Knowledge Management

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Knowledge Management"

Transcription

1 Knowledge Management INF5100 Autumn 2006 Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

2 Application Domain: Rescue and Emergency Applications Participants from different organizations paramedics, police, fire, Rescue Site Leader, Team Leaders Dynamic environment movement and activity on site personnel arriving and leaving October Sparse Mobile Adhoc Networks minimal infrastructure, few nodes heterogeneity, limited resources (battery, bandwidth) a lot of movement; frequent disconnections; delay tolerance October

3 Knowledge Management (KM) in Sparse MANETs Definition for KM: the tools, techniques and processes for the most effective management of an organization s intellectual assets (Davies et al 2003). Adapted to information sharing in Sparse MANETs: effective management of the intellectual assets (information resources) available for sharing in a Sparse MANET October Knowledge Management (KM) in Sparse MANETs Information sharing and content integration not solved sufficiently in middleware for SMANETs today. KM offer solutions, but these do not consider challenges posed by SMANETs Beneficial for dynamic environments (e.g. rescue operations) to combine middleware infrastructure provided by SMANET with KM solutions KM solutions may be valuable contribution to SMANETs - and vice versa October

4 Problem Statement Network wide information sharing in rescue operations Avoid information overflow Cross organizational administration Information not static, frequent updates Only partial view of available information Three main tasks Establish who needs what information Enable vocabulary sharing & mapping Efficient metadata management October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

5 What is Knowledge Management? Started in the 80s, Management Theory with the notion that all knowledge can be formalized the goal was to automatize production processes Multidisciplinary: political science, communication studies, IT, management sciences, Knowledge central seen as part of an organization's competence Central questions in KM: what is knowledge in the production process how can the knowledge flow be improved October What is Knowledge Management? the tools, techniques and processes for the most effective management of an organization s intellectual assets (Davies et al 2003) a dynamic, continuous organizational phenomenon of interdependent processes with varying scopes and changing characteristics. (Alavi/Leidner 2001) October

6 Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October Knowledge - Complementary Definition (Gardner95): KNOWING what information is needed how information must be processed why which information is needed where information can be found to achieve a specific result when which information is needed October

7 Perspectives on Knowledge Source: Alavi/Leidner 2001, p.111 October Hierarchical View of Knowledge Common in IT Data: raw numbers and facts - symbols not yet interpreted Information: interpreted data - data which has been assigned a meaning Always linked to specific situation, has only limited validity Knowledge: personalized information enables people to act and to deal intelligently with all the available information sources. (action component) Whole set of insights, experiences and procedures considered correct and true, guide people s thoughts, behavior and communication. Always applicable in several situations, valid over a relatively long period of time. October

8 Types of Knowledge The most common taxonomy Explicit: facts, in documents, models, pictures articulated, codified, and communicated in symbolic form and/or natural language Tacit: implicit, a mental model, skills rooted in action, experience and involvement in a specific context cognitive elements: mental models: mental maps, beliefs, paradigms, view-points technical elements: concrete know-how, crafts, skills apply to specific context, e.g. knowledge of the best way to approach a customer. Individual: is created by and exists in the individual Social/Collective: is created by and inherent in the collective actions of a group October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

9 Knowledge Management Processes Creating knowledge develop new - or replace existing - content within an organization s knowledge socialization, combination, externalization, internalization Storing/retrieving knowledge storage, organization, and retrieval of knowledge Transferring and Sharing knowledge communicating and sharing knowledge Applying knowledge integrate and make good use of knowledge in the organization October Knowledge Management Processes -RoleofIT Source: Alavi/Leidner 2001, p.125 October

10 Knowledge Storage/Retrieval Organizational Memory Knowledge in various forms e.g., documentation, structured information in databases, knowledge stored in expert systems, organizational procedures and processes Semantic memory: general, explicit and articulated knowledge e.g., organizational archives of annual reports Episodic memory: context-specific and situated knowledge e.g. specific circumstances of organizational decisions and their outcomes, place and time October Knowledge Storage/Retrieval Role of IT Enhancement and expansion of semantic and episodic organizational memory Increase speed of access to organizational memory Effective tools: Query languages, multimedia databases, DBMSs Groupware: enable creation and sharing of intra-organizational memory October

11 Knowledge Sharing (KS) and Transfer Sharing vs. Transfer: Transfer: focus, a clear objective, unidirectional Sharing: can be unintentionally, multiple directionally, without a specific objective may occur between and among individuals within and among teams among organizational units among organizations KM Systems for KS: repositories databases of knowledge (knowledge bases) networks facilitate communications among team members or groups of individuals October Knowledge Sharing (KS) and Transfer Knowledge about where the knowledge is often as important as the original knowledge itself Sharing this kind of metadata important E.g. corporate directories: who knows what in organization Knowledge transfer is driven by communication processes and information flows Forms of knowledge transfer: informal/formal, personal/impersonal Knowledge transfer to locations where it is needed and can be used is important October

12 Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October Knowledge Management Systems (KMS) IT-based systems developed to support and enhance all KM processes Three common applications: the coding and sharing of best practices the creation of corporate knowledge directories the creation of knowledge networks Requirements must provide ontologies must provide search capabilities often provide filter capabilities (filters can be computerbased or human-based) provide opportunities for collaboration and use of expertise October

13 KMS and Knowledge Bases Two main components of KMSs: knowledge bases and ontologies A knowledge base is a database Usually domain dependent Information may need to be abstracted, synthesized, or integrated with other information (e.g. in best practices databases) Ontologies provide shared vocabulary and facilitates reusability October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

14 What is an Ontology The term ontology can mean different things glossaries & data dictionaries thesauri & taxonomies schemas & data models formal ontologies & inference Many definitions the most commonly used: An ontology is an explicit specification of a conceptualization. (Gruber) October What is an Ontology Basically a model of some part of the world (Universe of Discourse) Defines a common vocabulary for sharing information in a domain Specifies terms for classes/concepts and relations between these informal text or using formal language (e.g. predicate logic) October

15 Ontology Modelling & Implementation Can be modelled using different knowledge modelling techniques and implemented in various kinds of languages Heavyweight ontologies: AI based languages (framebased, first order logic): e.g., Ontolingua, LOOM Ontology mark-up languages: RDF(S), DAML + OIL, OWL Only Lightweight ontologies : Techniques from software engineering & databases: UML, ER, SQL-scripts Not as expressive October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

