Building Knowledge about Buildings Matt Young and Eyal Amir University of Illinois, Urbana-Champaign.

Slides:



Advertisements
Similar presentations
Knowledge Representation using First-Order Logic
Advertisements

Extensibility of COREP and Compatibility between Basel II agreement and the future Directive An external analysis. Andrés Álvarez (University of Oviedo)
UNIVERSITÄT PADERBORN Die Universität der Informationsgesellschaft PeerThing P2P-based Semantic Resource Discovery Felix Heine, Matthias Hovestadt, Odej.
TU/e technische universiteit eindhoven Hera: Development of Semantic Web Information Systems Geert-Jan Houben Peter Barna Flavius Frasincar Richard Vdovjak.
CH-4 Ontologies, Querying and Data Integration. Introduction to RDF(S) RDF stands for Resource Description Framework. RDF is a standard for describing.
Land Administration, Poverty, and the Environment Further Perspectives.
Assessment and treatment of childhood topographical disorientation: A case study Jennifer Touse.
Of 27 lecture 7: owl - introduction. of 27 ece 627, winter ‘132 OWL a glimpse OWL – Web Ontology Language describes classes, properties and relations.
Database Systems: Design, Implementation, and Management Eighth Edition Chapter 6 Advanced Data Modeling.
Database Systems: Design, Implementation, and Management Tenth Edition
BIS Database Systems School of Management, Business Information Systems, Assumption University A.Thanop Somprasong Chapter # 6 Advanced Data Modeling.
Formal Methods in Software Engineering Credit Hours: 3+0 By: Qaisar Javaid Assistant Professor Formal Methods in Software Engineering1.
Research topics Semantic Web - Spring 2007 Computer Engineering Department Sharif University of Technology.
The Semantic Web Week 17 Knowledge Engineering – Real Example: Accuracy of Ontologies Module Website: Practical this.
Ontologies and the Semantic Web by Ian Horrocks presented by Thomas Packer 1.
The Semantic Web Week 14 Module Website: Lecture (SHORT): OWL PIZZAS Practical (LONGER): Getting to know Protégé-2000.
Semantics For the Semantic Web: The Implicit, the Formal and The Powerful Amit Sheth, Cartic Ramakrishnan, Christopher Thomas CS751 Spring 2005 Presenter:
From SHIQ and RDF to OWL: The Making of a Web Ontology Language
CHOROS: IMPROVING THE PERFORMANCE OF QUALITATIVE SPATIAL REASONING IN OWL Nikolaos Mainas, Euripides G.M. Petrakis Technical University Of Crete (TUC),
Business Domain Modelling Principles Theory and Practice HYPERCUBE Ltd 7 CURTAIN RD, LONDON EC2A 3LT Mike Bennett, Hypercube Ltd.
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
Introduction to BIM BIM Curriculum 01.
Špindlerův Mlýn, Czech Republic, SOFSEM Semantically-aided Data-aware Service Workflow Composition Ondrej Habala, Marek Paralič,
Georgios Christodoulou, Euripides G.M. Petrakis, and Sotirios Batsakis Department of Electronic and Computer Engineering, Technical University of Crete.
Ontology Development Kenneth Baclawski Northeastern University Harvard Medical School.
Knowledge representation
Agent Model for Interaction with Semantic Web Services Ivo Mihailovic.
Building an Ontology of Semantic Web Techniques Utilizing RDF Schema and OWL 2.0 in Protégé 4.0 Presented by: Naveed Javed Nimat Umar Syed.
MPEG-7 Interoperability Use Case. Motivation MPEG-7: set of standardized tools for describing multimedia content at different abstraction levels Implemented.
Welcome to Design Studies 1A STRUCTURES. who am I ? Mike Rosenman where am I ? Room 279 contact ? Ph: Fax:
A view-based approach for semantic service descriptions Carsten Jacob, Heiko Pfeffer, Stephan Steglich, Li Yan, and Ma Qifeng
CS200 Algorithms and Data StructuresColorado State University Part 4. Advanced Java Topics Instructor: Sangmi Pallickara
Coastal Atlas Interoperability - Ontologies (Advanced topics that we did not get to in detail) Luis Bermudez Stephanie Watson Marine Metadata Interoperability.
Semantic Web - an introduction By Daniel Wu (danielwujr)
Knowledge Representation of Statistic Domain For CBR Application Supervisor : Dr. Aslina Saad Dr. Mashitoh Hashim PM Dr. Nor Hasbiah Ubaidullah.
Advanced topics in software engineering (Semantic web)
Integrating SysML and OWL2 (only the static part of SysML Block Diagrams) October 2009 Henson Graves Lockheed Martin Aeronautics.
Scaling Heterogeneous Databases and Design of DISCO Anthony Tomasic Louiqa Raschid Patrick Valduriez Presented by: Nazia Khatir Texas A&M University.
Web Information Systems Modeling Luxembourg, June VisAVis: An Approach to an Intermediate Layer between Ontologies and Relational Database Contents.
© University of Manchester Simplifying OWL Learning lessons from Anaesthesia Nick Drummond BioHealth Informatics Group.
Metadata Common Vocabulary a journey from a glossary to an ontology of statistical metadata, and back Sérgio Bacelar
Ontology Design for USC Semantic Information Research Lab Chen Li, Tengfei Li, Tian Wang.
Semantic Web BY: Josh Rachner and Julio Pena. What is the Semantic Web? The semantic web is a part of the world wide web that allows data to be better.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
Topic Maps introduction Peter-Paul Kruijsen CTO, Morpheus software ISOC seminar, april 5 th 2005.
Digital Libraries1 David Rashty. Digital Libraries2 “A library is an arsenal of liberty” Anonymous.
Ontology Resource Discussion
Some Thoughts to Consider 8 How difficult is it to get a group of people, or a group of companies, or a group of nations to agree on a particular ontology?
Conclusions Presenter: Manolis Koubarakis Extended Semantic Web Conference 2012.
Semantic Water Quality Portal Jin Guang Zheng and Ping Wang Tetherless World Constellation.
1 Adaptive Data Access Interface for STEP Model Repositories- support AEC product lifecycle management Frank Wang Donghoon Yang Chuck Eastman.
Web Ontology Language (OWL). OWL The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about.
OWL Web Ontology Language Summary IHan HSIAO (Sharon)
Enable Semantic Interoperability for Decision Support and Risk Management Presented by Dr. David Li Key Contributors: Dr. Ruixin Yang and Dr. John Qu.
1 Instance Store Database Support for Reasoning over Individuals S Bechhofer, I Horrocks, D Turi. Instance Store - Database Support for Reasoning over.
Semantic Interoperability in GIS N. L. Sarda Suman Somavarapu.
- Laboratoire d'InfoRmatique en Image et Systèmes d'information LIRIS UMR 5205 CNRS/INSA.
1 A Methodology for automatic retrieval of similarly shaped machinable components Mark Ascher - Dept of ECE.
Banaras Hindu University. A Course on Software Reuse by Design Patterns and Frameworks.
Mathematical Service Matching Using Description Logic and OWL Kamelia Asadzadeh Manjili
OWL (Ontology Web Language and Applications) Maw-Sheng Horng Department of Mathematics and Information Education National Taipei University of Education.
COGNITIVE APPROACH TO ROBOT SPATIAL MAPPING
Semantic Web Project Status
Object-Oriented Analysis and Design
Online Laptop Shop through Semantic Web
Ontology.
ece 720 intelligent web: ontology and beyond
Ontology.
ONTOMERGE Ontology translations by merging ontologies Paper: Ontology Translation on the Semantic Web by Dejing Dou, Drew McDermott and Peishen Qi 2003.
University of Manchester
Presentation transcript:

