JESSE WEAVER, PH.D. Fundamental & Computational Sciences Directorate, Senior Research Computer Scientist Discovery 2020 Short Course on Semantic Data Analysis
More informationPropositional Logic. Andreas Klappenecker
Propositional Logic Andreas Klappenecker Propositions A proposition is a declarative sentence that is either true or false (but not both). Examples: College Station is the capital of the USA. There are
More informationReasoning and Query Answering in Description Logics
Reasoning and Query Answering in Description Logics Magdalena Ortiz Vienna University of Technology AMW School, 20 May 2013 1/117 Reasoning and Querying in DLs 1. Motivation Ontologies An ontology is a
More informationStructure of This Presentation
Inferencing for the Semantic Web: A Concise Overview Feihong Hsu fhsu@cs.uic.edu March 27, 2003 Structure of This Presentation General features of inferencing for the Web Inferencing languages Survey of
More informationINF3580 Semantic Technologies Spring 2012
INF3580 Semantic Technologies Spring 2012 Lecture 12: OWL: Loose Ends Martin G. Skjæveland 10th April 2012 Department of Informatics University of Oslo Today s Plan 1 Reminder: OWL 2 Disjointness and Covering
More informationAn Introduction to the Semantic Web. Jeff Heflin Lehigh University
An Introduction to the Semantic Web Jeff Heflin Lehigh University The Semantic Web Definition The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined
More informationKnowledge Sharing Among Heterogeneous Agents
Knowledge Sharing Among Heterogeneous Agents John F. Sowa VivoMind Research, LLC 29 July 2013 Facts of Life: Diversity and Heterogeneity Open-ended variety of systems connected to the Internet: The great
More informationSemantic Web Technologies
1/57 Introduction and RDF Jos de Bruijn debruijn@inf.unibz.it KRDB Research Group Free University of Bolzano, Italy 3 October 2007 2/57 Outline Organization Semantic Web Limitations of the Web Machine-processable
More informationSEMANTICS. Retrieval by Meaning
SEMANTICS 1 Retrieval by Meaning Query: "Accident of a Mercedes" Retrieved image: Methods for retrieval by meaning: high-level image understanding beyond state-of-the-art except easy cases natural language
More informationOWL as a Target for Information Extraction Systems
OWL as a Target for Information Extraction Systems Clay Fink, Tim Finin, James Mayfield and Christine Piatko Johns Hopkins University Applied Physics Laboratory and the Human Language Technology Center
More informationKnowledge Representation for the Semantic Web
Knowledge Representation for the Semantic Web Winter Quarter 2011 Pascal Hitzler Slides 4 01/13/2010 Kno.e.sis Center Wright State University, Dayton, OH http://www.knoesis.org/pascal/ KR4SW Winter 2011
More informationToday: RDF syntax. + conjunctive queries for OWL. KR4SW Winter 2010 Pascal Hitzler 3
Today: RDF syntax + conjunctive queries for OWL KR4SW Winter 2010 Pascal Hitzler 3 Today s Session: RDF Schema 1. Motivation 2. Classes and Class Hierarchies 3. Properties and Property Hierarchies 4. Property
More informationOrchestrating Music Queries via the Semantic Web
Orchestrating Music Queries via the Semantic Web Milos Vukicevic, John Galletly American University in Bulgaria Blagoevgrad 2700 Bulgaria +359 73 888 466 milossmi@gmail.com, jgalletly@aubg.bg Abstract
More informationQuerying Data through Ontologies
Querying Data through Ontologies Instructor: Sebastian Link Thanks to Serge Abiteboul, Ioana Manolescu, Philippe Rigaux, Marie-Christine Rousset and Pierre Senellart Web Data Management and Distribution
More informationOWL-DBC The Arrival of Scalable and Tractable OWL Reasoning for Enterprise Knowledge Bases
OWL-DBC The Arrival of Scalable and Tractable OWL Reasoning for Enterprise Knowledge Bases URL: [http://trowl.eu/owl- dbc/] Copyright @2013 the University of Aberdeen. All Rights Reserved This document
More informationSEMANTIC WEB AND COMPARATIVE ANALYSIS OF INFERENCE ENGINES
SEMANTIC WEB AND COMPARATIVE ANALYSIS OF INFERENCE ENGINES Ms. Neha Dalwadi 1, Prof. Bhaumik Nagar 2, Prof. Ashwin Makwana 1 1 Computer Engineering, Chandubhai S Patel Institute of Technology Changa, Dist.