16 Types of Ontologies We will look at two categorizations These are based on the richness of the internal structure Lightweight ontologies Heavyweight ontologies (ontology proper) the subject of their conceptualization October Lightweight Ontologies Catalogs: controlled vocabulary a finite list of terms. Glossary: list of terms and meaning as natural language statements. Not machine processable. Thesaurus: a networked collection of controlled vocabulary terms synonym relationship. No explicit hierarchy. Informal is-a hierarchies: not strict subclass Top-level categories and specifications of these (e.g. Yahoo). October

17 Heavyweight Ontologies Formal is-a strict subclass hierarchies, necessary for exploiting inheritance Formal instance relationships (formal is-a) includes domain instances Frames ontology includes classes with property information. All subclasses inherit properties. Value restrictions More expressive ontologies, can place restrictions on values that can fill a property. Expressing general logical constraints the most expressive, first order logic. October Lightweight vs. Heavyweight Ontologies Ontology Spectrum, (McGuinnes, 2002) October

18 Types of Ontologies Based on the Subject of the Conceptualization Top-level ontologies aka Upper-level ontologies, general concepts, existing ontologies link root terms to these (e.g. Cyc, SUMO) Domain ontologies Reusable in a specific domain (KM, medical, law, engineering, chemistry etc. ) E.g., UMLS (medical) Application ontologies application dependent, often extend & specialize vocabulary of a domain October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

19 Use of Ontologies in KM Knowledge representation Offer a way to cope with heterogeneous representations of resources Give shared and common understanding of a domain Can be communicated between people and application systems October Information Sharing and Integration Interoperability problem have to make the different systems and domains understand each other Structural heterogeneity data structures, schema solutions from domain of distributed databases Semantic heterogeneity meaning of content ontologies possible solution October

20 Ontologies in Information Integration As solution to semantic heterogeneity problem: explicitly describe semantics of information sources language for translation 3 General approaches: (Wache et. al 2001) Single: global ontology with shared semantics Multiple: need mapping between (each pair of) ontologies (inter-ontology mapping) Hybrid: multiple ontologies are built on top of or linked to a shared vocabulary of basic terms (may function like a bridge or a translation) October Single, Multiple, and Hybrid Ontology Approaches single ontology approach global ontology Or Top-level ontology shared vocabulary local ontology local ontology local ontology multiple ontology approach local ontology local ontology local ontology hybrid ontology approach October

21 Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October Ad-Hoc InfoWare Simplify application development for Sparse MANETS Configurable MW services scalable protocols and services Tradeoff between abstraction and awareness of location, resources, context,... between non-functional requirements, e.g. performance vs. security and availability Separation of mechanisms and policies Coordination of knowledge management and resource management Integration of information Information, data, meta-data, resources Context awareness Resource and QoS aware data placement Scenario domain: Rescue and emergency applications October

22 Ad-Hoc InfoWare Architecture Overview Knowledge Manager Semantic Metadata & Ontology Framework Profile & Context Mgnt Query Mgnt XML/RDF parser Data Dict. Manager SDDD LDD Resource Manager Replic. Mgnt Proposal Unit Resource Monitor Adjac. Monitor Local Monitor Resource Avail. Watchdogs Watchdogs Manager Watchdogs Execution Envir. Distributed Event Notification Service State Mgnt Delivery Storage Mgnt Availability & Scaling Security and Privacy Manager Authentication Access Control Key Management Encryption October Knowledge Management (KM) in Ad-Hoc InfoWare Manage knowledge sharing and integration in a Sparse MANET Adds layer of knowledge Services that allow relating metadata descriptions to semantic context. Only give tools (not decide usage & content) Share information about where to find knowledge about what October

23 Related to KM Elements Hierarchical view of knowledge Explicit knowledge Focused KM processes: Storage/Retrieval and Transfer ( or Knowledge Sharing) Not addressing learning aspect (knowledge creation) Use of ontologies Domain ontologies, e.g. medical, police, fire Upper level ontology/ shared vocabulary (similar to Hybrid approach) Ontology based update Metadata enriched with terms/concepts from ontologies Only ontology use (development etc not during rescue operation) October The Knowledge Manager Distributed Event Notification System Watchdogs Resource Management Knowledge Manager Data Dictionary Mgnt. LDD SDDD Semantic Metadata & Ontology Framework Profile & Context Mgnt Query Mgnt XML Parser AVAILABILITY RETRIEVAL UNDERSTANDING EXCHANGE INFORMATION OVERLOAD Security and Privacy Management SDDD = Semantic Linked Distributed Data Dictionary. LDD = Local Data Dictionary. October

24 Three Types of Metadata Information structure and content description metadata Data Dictionary Management Content, formats, data types etc Semantic metadata Semantic Metadata and Ontology Framework Relations between concepts, e.g. is-a, haspart, hasresource, hasdevicetype Profile and context metadata Profile and Context Management User profile, device profile Context: location, time, situation October Profiles and Context Profiles What, who Device type, resources, groups etc (for device profile) User preferences, roles, personalia etc (for user profile). Fairly static information Context Where, when, why location, time, situation (e.g. rescue operation) Dynamic information (network nodes moving) Used in different meanings (the term context) time, location and situation for a device or user semantic or topical context October

25 Three-layered Approach Conceptual Ontology layer Semantic/ topical Context (Instance) (Link) Implementation SDDD linking level Information layer LDD metadata SDDD = Semantic Linked Distributed Data Dictionary. LDD = Local Data Dictionary. October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

26 Approach to Ontology Based Update Ontologies to represent rescue operation context model profiles for user, device and information Update priorities information types rescue operation roles Operational structure and organization October Issues of Dynamic Update Dynamicity and limited resources unstable availability Frequent updates increased communication needs consistency issues Need efficient metadata management to achieve ontology based update in this environment October

