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IT-CODE

IT-CODE. PhD Defence. IT in C ollaborative D esign. Yoke-Chin Lai Aalborg University (Denmark) May 22 nd 2006. The Road Map. Introduction Background Research Hypothesis The Research Research Questions Case Studies and Important Findings Demonstrator – IT-CODE Conclusion

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IT-CODE

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  1. IT-CODE PhD Defence IT in Collaborative Design Yoke-Chin Lai Aalborg University (Denmark) May 22nd 2006

  2. The Road Map • Introduction • Background • Research Hypothesis • The Research • Research Questions • Case Studies and Important Findings • Demonstrator – IT-CODE • Conclusion • Contributions • Future Research Lines Y-C Lai PhD Defence, AAU

  3. From Memex to IT-CODE Y-C Lai PhD Defence, AAU

  4. Acquisition Retrieval Search Representation KM Dissemination Indexing Storage Background Common Understanding reaching Data interoperability Multidisciplinary team Problems Knowledge (Tacit & explicit) transfer Information integration has_difficulty conducts to_improve inadequate Collaborative Design applies ICT extension_of creates uses Semantic Web Tech. shares handles Knowledge applies IT-CODE?? Y-C Lai PhD Defence, AAU

  5. The Research Hypothesis • The Semantic Web technology is applicable to support collaboration in the building industry. • On top of the Semantic Web technology, an innovative meeting minutes taking approach can be developed, to facilitate tacit design knowledge transfer • by making explicit the meta-knowledge used to formalise reasoning. Y-C Lai PhD Defence, AAU

  6. Research Questions • How do the multidisciplinary project stakeholders collaborate at the early project stage, the design stage? • How do project stakeholders monitor the design information flow? • What technique do they use? • What technology do they use? • How will the contemporary ICT help to improve the current practices? Y-C Lai PhD Defence, AAU

  7. The 3 Case studies [case study] • Objectives • To study how the project stakeholders collaborate at the design stage. • To study the design information flow in real-life. • To identify the weakness the practising project information management strategy, if any. • Data collection methods • Observations • Semi-structured interviews Y-C Lai PhD Defence, AAU

  8. The 3 Case studies [case study] • Project phase of study • The conceptual design phase • Data analysis methodology • The contextual design formalisms (five types of work models) • Sequence Model • Flow Model • Culture model • Artefact model • Physical Model. Y-C Lai PhD Defence, AAU

  9. Refers to Summarise Stimulates The Information Flow in Design Meeting [case study] Dialog Brings Discuss Communication Agenda Meeting minutes Issues Decide Action Y-C Lai PhD Defence, AAU

  10. Summary of Findings [case study] • The implemented ICT supported codified knowledge management • Codified knowledge • Well structured data, e.g., database, spreadsheet • Semi-structured information, e.g., html/xml files • Weakly structured information, e.g., texts/graphics/multimedia files • Tacit design knowledge was found incorporated implicitly in the weakly structured information. • Face-to-face meetings were favoured in the design phase. • Meeting minutes were produced to summarise the discussion contents in the meetings. • Meeting minutes contained design rationale and reasoning behind decisions. Y-C Lai PhD Defence, AAU

  11. Constraints of Knowledge Management [case study] • Weaknesses identified from the case studies: • Difficulty to manage weakly structured information (natural language plain texts). • Difficulty to connect knowledge containers of various forms (e.g., books, digital databases, human minds). • Difficulty to formalise tacit design knowledge (e.g., design rationale, reasoning behind decisions). • Difficulty to make tacit design knowledge adequately explicit for both human and machine. • Difficulty to represent knowledge comprehensible to all targeted knowledge receivers. Y-C Lai PhD Defence, AAU

  12. The Demonstrator Objectives [demonstrator] • To be a knowledge management system that has the following functional requirements: • To integrate information distributed in different logic & physical containers. • To capture and store decision rationale. • To contextualise discussion contents. • To generate dynamic and semantically structured meeting minutes. Y-C Lai PhD Defence, AAU

  13. Semantic Web: The New Opportunity [demonstrator] • The Semantic Web • It is an extension of the current web (Bernes-Lee, 2001) • It is to provide rich descriptive means for the current web • Information becomes both human and machine understandable • Ontologies are the core of semantic web Source: Berners-Lee, T (2000), XML and the Web, http://www.w3.org/2000/Talks/0906-xmlweb-tbl/slide9-0.html Y-C Lai PhD Defence, AAU

  14. Definition of Ontology [demonstrator] • A formal explicit specification of a shared conceptualisation (Gruber, 93). • One of the main components in knowledge representation. • It can capture consensus knowledge • Its representation is both machine and human readable. • RDF Schema (RDFS) is an example of ontology language • Ontologies are sets of tuples. Person relation Concept is_a Actor Concept works_for Project relation Concept Y-C Lai PhD Defence, AAU

