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