27 Kinds of Dynamic Update - Overview (Vertical) Local update (Horizontal) Metadata Exchange (Horizontal) Ontology Based Between Entities Different level data dictionaries Metadata or Data Metadata Change or Append Both SDDDs Metadata Append SDDDs & KBs Both Both SDDD = Semantic Linked Distributed Data Dictionary. KB = Knowledge Base. October Outline Background Knowledge Management (KM) What is knowledge KM Processes Knowledge Management Systems and Knowledge Bases Ontologies What is an ontology Types of ontologies Use of ontologies in KM Ad-Hoc InfoWare (Example application) Ad-Hoc InfoWare and Approach Ontology Based Update Rescue Ontology Example October

28 Example of Organization and Structure in Rescue Operations October Simple Model of Rescue Operation Roles October

29 Upper Ontology for All Profiles October Information Profile and Example Information Priorities October

30 User Profile October Example of DB Schema Information Profile: pr:informationprofile(pr:ipid, pr:item) pr:informationitem(pr:iid, pr:subject, pr:priority) pr:informationpriority(pr:iprid,...) UserProfile: pr:userprofile(pr:upid, pr:person, pr:role) pr:rescueoperationrole(pr:rorid, pr:roroletype, pr:reportsto, pr:responsibility, pr:ismemberof, pr:hasupdatepriority) pr:responsibility(pr:pid,...) pr:team(pr:tid,...) pr:person(pr:pid, pr:name,...) October

31 Example of DB Content for User Profile October Rescue Scenario Timeline Populating the Knowledge Base Phase 1: initial population of knowledge base Phase 2: ontology individuals for current operation Phase 4: adjustments: changes and new arrivals October

32 Handling Profile Ontologies in our Architecture Storage - who keeps what? Based on user role in rescue operation Each node keeps its own device profile and user profile Components Rescue ontology profiles Profile and Context Management Semantic Metadata and Ontology Framework Sharing and dynamic update Data Dictionary Manager Viewed as resources to be shared October Litterature M. Alavi and D. Leidner. Knowledge Management and Knowledge Management Systems: conceptual foundations and research issues; MISQuarterly Vol. 25 No.1, pp , March tt/rm/alavi01-knowledgemanagement.pdf Deborah L. McGuinness. "Ontologies Come of Age". In Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, ies-come-of-age-mit-press-(with-citation).htm October

Information Technology for KM

Information Technology for KM On the Relations between Structural Case-Based Reasoning and Ontology-based Knowledge Management Ralph Bergmann & Martin Schaaf University of Hildesheim Data- and Knowledge Management Group www.dwm.uni-hildesheim.de

More information

Ontology and automatic code generation on modeling and simulation

Ontology and automatic code generation on modeling and simulation Ontology and automatic code generation on modeling and simulation Youcef Gheraibia Computing Department University Md Messadia Souk Ahras, 41000, Algeria youcef.gheraibia@gmail.com Abdelhabib Bourouis

More information

Performance Analysis, Data Sharing, Tools Integration: New Approach based on Ontology

Performance Analysis, Data Sharing, Tools Integration: New Approach based on Ontology Performance Analysis, Data Sharing, Tools Integration: New Approach based on Ontology Hong-Linh Truong Institute for Software Science, University of Vienna, Austria truong@par.univie.ac.at Thomas Fahringer

More information

Application of ontologies for the integration of network monitoring platforms

Application of ontologies for the integration of network monitoring platforms Application of ontologies for the integration of network monitoring platforms Jorge E. López de Vergara, Javier Aracil, Jesús Martínez, Alfredo Salvador, José Alberto Hernández Networking Research Group,

More information

Knowledge Management

Knowledge Management Knowledge Management Management Information Code: 164292-02 Course: Management Information Period: Autumn 2013 Professor: Sync Sangwon Lee, Ph. D D. of Information & Electronic Commerce 1 00. Contents

More information

BUSINESS VALUE OF SEMANTIC TECHNOLOGY

BUSINESS VALUE OF SEMANTIC TECHNOLOGY BUSINESS VALUE OF SEMANTIC TECHNOLOGY Preliminary Findings Industry Advisory Council Emerging Technology (ET) SIG Information Sharing & Collaboration Committee July 15, 2005 Mills Davis Managing Director

More information

I. INTRODUCTION NOESIS ONTOLOGIES SEMANTICS AND ANNOTATION

I. INTRODUCTION NOESIS ONTOLOGIES SEMANTICS AND ANNOTATION Noesis: A Semantic Search Engine and Resource Aggregator for Atmospheric Science Sunil Movva, Rahul Ramachandran, Xiang Li, Phani Cherukuri, Sara Graves Information Technology and Systems Center University

More information

Semantic Search in Portals using Ontologies

Semantic Search in Portals using Ontologies Semantic Search in Portals using Ontologies Wallace Anacleto Pinheiro Ana Maria de C. Moura Military Institute of Engineering - IME/RJ Department of Computer Engineering - Rio de Janeiro - Brazil [awallace,anamoura]@de9.ime.eb.br

More information

SERVICE-ORIENTED MODELING FRAMEWORK (SOMF ) SERVICE-ORIENTED SOFTWARE ARCHITECTURE MODEL LANGUAGE SPECIFICATIONS

SERVICE-ORIENTED MODELING FRAMEWORK (SOMF ) SERVICE-ORIENTED SOFTWARE ARCHITECTURE MODEL LANGUAGE SPECIFICATIONS SERVICE-ORIENTED MODELING FRAMEWORK (SOMF ) VERSION 2.1 SERVICE-ORIENTED SOFTWARE ARCHITECTURE MODEL LANGUAGE SPECIFICATIONS 1 TABLE OF CONTENTS INTRODUCTION... 3 About The Service-Oriented Modeling Framework

More information

Theme 6: Enterprise Knowledge Management Using Knowledge Orchestration Agency

Theme 6: Enterprise Knowledge Management Using Knowledge Orchestration Agency Theme 6: Enterprise Knowledge Management Using Knowledge Orchestration Agency Abstract Distributed knowledge management, intelligent software agents and XML based knowledge representation are three research

More information

Semantic Interoperability

Semantic Interoperability Ivan Herman Semantic Interoperability Olle Olsson Swedish W3C Office Swedish Institute of Computer Science (SICS) Stockholm Apr 27 2011 (2) Background Stockholm Apr 27, 2011 (2) Trends: from