Building Knowledge about Buildings Matt Young and Eyal Amir University of Illinois, Urbana-Champaign

The Problem Need a way to represent information about buildings. A wealth of information exists in floor plans, but what information do we need? How to encode it?

Our Goals A general framework for representing buildings which is: Simple enough to add data quickly/automatically. Complete enough to accurately represent the structure of a building. Able to answer queries regarding that structure.

Overview Previous Work Overview of Our Language Comparison with Current Technology Other Applications Future Work

Previous Work - Cyc Contains a “Building” constant, defined as “A specialization of both FixedStructure and HumanShelterConstruction.” By following assertions through the hierarchy, we can learn certain information about a building such as what rooms it contains, how many levels it has, etc. However, there is no structured presentation of how things are connected together, how the building is actually constructed.

Previous Work - IFC Data Model International standard for architectural firms, CAD developers, and construction companies. Very detailed information about building construction. However, also contains a great deal of information about processes, analysis, CAD data, etc. Also, it is inconsistently implemented.

Our Solution A language designed specifically to capture only the structure of a building. Encoded as an ontology in OWL DL, for ease of use with the Semantic Web, and (hopefully) full decidability on inference.

Language – General Classes Classes define different features of a Building. Four main classes Building External_Feature Internal_Feature Material Subclasses define distinct feature types.

Language - Properties Properties define relations between features. Most are defined symmetrically, for strong connectedness.

Language - Assertions Assertions enforce proper construction of buildings. Ensure that certain properties must be filled with some value (or possibly more than one value). There are no value restrictions.

Language - Specialization Language can be extended with subclasses of the general classes define to subtypes of each feature. e.g. House is a subtype of Building, Bedroom is a subtype of Room. Subtypes are defined by additional restrictions, some of which may be value restrictions. Subtypes can also be inferred, but this slows down search considerably.

Language - Limitations No spatial information (size, shape). No information about environment surrounding building. Some features are difficult to encode: Features serving multiple purposes (e.g. A roof also serving as a wall, such as in an A-frame). Features which are both external and internal.

Comparison with Current Technology Architectural FeatureHouseplans.com Our language # of Bedrooms/BathsYes # of FloorsYes Includes certain room typeYes Square footageYesNo Has X room on Y floorNoYes Has X room connected to Y roomNoYes # of exits from each roomNoYes

Other Applications Find paths out of buildings (fire escapes). Complete a building floor plan given a partial encoding of the building. Use a knowledge base encoded in this language to categorize buildings given partial information about them.

Future Work Adding spatial information without losing decidability. Adding encoding for surrounding environment and for objects within the building to create a full virtual world space. Encoding data automatically from floor plans or IFC models.

Conclusion Special thanks to Eyal for all his help and guidance. Questions / Comments ?