More informationThe Semantic Web Explained
The Semantic Web Explained The Semantic Web is a new area of research and development in the field of computer science, aimed at making it easier for computers to process the huge amount of information
More informationToday s Plan. INF3580 Semantic Technologies Spring Model-theoretic semantics, a quick recap. Outline
Today s Plan INF3580 Semantic Technologies Spring 2011 Lecture 6: Introduction to Reasoning with RDF 1 Martin Giese 1st March 2010 2 3 Domains, ranges and open worlds Department of Informatics University
More informationSemantic Web Systems Ontologies Jacques Fleuriot School of Informatics
Semantic Web Systems Ontologies Jacques Fleuriot School of Informatics 15 th January 2015 In the previous lecture l What is the Semantic Web? Web of machine-readable data l Aims of the Semantic Web Automated
More informationNonstandard Inferences in Description Logics
Nonstandard Inferences in Description Logics Franz Baader Theoretical Computer Science Germany Short introduction to Description Logics Application in chemical process engineering Non-standard inferences
More information4.8 Huffman Codes. These lecture slides are supplied by Mathijs de Weerd
4.8 Huffman Codes These lecture slides are supplied by Mathijs de Weerd Data Compression Q. Given a text that uses 32 symbols (26 different letters, space, and some punctuation characters), how can we
More informationOn the Reduction of Dublin Core Metadata Application Profiles to Description Logics and OWL
On the Reduction of Dublin Core Metadata Application Profiles to Description Logics and OWL Dimitrios A. Koutsomitropoulos High Performance Information Systems Lab, Computer Engineering and Informatics
More informationSemantic Web and Natural Language Processing
Semantic Web and Natural Language Processing Wiltrud Kessler Institut für Maschinelle Sprachverarbeitung Universität Stuttgart Semantic Web Winter 2014/2015 This work is licensed under a Creative Commons
More informationLecture 3: Graphs and flows
Chapter 3 Lecture 3: Graphs and flows Graphs: a useful combinatorial structure. Definitions: graph, directed and undirected graph, edge as ordered pair, path, cycle, connected graph, strongly connected
More informationDeep integration of Python with Semantic Web technologies
Deep integration of Python with Semantic Web technologies Marian Babik, Ladislav Hluchy Intelligent and Knowledge Technologies Group Institute of Informatics, SAS Goals of the presentation Brief introduction
More information(Conceptual) Clustering methods for the Semantic Web: issues and applications
(Conceptual) Clustering methods for the Semantic Web: issues and applications Nicola Fanizzi and Claudia d Amato Computer Science Department University of Bari, Italy Poznań, June 21th, 2011 Contents 1
More informationChapter 13: Advanced topic 3 Web 3.0
Chapter 13: Advanced topic 3 Web 3.0 Contents Web 3.0 Metadata RDF SPARQL OWL Web 3.0 Web 1.0 Website publish information, user read it Ex: Web 2.0 User create content: post information, modify, delete
More informationOntologies. COMP 210: Lecture 26: Ontologies. Ontologies. Ontologies. Winston s ZOOKEEPER ZOOKEEPER 4/23/2010
COMP 210: Lecture 26: Trevor Bench-Capon Room 215, Ashton Building http://www.csc.liv.ac.uk/~tbc/comp210 A problem we identified with rule based expert systems, was the lack of rigorous semantics for their
More informationAdding formal semantics to the Web
Adding formal semantics to the Web building on top of RDF Schema Jeen Broekstra On-To-Knowledge project Context On-To-Knowledge IST project about content-driven knowledge management through evolving ontologies
More informationPrinciples of Knowledge Representation and Reasoning
Principles of Knowledge Representation and Semantic Networks and Description Logics II: Description Logics Terminology and Notation Albert-Ludwigs-Universität Freiburg Bernhard Nebel, Stefan Wölfl, and
More informationAn R2RML Mapping Management API in Java. Making an API Independent of its Dependencies
An R2RML Mapping Management API in Java Making an API Independent of its Dependencies Marius Strandhaug Master s Thesis Spring 2014 Abstract When developing an Application Programming Interface (API),
More informationFOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES
FOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES Semantics of SPARQL Sebastian Rudolph Dresden, June 14 Content Overview & XML 9 APR DS2 Hypertableau II 7 JUN DS5 Introduction into RDF 9 APR DS3 Tutorial 5 11
More informationmodel (ontology) and every DRS and CMS server has a well-known address (IP and port).