More information

Ontology-based User Modeling for Knowledge Management Systems

Ontology-based User Modeling for Knowledge Management Systems -based User Modeling for Knowledge Management Systems Liana Razmerita, Albert Angehrn 1 and Alexander Maedche 2 1 INSEAD,CALT-Centre of Advanced Learning Technologies, 77300 Fontainebleau, France liana.razmerita@ugal.ro,

More information

Ontology for Home Energy Management Domain

Ontology for Home Energy Management Domain Ontology for Home Energy Management Domain Nazaraf Shah 1,, Kuo-Ming Chao 1, 1 Faculty of Engineering and Computing Coventry University, Coventry, UK {nazaraf.shah, k.chao}@coventry.ac.uk Abstract. This

More information

Information Services for Smart Grids

Information Services for Smart Grids Smart Grid and Renewable Energy, 2009, 8 12 Published Online September 2009 (http://www.scirp.org/journal/sgre/). ABSTRACT Interconnected and integrated electrical power systems, by their very dynamic

More information

Reusable Knowledge-based Components for Building Software. Applications: A Knowledge Modelling Approach

Reusable Knowledge-based Components for Building Software. Applications: A Knowledge Modelling Approach Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach Martin Molina, Jose L. Sierra, Jose Cuena Department of Artificial Intelligence, Technical University

More information

Artificial Intelligence & Knowledge Management

Artificial Intelligence & Knowledge Management Artificial Intelligence & Knowledge Management Nick Bassiliades, Ioannis Vlahavas, Fotis Kokkoras Aristotle University of Thessaloniki Department of Informatics Programming Languages and Software Engineering

More information

Semantic EPC: Enhancing Process Modeling Using Ontologies

Semantic EPC: Enhancing Process Modeling Using Ontologies Institute for Information Systems IWi Institut (IWi) für at the German Research Wirtschaftsinformatik Center for im DFKI Saarbrücken Artificial Intelligence (DFKI), Saarland University Semantic EPC: Enhancing

More information

The Data Grid: Towards an Architecture for Distributed Management and Analysis of Large Scientific Datasets

The Data Grid: Towards an Architecture for Distributed Management and Analysis of Large Scientific Datasets The Data Grid: Towards an Architecture for Distributed Management and Analysis of Large Scientific Datasets!! Large data collections appear in many scientific domains like climate studies.!! Users and

More information

Secure Semantic Web Service Using SAML

Secure Semantic Web Service Using SAML Secure Semantic Web Service Using SAML JOO-YOUNG LEE and KI-YOUNG MOON Information Security Department Electronics and Telecommunications Research Institute 161 Gajeong-dong, Yuseong-gu, Daejeon KOREA

More information

Vertical Integration of Enterprise Industrial Systems Utilizing Web Services

Vertical Integration of Enterprise Industrial Systems Utilizing Web Services Vertical Integration of Enterprise Industrial Systems Utilizing Web Services A.P. Kalogeras 1, J. Gialelis 2, C. Alexakos 1, M. Georgoudakis 2, and S. Koubias 2 1 Industrial Systems Institute, Building

More information

WHITE PAPER TOPIC DATE Enabling MaaS Open Data Agile Design and Deployment with CA ERwin. Nuccio Piscopo. agility made possible

WHITE PAPER TOPIC DATE Enabling MaaS Open Data Agile Design and Deployment with CA ERwin. Nuccio Piscopo. agility made possible WHITE PAPER TOPIC DATE Enabling MaaS Open Data Agile Design and Deployment with CA ERwin Nuccio Piscopo agility made possible Table of Contents Introduction 3 MaaS enables Agile Open Data Design 4 MaaS

More information

DLDB: Extending Relational Databases to Support Semantic Web Queries

DLDB: Extending Relational Databases to Support Semantic Web Queries DLDB: Extending Relational Databases to Support Semantic Web Queries Zhengxiang Pan (Lehigh University, USA zhp2@cse.lehigh.edu) Jeff Heflin (Lehigh University, USA heflin@cse.lehigh.edu) Abstract: We

More information

Long Term Knowledge Retention and Preservation

Long Term Knowledge Retention and Preservation Long Term Knowledge Retention and Preservation Aziz Bouras University of Lyon, DISP Laboratory France abdelaziz.bouras@univ-lyon2.fr Recent years: How should digital 3D data and multimedia information

More information

The Ontological Approach for SIEM Data Repository

The Ontological Approach for SIEM Data Repository The Ontological Approach for SIEM Data Repository Igor Kotenko, Olga Polubelova, and Igor Saenko Laboratory of Computer Science Problems, Saint-Petersburg Institute for Information and Automation of Russian

More information

2. Using Ontologies in Software Engineering and Technology

2. Using Ontologies in Software Engineering and Technology 2. Using Ontologies in Software Engineering and Technology Francisco Ruiz ALARCOS Research Group. Dept. of Information Technologies and Systems, Escuela Superior de Informática, University of Castilla-La

More information

Chapter 13: Knowledge Management In Nutshell. Information Technology For Management Turban, McLean, Wetherbe John Wiley & Sons, Inc.

Chapter 13: Knowledge Management In Nutshell. Information Technology For Management Turban, McLean, Wetherbe John Wiley & Sons, Inc. Chapter 13: Knowledge Management In Nutshell Information Technology For Management Turban, McLean, Wetherbe John Wiley & Sons, Inc. Objectives Define knowledge and describe the different types of knowledge.

More information

Chapter 8 The Enhanced Entity- Relationship (EER) Model

Chapter 8 The Enhanced Entity- Relationship (EER) Model Chapter 8 The Enhanced Entity- Relationship (EER) Model Copyright 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 8 Outline Subclasses, Superclasses, and Inheritance Specialization

More information

Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object

Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object Anne Monceaux 1, Joanna Guss 1 1 EADS-CCR, Centreda 1, 4 Avenue Didier Daurat 31700 Blagnac France

More information

OWL based XML Data Integration

OWL based XML Data Integration OWL based XML Data Integration Manjula Shenoy K Manipal University CSE MIT Manipal, India K.C.Shet, PhD. N.I.T.K. CSE, Suratkal Karnataka, India U. Dinesh Acharya, PhD. ManipalUniversity CSE MIT, Manipal,

More information

Semantics and Ontology of Logistic Cloud Services*

Semantics and Ontology of Logistic Cloud Services* Semantics and Ontology of Logistic Cloud s* Dr. Sudhir Agarwal Karlsruhe Institute of Technology (KIT), Germany * Joint work with Julia Hoxha, Andreas Scheuermann, Jörg Leukel Usage Tasks Query Execution