  15. Property Definitions Class Definitions RDFS: The Lightweight Ontology Y-C Lai PhD Defence, AAU

  16. correlate Implicit relation Explicit relation The Concept Behind IT-CODE [demonstrator] • Represent information chunk as object • Represent document as the container of the information objects Issue 1 Xxxxxxx Xxxxxx xxxxxxx Issue 2 Issue 3 object2 object1 Object3 Y-C Lai PhD Defence, AAU

  17. ”Following his initial review.....Jackadvised...” Ytutut hgfhd Hgjghgjh xxds 12/08/03 05/08/03 Annotate the Information [demonstrator] An example of discussion issue in meeting dated 12/08/03: ”Following his initial review of the option 3 layout drawings, Jack advised that the deletion of one floor would reduce total vertical loads and the structural vertical member sizes are expected to be reduced.” Meta-tag Meta-tag Object 1 Object 2 Relation e.g: causes, improves, solves, agrees_with, is_consistent_with, has_alternative Y-C Lai PhD Defence, AAU

  18. Meta-tag What is Meta-tag [demonstrator] • Tag of metadata, e.g. <author>, <URI>, <type_of> • Metadata is ”data about data” • Useful to make information machine readable • Domain specific metadata can be defined and expressed in ontologies models. Y-C Lai PhD Defence, AAU

  19. Examples of Metadata Elements [demonstrator] • Sources: • Dublin Core Metadata Initiative (DCMI), http://dublincore.org/documents/dces/ • Wordnet, http://www.semanticweb.org/library/wordnet/wordnet-20000620.rdfs • International Organisation for Standardization (ISO), http://www.iso.org/iso/en/ISOOnline.frontpage Y-C Lai PhD Defence, AAU

  20. B B-M1: hkjh ssss hkjhwy B-M2: kjkjlkj B-M3: asere jkjd A A-M1: ghj uyt hgjh lko ssda A-M2: hjkhs hjwe fdsd nkjjh Differently strucrured information Documenting The web B A B-M3 A-M2 B-M1 A-M1 Accessing B-M2 Extracting IT-CODE WWW Interpreting Intranet Information Integration [demonstrator] Y-C Lai PhD Defence, AAU

  21. Brings Communication Dialog Discuss Stimulates Decide Action Issues Contextualise the Discussion Contents [demonstrator] • Who raises the issue? • What is the issue type? • Problem? • Propostion/Alternative? • Solution/Agreement? • Are there any precedent cases? • What is the status of the issue? • Why does the issue occur? • What is the consequence? • How to solve the issue? Y-C Lai PhD Defence, AAU

  22. Ontology Model Excerpt– Class Definitions Y-C Lai PhD Defence, AAU

  23. Ontology Model Excerpt– Property Definitions Y-C Lai PhD Defence, AAU

  24. The Data Model (Instance) [demonstrator] <Container> meeting minutes_001 <Actor> Inst_003 <Location> URL:http://xxx.xx assignee Rose has_location Harry <Action> has_name contains issue_raiser <Actor> Instance_001 <Project stage> causes <Role> <Decision> Deletion of 1 floor...expect to be reduced. has_role project_stage agrees_with reviewer project_stage has_role <Proposition> causes is_solved_by Stan improves_on has_name <Problem> Bla bla bla proposes <Actor> Inst_002

  25. RDF Excerpts Y-C Lai PhD Defence, AAU

  26. RDF data file Sesame 1.1 Tomcat 5.0 MySQL Tools for IT-CODE [demonstrator] Protege 3.0 Ontology editor RDF(S) based repository • Single user applet • Front-end data input • RDF data file generated • Simple but precise query • RDF(S) based precise query • Multi-user server environment support • Easily extensible knowledge base • Compatible with different type of database Y-C Lai PhD Defence, AAU

  27. The Components of IT-CODE [demonstrator] Y-C Lai PhD Defence, AAU

  28. Applet- Project & Meeting Attributes How to solve the issue? Y-C Lai PhD Defence, AAU

  29. Applet– Issue Contextualisation What is the issue type? What is the issue status? Who raise the issue? Categorisation – to facilitate precedent search Why does the issue occur? What is the consequence? Y-C Lai PhD Defence, AAU

  30. Applet– Discussion Trail Search Query: To search all issues that were discussed in the meeting dated 25 November 2003 and related to the schematic design process Y-C Lai PhD Defence, AAU

  31. The Semantic Web Client [demonstrator] • the gateway to access the Sesame repository Archives of previous projects Search results Y-C Lai PhD Defence, AAU

  32. Conclusion Contribution 1:The Innovative Meeting Minutes • Information was structured based on semantic network. • Information had better interoperability. • Information was dynamically linked. • Semantic search was supported. • Form based user interface was used. Y-C Lai PhD Defence, AAU