7 Implementation In this chapter we describe the Decentralized Reasoning Service (DRS), a prototype service implementation that performs the cooperative reasoning process presented before. We present also
More informationOn the Scalability of Description Logic Instance Retrieval
On the Scalability of Description Logic Instance Retrieval V. Haarslev 1, R. Moeller 2, M. Wessel 2 1 Concordia University, Montreal 2 Hamburg University of Technology (TUHH) 1 Supported by EU Project
More informationSemantic Web Rules. - Tools and Languages - Holger Knublauch. Tutorial at Rule ML 2006, Athens, GA
Semantic Web Rules - Tools and Languages - Tutorial at Rule ML 2006, Athens, GA Holger Knublauch Semantic Web Languages RDF Schema OWL SWRL Jena Rules Language SPARQL RDF Triples are the common foundation
More informationA Semantic Model for Federated Queries Over a Normalized Corpus
A Semantic Model for Federated Queries Over a Normalized Corpus Samuel Croset, Christoph Grabmüller, Dietrich Rebholz-Schuhmann 17 th March 2010, Hinxton EBI is an Outstation of the European Molecular
More informationTOOP: A Common Semantic Model for the Once-Only Principle Jack Verhoosel, TNO June 14, 2018
TOOP: A Common Semantic Model for the Once-Only Principle Jack Verhoosel, TNO June 14, 2018 2 Why a TOOP Common Semantic Model? 28 member states with different terms So, let s speak in TOOP terms and use
More informationExercise 3.1 (Win-Move Game: Draw Nodes) Consider again the Win-Move-Game. There, WinNodes and LoseNodes have been axiomatized.
Semantic Web 12 3. Unit: OWL Exercise 3.1 (Win-Move Game: Draw Nodes) Consider again the Win-Move-Game. There, WinNodes and LoseNodes have been axiomatized. a) Is it possible to characterize DrawNodes
More informationMandatory exercises. INF3580/4580 Semantic Technologies Spring 2017 Lecture 12: OWL: Loose Ends. Outline. Make it simple!
Mandatory exercises INF3580/4580 Semantic Technologies Spring 2017 Lecture 12: OWL: Loose Ends Ernesto Jiménez-Ruiz 3rd April 2017 Oblig 6 published after lecture. First attempt by April 25th. Second attempt
More informationRacer - An Inference Engine for the Semantic Web
Racer - An Inference Engine for the Semantic Web Concordia University Department of Computer Science and Software Enineering http://www.cse.concordia.ca/~haarslev/ Collaboration with: Ralf Möller, Hamburg
More informationSemantics. KR4SW Winter 2011 Pascal Hitzler 1
Semantics KR4SW Winter 2011 Pascal Hitzler 1 Knowledge Representation for the Semantic Web Winter Quarter 2011 Pascal Hitzler Slides 5 01/20+25/2010 Kno.e.sis Center Wright State University, Dayton, OH
More informationDAML+OIL: an Ontology Language for the Semantic Web
DAML+OIL: an Ontology Language for the Semantic Web DAML+OIL Design Objectives Well designed Intuitive to (human) users Adequate expressive power Support machine understanding/reasoning Well defined Clearly
More informationCC LA WEB DE DATOS PRIMAVERA Lecture 4: Web Ontology Language (I) Aidan Hogan
CC6202-1 LA WEB DE DATOS PRIMAVERA 2015 Lecture 4: Web Ontology Language (I) Aidan Hogan aidhog@gmail.com PREVIOUSLY ON LA WEB DE DATOS (1) Data, (2) Rules/Ontologies, (3) Query, RDF: Resource Description
More informationSemantic Web. Ontology Pattern. Gerd Gröner, Matthias Thimm. Institute for Web Science and Technologies (WeST) University of Koblenz-Landau
Semantic Web Ontology Pattern Gerd Gröner, Matthias Thimm {groener,thimm}@uni-koblenz.de Institute for Web Science and Technologies (WeST) University of Koblenz-Landau July 18, 2013 Gerd Gröner, Matthias
More informationUsing ontologies function management
for Using ontologies function management Caroline Domerg, Juliette Fabre and Pascal Neveu 22th July 2010 O. Corby C.Faron-Zucker E.Gennari A. Granier I. Mirbel V. Negre A. Tireau Semantic Web tools Ontology