More information

A Framework for Ontology-Based Knowledge Management System

A Framework for Ontology-Based Knowledge Management System A Framework for Ontology-Based Knowledge Management System Jiangning WU Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China E-mail: jnwu@dlut.edu.cn Abstract Knowledge

More information

SEMANTIC VIDEO ANNOTATION IN E-LEARNING FRAMEWORK

SEMANTIC VIDEO ANNOTATION IN E-LEARNING FRAMEWORK SEMANTIC VIDEO ANNOTATION IN E-LEARNING FRAMEWORK Antonella Carbonaro, Rodolfo Ferrini Department of Computer Science University of Bologna Mura Anteo Zamboni 7, I-40127 Bologna, Italy Tel.: +39 0547 338830

More information

Semantically Enhanced Web Personalization Approaches and Techniques

Semantically Enhanced Web Personalization Approaches and Techniques Semantically Enhanced Web Personalization Approaches and Techniques Dario Vuljani, Lidia Rovan, Mirta Baranovi Faculty of Electrical Engineering and Computing, University of Zagreb Unska 3, HR-10000 Zagreb,

More information

Session Two. Organizational Knowledge Management

Session Two. Organizational Knowledge Management Knowledge Management Session Two Organizational Knowledge Management Intellectual capital Intellectual capital is combination of the Intellectual property (IP) held by a business and the people in that

More information

TOWARDS AN INTEGRATION OF ENGINEERING KNOWLEDGE MANAGEMENT AND KNOWLEDGE BASED ENGINEERING

TOWARDS AN INTEGRATION OF ENGINEERING KNOWLEDGE MANAGEMENT AND KNOWLEDGE BASED ENGINEERING TOWARDS AN NTEGRATON OF ENGNEERNG KNOWLEDGE MANAGEMENT AND KNOWLEDGE BASED ENGNEERNG Rdiger Klein DaimlerChrysler Research and Technology Knowledge Based Engineering Group Alt-Moabit 96a D-10559 Berlin

More information

Static Analysis and Validation of Composite Behaviors in Composable Behavior Technology

Static Analysis and Validation of Composite Behaviors in Composable Behavior Technology Static Analysis and Validation of Composite Behaviors in Composable Behavior Technology Jackie Zheqing Zhang Bill Hopkinson, Ph.D. 12479 Research Parkway Orlando, FL 32826-3248 407-207-0976 jackie.z.zhang@saic.com,

More information

ECOR. Terminology and Ontology in Semantic Interoperability of Electronic Health Records. Dr. W. Ceusters. Saarland University

ECOR. Terminology and Ontology in Semantic Interoperability of Electronic Health Records. Dr. W. Ceusters. Saarland University Terminology and Ontology in Semantic Interoperability of Electronic Health Records Dr. W. Ceusters Saarland University Semantic Interoperability Working definition: Two information systems are semantically

More information

Considerations: Mastering Data Modeling for Master Data Domains

Considerations: Mastering Data Modeling for Master Data Domains Considerations: Mastering Data Modeling for Master Data Domains David Loshin President of Knowledge Integrity, Inc. June 2010 Americas Headquarters EMEA Headquarters Asia-Pacific Headquarters 100 California

More information

A Collaborative System Software Solution for Modeling Business Flows Based on Automated Semantic Web Service Composition

A Collaborative System Software Solution for Modeling Business Flows Based on Automated Semantic Web Service Composition 32 A Collaborative System Software Solution for Modeling Business Flows Based on Automated Semantic Web Service Composition Ion SMEUREANU, Andreea DIOŞTEANU Economic Informatics Department, Academy of

More information

Concepts of Database Management Seventh Edition. Chapter 9 Database Management Approaches

Concepts of Database Management Seventh Edition. Chapter 9 Database Management Approaches Concepts of Database Management Seventh Edition Chapter 9 Database Management Approaches Objectives Describe distributed database management systems (DDBMSs) Discuss client/server systems Examine the ways

More information

KM road map. Technology Components of KM. Chapter 5- The Technology Infrastructure. Knowledge Management Systems

KM road map. Technology Components of KM. Chapter 5- The Technology Infrastructure. Knowledge Management Systems Knowledge Management Systems Chapter 5- The Technology Infrastructure Dr. Mohammad S. Owlia Associate Professor, Industrial Engineering Department, Yazd University E-mail :owliams@gmail.com, Website :

More information

An Ontology-based e-learning System for Network Security

An Ontology-based e-learning System for Network Security An Ontology-based e-learning System for Network Security Yoshihito Takahashi, Tomomi Abiko, Eriko Negishi Sendai National College of Technology a0432@ccedu.sendai-ct.ac.jp Goichi Itabashi Graduate School

More information

Amit Sheth & Ajith Ranabahu, 2010. Presented by Mohammad Hossein Danesh

Amit Sheth & Ajith Ranabahu, 2010. Presented by Mohammad Hossein Danesh Amit Sheth & Ajith Ranabahu, 2010 Presented by Mohammad Hossein Danesh 1 Agenda Introduction to Cloud Computing Research Motivation Semantic Modeling Can Help Use of DSLs Solution Conclusion 2 3 Motivation

More information

Model Driven Interoperability through Semantic Annotations using SoaML and ODM

Model Driven Interoperability through Semantic Annotations using SoaML and ODM Model Driven Interoperability through Semantic Annotations using SoaML and ODM JiuCheng Xu*, ZhaoYang Bai*, Arne J.Berre*, Odd Christer Brovig** *SINTEF, Pb. 124 Blindern, NO-0314 Oslo, Norway (e-mail:

More information

Ontological Representations of Software Patterns

Ontological Representations of Software Patterns Ontological Representations of Software Patterns Jean-Marc Rosengard and Marian F. Ursu University of London http://w2.syronex.com/jmr/ Abstract. This paper 1 is based on and advocates the trend in software

More information

A Framework for Collaborative Project Planning Using Semantic Web Technology

A Framework for Collaborative Project Planning Using Semantic Web Technology A Framework for Collaborative Project Planning Using Semantic Web Technology Lijun Shen 1 and David K.H. Chua 2 Abstract Semantic web technology has become an enabling technology for machines to automatically