  33. Conclusion Contribution 2: The concept of total knowledge management was applied in the demonstrator (IT-CODE). Y-C Lai PhD Defence, AAU

  34. Conclusion Contribution 3:The concept of associative thinking was incorporated into the innovative meeting minutes to contextualise the discussion contents. • As a suggestion to make explicit the reasoning behind decisions. Y-C Lai PhD Defence, AAU

  35. Conclusion Contribution 4:The emerging Semantic Web technology was suggested having the applicable potential to support design knowledge management in the building industry. • A demonstrator was constructed using the ontological representation approach and the corresponding ontology language • to support semantic search, • to support semantic integration of different information resources, • to make explicit the meta-knowledge, and • to facilitate tacit knowledge transfer. Y-C Lai PhD Defence, AAU

  36. Future Research Lines [conclusion] • To use pre-defined domain-specific metadata in the ontology modelling process. • E.g., ISO/IEC 82045-5 • To investigate possible linking to IFC based product model description. • More efficient integration of domain knowledge. • To enable simulation of decision making process • Need a more expressive ontology language with logic support, e.g. OWL. OWL (Web Ontology Language), http://www.w3.org/TR/owl-features/ Y-C Lai PhD Defence, AAU

  37. Future Research Lines [conclusion] • To improve usability • To create an easy-to-use knowledge authoring environment. • Need a better system coherence. • Seamless integration of the different knowledge authoring tools (Protégé & Sesame) used. • Suggestion 1: Integrate with web-based Content Management tools, e.g. Wiki, Bloki. • Suggestion 2: Incorporate speech recognition tools and discourse annotation tools (natural language processing). • Knowledge authoring complications in discourse annotation tools. • Immature speech recognition technology. Y-C Lai PhD Defence, AAU

  38. Thank you. Question/s? or Bye bye. Y-C Lai PhD Defence, AAU

  39. Data-Information-Knowledge <Q&A> Y-C Lai PhD Defence, AAU

  40. Sequence Model <Q&A> • To illustrate the sequence of activities conducted in a design progress meeting. • To study the intent of an activity • To study the action taken to achieve the intent. • To study the reasoning behind the action. Y-C Lai PhD Defence, AAU

  41. Flow Model <Q&A> • To study the interaction and communication flow of the interviewees. • To study the technique/s used to organise roles. • To study what technology and/or tool the interviewees used to complete the tasks. Y-C Lai PhD Defence, AAU

  42. Culture Model <Q&A> • To study the working culture of a group. • To study the working practices of the group. • To study how the different working practices influence one (person) another. • To study how the authority (power) is used to achieve the defined work objective. Y-C Lai PhD Defence, AAU

  43. Artefact Model <Q&A> • To study the variety of artefact models used. • To study how does the model help to achieve more efficient communication and understanding sharing. • In the case studies, meeting minutes were chosen. Y-C Lai PhD Defence, AAU

  44. Meeting Room Chung (QS) Shawn Henry Log book Log book drawings Chris Log book Meeting Table Lawrence Log book Meeting agenda drawings Alice Log book Log book Pat M Joe Patrick Y Physical Model <Q&A> • To study the connection between the physical environment with the working culture and communication flow. Y-C Lai PhD Defence, AAU

  45. Vannevar Bush – Memex (1945) <Q&A> "He [mankind] has built a civilization so complex that he needs to mechanize his records more fully if he is to push his experiment to its logical conclusion and not merely become bogged down part way there by overtaxing his limited memory." Vannevar Bush, "As We May Think," LIFE 19:11 (1945) Source: ArtMuseum.net, http://www.artmuseum.net/w2vr/timeline/Bush.html Y-C Lai PhD Defence, AAU

  46. Ted Nelson – Hypertext (1963) <Q&A> "Everything is deeply intertwingled" Hypertext diagram from Ted Nelson's Literary Machines Source: ArtMuseum.net, http://www.artmuseum.net/w2vr/timeline/Nelson.html Y-C Lai PhD Defence, AAU

  47. Douglas Engelbart – Augmentation (1968) <Q&A> "Our goal of augmenting the human intellect... will exhibit more of what can be called intelligence than an unaided human could... by organizing his intellectual capabilities into higher levels of synergistic structuring." oNLine System (NLS)demonstration at the 1968 Fall Joint Computer Conference Source: ArtMusuem.net, http://www.artmuseum.net/w2vr/timeline/Engelbart.html# Y-C Lai PhD Defence, AAU

  48. Tim Berners-Lee – WWW <Q&A> • The current web (web 1.0) • Contents are structured in paragraphs of natural language chunks (using for instance the <p></p> tag). • Prominent technologies are hyperlinks and keywords search • Limited support in information processing Y-C Lai PhD Defence, AAU

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