Trustworthy Semantic Web Knowledge Management + E-Business + Semantic Web = Semantic E-Business

1. Trustworthy Semantic Web Knowledge Management + E-Business + Semantic Web = Semantic E-Business Dr. Bhavani Thuraisingham November 3, 2008

2. Outline of the Unit • What is Knowledge Management? • Basic concepts: Components and Models • Organizational Learning Process • Knowledge Management Architecture • Secure Knowledge Management and Trust Negotiation • Knowledge Models • Some efforts • Integration of KM with E-Business and Semantic Web • Reference: IEEE Transactions on Systems, Man and Cybernetics, May 2006 • Chapters 17 and 19 of the textbook

3. What is Knowledge Management • Knowledge management, or KM, is the process through which organizations generate value from their intellectual property and knowledge-based assets • KM involves the creation, dissemination, and utilization of knowledge • Reference: http://www.commerce-database.com/knowledge-management.htm?source=google

4. Knowledge Management Components Knowledge Components of Management: Components, Cycle and Technologies Cycle: Technologies: Components: Knowledge, Creation Expert systems Strategies Sharing, Measurement Collaboration Processes And Improvement Training Metrics Web

5. Knowledge Models • Level 1: Highest Level • Mental models utilized by psychologists • Social models (e.g. social network models) used by sociologists • Level 2: Mid-level • Models utilized by expert systems • Process modeling • Level: Bottom level • Models understood by machines • E.g., rule-based, frame-based, etc.

6. Organizational Learning Process Diffusion - Tacit, Explicit Integration Modification Identification Creation Metrics Action Incentives Source: Reinhardt and Pawlowsky also see: Tools in Organizational Learning http://duplox.wz-berlin.de/oldb/forslin.html

7. Six Principals of Effective Learning • Effective Learning Requires: • Understanding 1) Mental models, paradigms, context, observation, assumptions, opinion, fact, truth 2) Systems Thinking - Variation • Skills 3) Ability to challenge assumptions 4) Listen to Understand • Process 5) Complete observe, assess (reflection, gain understanding), design (develop theory, prediction, vision), implement (test), cycle 6) Teach others

8. Knowledge Management Metrics - The Goal of Metrics • Measuring Success (How am I doing?) • Benchmarking (How am I comparatively doing?) • Tracking Improvement (Am I getting better?) • Direct • future investment (technology, employees) • strategy • alignment (culture, incentives) “One way to ensure your doing worse is to not measure” - Adapted from Pressman

9. Learning By-Product Measures • Papers in Competitive Journals and Magazines • Percentage New Technology compared to all Technology • Process Cycle Time • Employee Surveys • Involvement with decisions • Recognition for work achieved • Access to information • Rewarding risk taking • Overall Satisfaction • Employee Retention • ‘Employee Suggestion Process

10. Knowledge Management: Incentive-based Approaches • Receiver • Positive Incentives • Knowledge Gained • Can teach others what is learned • Teacher • Positive Incentives • “Knowledge Transfer Champion” prestige • Can improve knowledge • Negative Incentives • Time • Unqualified teacher • Negative Incentives • Time • Students not willing to learn

11. Knowledge Management: Strategies, Processes, Metrics and Tools Knowledge Management: Within and Across Corporations and Agencies Strategies e.g., Management Plans; Policies; Data sharing vs. Privacy Processes e.g., best practices Tools e.g., Semantic Web Metrics e.g., web usage

12. Knowledge Management Architecture Knowledge Creation and Acquisition Manager Knowledge Representation Manager Knowledge Dissemination and Sharing Manager Knowledge Manipulation Manager

13. Knowledge Exchange & AnnotationEngine (KEAN) • Resides on any web-accessible knowledge base (any intranet, www) • Increases incentive to share information • Author gets positive and negative feedback about information that is submitted • Feedback system - no more publishing documents that disappear into the ether • Prestige - top rated document views • Quality filters steer user towards best information • Domain specific instances of KEAN are created • Works with Java enabled browser

14. The Three Versions of KEAN Architecture • Version 1 “beta version” • No reuse • Two-tiered • Stored procedures • Version 2 “newest version” • GUI reuse via JavaBeans • Two-tiered • JDBC access to database • Version 3 “final version” • Logic reuse via Enterprise JavaBeans (EJB) • Three-tiered • CORBA access to objects