More information

Semantic Information on Electronic Medical Records (EMRs) through Ontologies

Semantic Information on Electronic Medical Records (EMRs) through Ontologies Semantic Information on Electronic Medical Records (EMRs) through Ontologies Suarez Barón M. J. Researcher, Research Center at Colombian School of Industrial Careers marcojaviersuarezbaron@gmail.com Bogotá,

More information

Building Views and Charts in Requests Introduction to Answers views and charts Creating and editing charts Performing common view tasks

Building Views and Charts in Requests Introduction to Answers views and charts Creating and editing charts Performing common view tasks Oracle Business Intelligence Enterprise Edition (OBIEE) Training: Working with Oracle Business Intelligence Answers Introduction to Oracle BI Answers Working with requests in Oracle BI Answers Using advanced

More information

Automatic Timeline Construction For Computer Forensics Purposes

Automatic Timeline Construction For Computer Forensics Purposes Automatic Timeline Construction For Computer Forensics Purposes Yoan Chabot, Aurélie Bertaux, Christophe Nicolle and Tahar Kechadi CheckSem Team, Laboratoire Le2i, UMR CNRS 6306 Faculté des sciences Mirande,

More information

Architectural Design

Architectural Design Software Engineering Architectural Design 1 Software architecture The design process for identifying the sub-systems making up a system and the framework for sub-system control and communication is architectural

More information

No More Keyword Search or FAQ: Innovative Ontology and Agent Based Dynamic User Interface

No More Keyword Search or FAQ: Innovative Ontology and Agent Based Dynamic User Interface IAENG International Journal of Computer Science, 33:1, IJCS_33_1_22 No More Keyword Search or FAQ: Innovative Ontology and Agent Based Dynamic User Interface Nelson K. Y. Leung and Sim Kim Lau Abstract

More information

Deploying a distributed data storage system on the UK National Grid Service using federated SRB

Deploying a distributed data storage system on the UK National Grid Service using federated SRB Deploying a distributed data storage system on the UK National Grid Service using federated SRB Manandhar A.S., Kleese K., Berrisford P., Brown G.D. CCLRC e-science Center Abstract As Grid enabled applications

More information

Business Rule Standards -- Interoperability and Portability

Business Rule Standards -- Interoperability and Portability Rule Standards -- Interoperability and Portability April 2005 Mark H. Linehan Senior Technical Staff Member IBM Software Group Emerging Technology mlinehan@us.ibm.com Donald F. Ferguson IBM Fellow Software

More information

Business Intelligence and Decision Support Systems

Business Intelligence and Decision Support Systems Chapter 12 Business Intelligence and Decision Support Systems Information Technology For Management 7 th Edition Turban & Volonino Based on lecture slides by L. Beaubien, Providence College John Wiley

More information

Combining RDF and Agent-Based Architectures for Semantic Interoperability in Digital Libraries

Combining RDF and Agent-Based Architectures for Semantic Interoperability in Digital Libraries Combining RDF and Agent-Based Architectures for Semantic Interoperability in Digital Libraries Norbert Fuhr, Claus-Peter Klas University of Dortmund, Germany {fuhr,klas}@ls6.cs.uni-dortmund.de 1 Introduction

More information

Graph-Based Linking and Visualization for Legislation Documents (GLVD) Dincer Gultemen & Tom van Engers

Graph-Based Linking and Visualization for Legislation Documents (GLVD) Dincer Gultemen & Tom van Engers Graph-Based Linking and Visualization for Legislation Documents (GLVD) Dincer Gultemen & Tom van Engers Demand of Parliaments Semi-structured information and semantic technologies Inter-institutional business

More information

AN ONTOLOGICAL APPROACH TO WEB APPLICATION DESIGN USING W2000 METHODOLOGY

AN ONTOLOGICAL APPROACH TO WEB APPLICATION DESIGN USING W2000 METHODOLOGY STUDIA UNIV. BABEŞ BOLYAI, INFORMATICA, Volume L, Number 2, 2005 AN ONTOLOGICAL APPROACH TO WEB APPLICATION DESIGN USING W2000 METHODOLOGY ANNA LISA GUIDO, ROBERTO PAIANO, AND ANDREA PANDURINO Abstract.

More information

Distributed Database for Environmental Data Integration

Distributed Database for Environmental Data Integration Distributed Database for Environmental Data Integration A. Amato', V. Di Lecce2, and V. Piuri 3 II Engineering Faculty of Politecnico di Bari - Italy 2 DIASS, Politecnico di Bari, Italy 3Dept Information

More information

Automating Service Negotiation Process for Service Architecture on the cloud by using Semantic Methodology

Automating Service Negotiation Process for Service Architecture on the cloud by using Semantic Methodology Automating Process for Architecture on the cloud by using Semantic Methodology Bhavana Jayant.Adgaonkar Department of Information Technology Amarutvahini College of Engineering Sangamner, India adgaonkarbhavana@yahoo.in

More information

Languages and Semantic Web Architecture

Languages and Semantic Web Architecture Languages and Semantic Web Architecture The Semantic Web Tower what is the semantic web Problems Layering the Semantic Web The problem in detail and suggested approaches Øyvind Evensen What is the semantic

More information

fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries

fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries Johan Montagnat CNRS, I3S lab, Modalis team on behalf of the CrEDIBLE

More information

A Semantic Approach towards CWM-based ETL Processes

A Semantic Approach towards CWM-based ETL Processes Proceedings of I-SEMANTICS 08 Graz, Austria, September 3-5, 2008 A Semantic Approach towards CWM-based ETL Processes Anh Duong Hoang Thi (Hue University Information Technology Center, Hue, Vietnam htaduong@hueuni.edu.vn)

More information

Towards Semantics-Enabled Distributed Infrastructure for Knowledge Acquisition

Towards Semantics-Enabled Distributed Infrastructure for Knowledge Acquisition Towards Semantics-Enabled Distributed Infrastructure for Knowledge Acquisition Vasant Honavar 1 and Doina Caragea 2 1 Artificial Intelligence Research Laboratory, Department of Computer Science, Iowa State

