Semantic Web Methods for Knowledge Management Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) an der Fakultät für Wirtschaftswissenschaften der Universität Fridericiana zu Karlsruhe (TH) genehmigte DISSERTATION von Diplom-Informatiker Stefan Decker Tag der mündlichen Prüfung: 22. Februar 2002 Referent: Prof. Dr. Rudi Studer 1. Korreferent: Prof. Dr. Peter Knauth 2. Korreferent: Prof. Dr. Gio Wiederhold 2002 Karlsruhe What information consumes is rather obvious: It consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sour- ces that might consume it. Nobel Laureate Economist Herbert A. Simon. Acknowledgement The main results of this thesis were obtained during my time at the Institute AIFB at the University of Karlsruhe, Germany. I would like to express my gratitude to my advisor, Prof. Dr. Rudi Studer, for his support, patience, and encouragement throughout my graduate studies. It is not often that one finds an advisor and colleague who always finds the time for listening to the little problems and roadblocks that unavoidably crop up in the course of performing research. I am also grateful to Prof. Dr. Peter Knauth and Prof. Gio Wiederhold who were willing to serve on my dissertation committee on a very short notice, and to Prof. Dr. Wolfried Stucky and Prof. Dr. Andreas Geyer-Schulz, who served on the examination committee. My thanks also go to all the colleagues at the Institute AIFB - in particular to Dr. Michael Erdmann - together we worked on the nitty-gritty details of the Ontobroker architecture, and Michael helped me to shape my ideas about the future of the Web. The vision, energy and dedication of Dr. Dieter Fensel has been invaluable for this thesis and the Ontobroker project - without him that project had not happened. Michael Schenk, Ulf Steinberg, and Thorsten Wolf, who wrote their diploma theses under my supervision, contributed heavily to Ontobroker. Dr. Wolfgang Weitz was always there for a discussion when I got stuck. I'm grateful to Dr. Jürgen Angele for the collaboration during my time in Karlsruhe. I'm especially indebted to Prof. Dr. Gio Wiederhold, who gave me the opportunity to work at Stan- ford University and taught me a lot about research and life in general. I thank Jade Reidy and Michael Sintek for proofreading drafts of this thesis - any remaining errors are of course mine. My parents, Maria and Bernhard, receive my deepest gratitude and love for their dedication and the many years of support during my undergraduate studies that provided the foundation for this work. Last, but not least, I would like to thank my wife Birgit and my children Jana and Robin for their understanding and love during the past years. Their support and encouragement was in the end what made this dissertation possible. v Table of Contents Chapter 1 Introduction . 1 1.1 Motivation . 1 1.1.1 Knowledge Management . 1 1.1.2 The Web . 2 1.2 Goals . 2 1.3 Approaches . 3 1.4 Outline . 4 PART I KNOWLEDGE MANAGEMENT AND ORGANIZATIONAL MEMORIES Chapter 2 Preliminaries: What is Knowledge and Knowledge Management? . 11 2.1 What is Knowledge Management? . 11 2.2 Knowledge in Computer Science . 13 2.2.1 Knowledge in Artificial Intelligence . 13 2.2.2 Ontologies . 15 2.2.3 Representing Procedural Knowledge . 21 2.2.4 Knowledge and Computer Supported Cooperative Work . 22 Chapter 3 Dimensions of Knowledge Management . 25 3.1 Elements of Knowledge Management . 25 3.1.1 Corporate Culture . 25 3.1.2 Organization . 26 3.1.3 People . 28 3.1.4 Technology . 29 3.2 Elements of Knowledge Management II . 29 3.2.1 Defining Knowledge Goals . 29 3.2.2 Knowledge Identification . 29 3.2.3 Knowledge Acquisition . 30 3.2.4 Knowledge Development . 32 3.2.5 Knowledge Sharing and Dissemination . 33 3.2.6 Knowledge Preservation . 34 3.2.7 Knowledge Utilization . 34 3.2.8 Knowledge Assessment . 35 3.3 A Synthesis: The Knowledge Management Cube . 35 Chapter 4 Organizational Memory Information Systems . 37 4.1 IT-Support for Knowledge Management . 37 4.2 Crucial Points for Realizing OMIS . 38 4.2.1 Knowledge Acquisition and Maintenance . 39 4.2.2 Knowledge Integration . 41 4.2.3 Knowledge Retrieval . 42 4.2.4 Differences between OMIS and other Information Systems . 43 4.2.5 OMIS and Expert Systems . 44 vi Chapter 5 A Modeling Schema for Integrating Enterprise Processes and OMIS Support . 45 5.1 Motivation . 45 5.2 CommonKADS . 46 5.2.1 CommonKADS Organization Model . 47 5.2.2 CommonKADS Task Model . 49 5.2.3 CommonKADS Expertise Model . 49 5.3 Relationship between Process Meta Models and Models for Knowledge Based Systems . 51 5.4 Deriving the Schema of OMMM . 53 5.5 Views of OMMM . 54 5.6 Related Work in Enterprise Modeling . 59 5.7 An Application: ERBUS . 62 5.7.1 Introduction . 62 5.7.2 Modeling the Design Process of Industrial Designer . 63 5.7.3 Identifying Tasks to Support . 64 5.7.4 Experiences and Assessment . 65 5.8 Summary . 66 PART II KNOWLEDGE MANAGEMENT WITH ONTOBROKER Chapter 6 Introduction to Ontobroker . 71 6.1 Motivation . 71 6.2 The Architecture of Ontobroker . 74 6.2.1 The Approach . 75 6.2.2 The System . 76 Chapter 7 SiLRI: The Representation Language and System . 79 7.1 Introduction . 79 7.1.1 Higher-Order Logics . 80 7.1.2 Full First-Order Logic-Based Inference Engines . 81 7.1.3 Description Logic . 81 7.1.4 Logic Programming and Deductive Databases . 81 7.2 F-Logic in SiLRI . 82 7.2.1 Syntax of F-Logic in SiLRI . 83 7.3 Semantics of F-Logic . 84 7.3.1 Constructing Domain-Specific Logic Languages . 86 7.3.1.1 Frame-Logic . 88 7.3.1.2 Chronolog . 90 7.3.1.3 C-F-Logic: An Amalgamation of F-logic and Chronolog . 91 7.3.1.4 Assessment of the Approach . 93 7.3.2 Optimized Lloyd-Topor Transformation . 94 7.4 Selecting an Evaluation Procedure and Semantics . 96 7.5 Implementation of SiLRI . 96 7.6 Critical Evaluation of F-Logic as a Representation and Query Language for the Web . 97 vii Chapter 8 Document Annotation . 99 8.1 Metadata . 99 8.2 HTML-A . ..