More informationLightweight Semantic Web Motivated Reasoning in Prolog
Lightweight Semantic Web Motivated Reasoning in Prolog Salman Elahi, s0459408@sms.ed.ac.uk Supervisor: Dr. Dave Robertson Introduction: As the Semantic Web is, currently, in its developmental phase, different
More informationHelmi Ben Hmida Hannover University, Germany
Helmi Ben Hmida Hannover University, Germany 1 Summarizing the Problem: Computers don t understand Meaning My mouse is broken. I need a new one 2 The Semantic Web Vision the idea of having data on the
More informationOn the use of Abstract Workflows to Capture Scientific Process Provenance
On the use of Abstract Workflows to Capture Scientific Process Provenance Paulo Pinheiro da Silva, Leonardo Salayandia, Nicholas Del Rio, Ann Q. Gates The University of Texas at El Paso CENTER OF EXCELLENCE
More informationOntology Design: OWL Constructs. Tutor: Aldo Gangemi Lecture LEX09 Fiesole, Italy
Ontology Design: OWL Constructs Tutor: Aldo Gangemi Lecture 1 @ LEX09 Fiesole, Italy Name: Aldo Gangemi Tutor info Institute: ISTC-CNR, Rome, Italy Research Group: Semantic Technology Laboratory (STLab)
More informationModularity in Ontologies: Introduction (Part A)
Modularity in Ontologies: Introduction (Part A) Thomas Schneider 1 Dirk Walther 2 1 Department of Computer Science, University of Bremen, Germany 2 Faculty of Informatics, Technical University of Madrid,
More informationOntological Modeling: Part 2
Ontological Modeling: Part 2 Terry Halpin LogicBlox This is the second in a series of articles on ontology-based approaches to modeling. The main focus is on popular ontology languages proposed for the
More informationORM and Description Logic. Dr. Mustafa Jarrar. STARLab, Vrije Universiteit Brussel, Introduction (Why this tutorial)
Web Information Systems Course University of Hasselt, Belgium April 19, 2007 ORM and Description Logic Dr. Mustafa Jarrar mjarrar@vub.ac.be STARLab, Vrije Universiteit Brussel, Outline Introduction (Why
More informationKnowledge Representation for the Semantic Web Lecture 1: Introduction
Knowledge Representation for the Semantic Web Lecture 1: Introduction Daria Stepanova Max Planck Institute for Informatics D5: Databases and Information Systems group WS 2017/18 1 / 32 Overview Organization
More informationSemantic Web. Part 3 The ontology layer 1: Ontologies, Description Logics, and OWL
Semantic Web Part 3 The ontology layer 1: Ontologies, Description Logics, and OWL Riccardo Rosati Corso di Laurea Magistrale in Ingegneria Informatica Sapienza Università di Roma 2012/2013 REMARK Most
More informationA Formal Definition of RESTful Semantic Web Services. Antonio Garrote Hernández María N. Moreno García
A Formal Definition of RESTful Semantic Web Services Antonio Garrote Hernández María N. Moreno García Outline Motivation Resources and Triple Spaces Resources and Processes RESTful Semantic Resources Example
More informationKnowledge Representation for the Semantic Web
Knowledge Representation for the Semantic Web Winter Quarter 2010 Pascal Hitzler Slides 6 02/04/2010 Kno.e.sis Center Wright State University, Dayton, OH http://www.knoesis.org/pascal/ KR4SW Winter 2010
More informationProgramming THE SEMANTIC WEB. Build an application upon Semantic Web models. Brief overview of Apache Jena and OWL-API.
Programming THE SEMANTIC WEB Build an application upon Semantic Web models. Brief overview of Apache Jena and OWL-API. Recap: Tools Editors (http://semanticweb.org/wiki/editors) Most common editor: Protégé
More informationSemantic Nets, Frames, World Representation. CS W February, 2004
Semantic Nets, Frames, World Representation CS W4701 24 February, 2004 Knowledge Representation as a medium for human expression An intelligent system must have KRs that can be interpreted by humans. We
More information