More information

Semantic Business Process Management Lectuer 1 - Introduction

Semantic Business Process Management Lectuer 1 - Introduction Arbeitsgruppe Semantic Business Process Management Lectuer 1 - Introduction Prof. Dr. Adrian Paschke Corporate Semantic Web (AG-CSW) Institute for Computer Science, Freie Universitaet Berlin paschke@inf.fu-berlin.de

More information

KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE

KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE Main Topics of This Lecture Challenges in building KM Systems Compare CSLC and KMSLC User s vs. Expert s Characteristics Stages of KMSLC 2-2 CHALLENGES IN BUILDING

More information

Databases in Organizations

Databases in Organizations The following is an excerpt from a draft chapter of a new enterprise architecture text book that is currently under development entitled Enterprise Architecture: Principles and Practice by Brian Cameron

More information

Software Engineering. System Models. Based on Software Engineering, 7 th Edition by Ian Sommerville

Software Engineering. System Models. Based on Software Engineering, 7 th Edition by Ian Sommerville Software Engineering System Models Based on Software Engineering, 7 th Edition by Ian Sommerville Objectives To explain why the context of a system should be modeled as part of the RE process To describe

More information

bigdata Managing Scale in Ontological Systems

bigdata Managing Scale in Ontological Systems Managing Scale in Ontological Systems 1 This presentation offers a brief look scale in ontological (semantic) systems, tradeoffs in expressivity and data scale, and both information and systems architectural

More information

Service-Oriented Architecture and Software Engineering

Service-Oriented Architecture and Software Engineering -Oriented Architecture and Software Engineering T-86.5165 Seminar on Enterprise Information Systems (2008) 1.4.2008 Characteristics of SOA The software resources in a SOA are represented as services based

More information

Implementing Ontology-based Information Sharing in Product Lifecycle Management

Implementing Ontology-based Information Sharing in Product Lifecycle Management Implementing Ontology-based Information Sharing in Product Lifecycle Management Dillon McKenzie-Veal, Nathan W. Hartman, and John Springer College of Technology, Purdue University, West Lafayette, Indiana

More information

The SEEMP project Single European Employment Market-Place An e-government case study

The SEEMP project Single European Employment Market-Place An e-government case study The SEEMP project Single European Employment Market-Place An e-government case study 1 Scenario introduction Several e-government projects have been developed in the field of employment with the aim of

More information

A generic approach for data integration using RDF, OWL and XML

A generic approach for data integration using RDF, OWL and XML A generic approach for data integration using RDF, OWL and XML Miguel A. Macias-Garcia, Victor J. Sosa-Sosa, and Ivan Lopez-Arevalo Laboratory of Information Technology (LTI) CINVESTAV-TAMAULIPAS Km 6

More information

Service Oriented Architecture

Service Oriented Architecture Service Oriented Architecture Charlie Abela Department of Artificial Intelligence charlie.abela@um.edu.mt Last Lecture Web Ontology Language Problems? CSA 3210 Service Oriented Architecture 2 Lecture Outline

More information

ONTOLOGY-BASED APPROACH TO DEVELOPMENT OF ADJUSTABLE KNOWLEDGE INTERNET PORTAL FOR SUPPORT OF RESEARCH ACTIVITIY

ONTOLOGY-BASED APPROACH TO DEVELOPMENT OF ADJUSTABLE KNOWLEDGE INTERNET PORTAL FOR SUPPORT OF RESEARCH ACTIVITIY ONTOLOGY-BASED APPROACH TO DEVELOPMENT OF ADJUSTABLE KNOWLEDGE INTERNET PORTAL FOR SUPPORT OF RESEARCH ACTIVITIY Yu. A. Zagorulko, O. I. Borovikova, S. V. Bulgakov, E. A. Sidorova 1 A.P.Ershov s Institute

More information

Supporting Change-Aware Semantic Web Services

Supporting Change-Aware Semantic Web Services Supporting Change-Aware Semantic Web Services Annika Hinze Department of Computer Science, University of Waikato, New Zealand a.hinze@cs.waikato.ac.nz Abstract. The Semantic Web is not only evolving into

More information

Introduction to Service Oriented Architectures (SOA)

Introduction to Service Oriented Architectures (SOA) Introduction to Service Oriented Architectures (SOA) Responsible Institutions: ETHZ (Concept) ETHZ (Overall) ETHZ (Revision) http://www.eu-orchestra.org - Version from: 26.10.2007 1 Content 1. Introduction

More information

On the general structure of ontologies of instructional models

On the general structure of ontologies of instructional models On the general structure of ontologies of instructional models Miguel-Angel Sicilia Information Engineering Research Unit Computer Science Dept., University of Alcalá Ctra. Barcelona km. 33.6 28871 Alcalá

More information

Representing the Hierarchy of Industrial Taxonomies in OWL: The gen/tax Approach

Representing the Hierarchy of Industrial Taxonomies in OWL: The gen/tax Approach Representing the Hierarchy of Industrial Taxonomies in OWL: The gen/tax Approach Martin Hepp Digital Enterprise Research Institute (DERI), University of Innsbruck Florida Gulf Coast University, Fort Myers,

More information

Department of Defense Net-Centric Data Strategy

Department of Defense Net-Centric Data Strategy Department of Defense Net-Centric Data Strategy May 9, 2003 Prepared by: Department of Defense Chief Information Officer (CIO) TABLE OF CONTENTS 1. PURPOSE... 1 2. INTRODUCTION... 1 2.1 DOD DATA VISION...