15. Structure of Version 1 - Beta Version of KEAN Stored Procedures (PL/SQL) ORACLE WEB SERVER • Html • JavaScript • Applets • ORACLE “Thin http” client Database tier

16. Structure of Version 2 Code reuse with a two tier architecture JDBC ORACLE WEB SERVER • KeanBeans • ORACLE “Thick” client Database tier

17. Structure of Version 3 web Server • KeanBeans • RDBMSs • and • OODBMS • CORBA ORB • EJB “thin” client middle tier server tier

18. Secure Knowledge Management • Protecting the intellectual property of an organization • Access control including role-based access control • Security for process/activity management and workflow • Users must have certain credentials to carry out an activity • Composing multiple security policies across organizations • Security for knowledge management strategies and processes • Risk management and economic tradeoffs • Digital rights management and trust negotiation

19. Trust Management and Negotiation • Design a Trust Model • Investigate the current trust models. Identify the inadequacies of current trust models and design a model for the semantic web/DIVO • Components include trust management, trust negotiation as well as economic tradeoffs • Design a Language for specifying Trust policies • Start with XML, RDF and Web Rules language and incorporate features for trust management and negotiation • Design and develop techniques for enforcing the trust policies • Automated Trust Negotiation: A attempts to access database D based on access control policies; However before A can access D, triggers go off and owner of D exchanges credential information with A (

20. Knowledge Management for Coalitions Knowledge for Coalition Export Export Knowledge Knowledge Export Knowledge Component Component Knowledge for Knowledge for Agency A Agency C Component Knowledge for Agency B

21. Status and Directions • Knowledge management has exploded due to the web • Knowledge Management has different dimensions • Technology, Business • Tools are emerging • Need effective partnerships between business leaders, technologists and policy makers • Major direction is integrating E-Business processes and semantic web technologies for knowledge management

22. Semantic E-Business • E-Business processes (e.g., order management, supply chain management, contracts management, workflow management) • Service oriented architectures • Apply semantic web technologies such as XML, RDF, Ontologies and RulesML to represent data and reason about the data for the e-business processes • Results in effective knowledge management as organization is getting benefits • The topic is called Semantic E-Business • IEEE Transactions on Systems, Man and Cybernetics, March 2006

23. Some Efforts - 1 • Messaging (ebMS) : This is a specialization of web services for business to business applications. • Business Process and Collaboration (ebBP) : This set of specification enables collaboration among business partners. • Collaboration Protocol Profile and Agreement (CPPA) : Their effort provides definitions for the sets of information used in business collaborations. • Registry and Repository : The goal of this effort is to come up with specification hat enable interoperable registries and repositories • Core Components (CCTS) : This effort focuses on technologies such as context and content assembly.

24. Some Efforts - 2 • Semantic web technologies have many applications in knowledge management. For example, we need ontologies to capture the represent knowledge and reason about the knowledge. • Paul Warren gives an example on how ”a political scientist, Sally who wants to research the extent to which British Prime Minister Tony Blair's stance on Zimbabwe has changed over a year and what factors might have caused that change.” • He further states that “in the world of the Semantic Web, Sally could search for everything written by Blair on this topic over a specific time period. She could also search for transcripts of his speeches. Information markup wouldn't stop at the article or report level but would also exist at the article section level. So, Sally could also locate articles written by political commentators that contain transcripts of Blair's speeches” • Now knowledge management also has applications for building the semantic web. For example, prior knowledge captured as a result of knowledge management can be used by agents to better understand the web pages. With respect to security, in the example by Warren, confidentiality, privacy and trust policies will determine the extent to which Sally trusts the articles and has access to the articles in putting together her report on Tony Blair’s speeches.

25. Some Efforts: OBELIX • Ontologies have also been developed for e-commerce applications specified in languages such as RDF, RDF-S, OWL and OWL-S • For example, in the Obelix project a very good description of e-business and ontologies is provided. The authors state that a problem with e-commerce is the vague ideas that lack precise description they then discuses their approach which they call e3value which is based on requirements engineering and they define ontologies for e-commerce. • It is stated that “OBELIX is the first ontology-based e-business system of its kind in the world to provide smart, scaleable integration and interoperability capabilities”. • It is also stated that this project “ incorporates ontology management and configuration, an e-business application server and ontology-based e-application tools as well as an e-business library.” • OBLEIX is a European Commission project and the goal is to automate e-business services in a semantic web environment which has come to be called semantic e-business.