More information

Ontology Modeling Using UML

Ontology Modeling Using UML Ontology Modeling Using UML Xin Wang Christine W. Chan Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada S4S 0A2 wangx@cs.uregina.ca, chan@cs.uregina.ca Abstract Ontology

More information

Bootstrapping Adoption of a Universal Exchange Language for Health Information Exchange

Bootstrapping Adoption of a Universal Exchange Language for Health Information Exchange Bootstrapping Adoption of a Universal Exchange Language for Health Information Exchange Speakers: Tajh L. Taylor, Lowell Vizenor OMG SOA in Healthcare Conference July 15, 2011 Agenda The Health Information

More information

Federal Enterprise Architecture and Service-Oriented Architecture

Federal Enterprise Architecture and Service-Oriented Architecture Federal Enterprise Architecture and Service-Oriented Architecture Concepts and Synergies Melvin Greer Chief Strategist, SOA / Cloud Computing Certified Enterprise Architect Copyright August 19, 2010 2010

More information

Security Issues for the Semantic Web

Security Issues for the Semantic Web Security Issues for the Semantic Web Dr. Bhavani Thuraisingham Program Director Data and Applications Security The National Science Foundation Arlington, VA On leave from The MITRE Corporation Bedford,

More information

Semantic Technologies for Big Data. Marin Dimitrov (Ontotext)

Semantic Technologies for Big Data. Marin Dimitrov (Ontotext) Semantic Technologies for Big Data Marin Dimitrov (Ontotext) XML Amsterdam 2012 XML Amsterdam 2012 #2 About Ontotext Provides products and services for creating, managing and exploiting semantic data Founded

More information

Relational Database Basics Review

Relational Database Basics Review Relational Database Basics Review IT 4153 Advanced Database J.G. Zheng Spring 2012 Overview Database approach Database system Relational model Database development 2 File Processing Approaches Based on

More information

Master Data Management

Master Data Management Master Data Management Managing Data as an Asset By Bandish Gupta Consultant CIBER Global Enterprise Integration Practice Abstract: Organizations used to depend on business practices to differentiate them

More information

technische universiteit eindhoven WIS & Engineering Geert-Jan Houben

technische universiteit eindhoven WIS & Engineering Geert-Jan Houben WIS & Engineering Geert-Jan Houben Contents Web Information System (WIS) Evolution in Web data WIS Engineering Languages for Web data XML (context only!) RDF XML Querying: XQuery (context only!) RDFS SPARQL

More information

Knowledge-based Approach in Information Systems Life Cycle and Information Systems Architecture

Knowledge-based Approach in Information Systems Life Cycle and Information Systems Architecture 5 th Slovakian-Hungarian Joint Symposium on Applied Machine Intelligence and Informatics January 25-26, 2007 Poprad, Slovakia Knowledge-based Approach in Information Systems Life Cycle and Information

More information

The Semantic Web: Web of (integrated) Data

The Semantic Web: Web of (integrated) Data The Semantic Web: Web of (integrated) Data Frank van Harmelen Vrije Universiteit Amsterdam Take home message Semantic Web = Web of Data (no longer only web of text, web of pictures) Set of open, stable

More information

CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONS

CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONS CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONS Keyvan Mohebbi 1, Suhaimi Ibrahim 2, Norbik Bashah Idris 3 1 Faculty of Computer Science and Information Systems, Universiti Teknologi

More information

Introduction to the Semantic Web

Introduction to the Semantic Web Introduction to the Semantic Web Asunción Gómez-Pérez {asun}@fi.upm.es http://www.oeg-upm.net Omtological Engineering Group Laboratorio de Inteligencia Artificial Facultad de Informática Universidad Politécnica

More information

Using LDAP in a Filtering Service for a Digital Library

Using LDAP in a Filtering Service for a Digital Library Using LDAP in a Filtering Service for a Digital Library João Ferreira (**) José Luis Borbinha (*) INESC Instituto de Enghenharia de Sistemas e Computatores José Delgado (*) INESC Instituto de Enghenharia

More information

ONTODESIGN; A DOMAIN ONTOLOGY FOR BUILDING AND EXPLOITING PROJECT MEMORIES IN PRODUCT DESIGN PROJECTS

ONTODESIGN; A DOMAIN ONTOLOGY FOR BUILDING AND EXPLOITING PROJECT MEMORIES IN PRODUCT DESIGN PROJECTS ONTODESIGN; A DOMAIN ONTOLOGY FOR BUILDING AND EXPLOITING PROJECT MEMORIES IN PRODUCT DESIGN PROJECTS DAVY MONTICOLO Zurfluh-Feller Company 25150 Belfort France VINCENT HILAIRE SeT Laboratory, University

More information

Simplifying e Business Collaboration by providing a Semantic Mapping Platform

Simplifying e Business Collaboration by providing a Semantic Mapping Platform Simplifying e Business Collaboration by providing a Semantic Mapping Platform Abels, Sven 1 ; Sheikhhasan Hamzeh 1 ; Cranner, Paul 2 1 TIE Nederland BV, 1119 PS Amsterdam, Netherlands 2 University of Sunderland,

More information

THE e-knowledge BASED INNOVATION SEMINAR

THE e-knowledge BASED INNOVATION SEMINAR The Kaieteur Institute For Knowledge Management THE e-knowledge BASED INNOVATION SEMINAR OVERVIEW! Introduction Knowledge is a new form of renewable and intangible energy that is transforming many organizations.

More information

Applying 4+1 View Architecture with UML 2. White Paper

Applying 4+1 View Architecture with UML 2. White Paper Applying 4+1 View Architecture with UML 2 White Paper Copyright 2007 FCGSS, all rights reserved. www.fcgss.com Introduction Unified Modeling Language (UML) has been available since 1997, and UML 2 was

More information

SmartLink: a Web-based editor and search environment for Linked Services

SmartLink: a Web-based editor and search environment for Linked Services SmartLink: a Web-based editor and search environment for Linked Services Stefan Dietze, Hong Qing Yu, Carlos Pedrinaci, Dong Liu, John Domingue Knowledge Media Institute, The Open University, MK7 6AA,

More information

Context Model Based on Ontology in Mobile Cloud Computing

Context Model Based on Ontology in Mobile Cloud Computing Context Model Based on Ontology in Mobile Cloud Computing Changbok Jang, Euiin Choi * Dept. Of Computer Engineering, Hannam University, Daejeon, Korea chbjang@dblab.hannam.ac.kr, eichoi@hnu.kr Abstract.

More information

fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries

fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries fédération de données et de ConnaissancEs Distribuées en Imagerie BiomédicaLE Data fusion, semantic alignment, distributed queries Johan Montagnat CNRS, I3S lab, Modalis team on behalf of the CrEDIBLE

More information

Lecture 18 of 42. Lecture 18 of 42

Lecture 18 of 42. Lecture 18 of 42 Knowledge Representation Concluded: KE, CIKM, & Representing Events over Time Discussion: Structure Elicitation, Event Calculus William H. Hsu Department of Computing and Information Sciences, KSU KSOL

More information