24.06.03 NEW: Roadmap 2003 Knowledge Management Period 2003 - 2010

24.06.03

NEW: Roadmap 2003

Knowledge Management

Period 2003 - 2010

24.06.03

2003

2005

Conceptual Retrieval

Ad-Hoc/CollaborativeWork Organization

Self-OrganizingArchives

Knowledgee-Trading Platform

CollaborativeKnowledgeEvolution

UnintrusiveKnowledge Acquisition

Evolutionary & collaborativeKnowledge Organization

Need-drivenKnowledge Exploitation

Technology Roadmap for the DFKI Department Knowledge Management 2003-2005

Communicating OntologyAgents

Profile Observation & Learning

Collaborative, Profile-Oriented

Question Answering

Virtual Enterprise Environment

Explication of Information Needs

SustainableOntologies

Knowledge as Commodity

ContextIdentification by Observation

Attention-basedIndexing

Individualized Task Assistant

Profile-Based Story Highlighting

Soft-Concept Capturing

HypermediaFact Mining

Teaching on demand

Document evolution

Support for Dynamic Task Sequences

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2006

2010

2008

Knowledge Quality Models




IndividualizedBusiness Associate

Knowledge Quality Management

Adaptive OM Structuring

Living Organizational Memories

Co-operativeOM Societies

Trend Scouting

Knowledge “On the Fly”

Confidentiality Assurance

Self-OrganizingDocuments


Collaborative Information Retrieval

Sharable Business Rules

Concept Negotiation

Wide-AreaKnowledge

ServicesInteracting Ontologies

Knowledge Assessment Procedures

Competence Mapping

Personal Knowledge Workspace

Personal Adaptive Memory

Competence Crawler

Context Mining

Situated Knowledge Partners

Personal Knowledge Representatives

Competence Learner

Context-Specific Individual Knowledge Delivery

Trust signets

Information squalls

Holistic retrieval

Experience gathering

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EvolutionaryKnowledge organization

Need-driven Knowledge Exploitation

Profile-mapping and Profile-

merging with vague

concepts

Acquisition and

exploitation of weak

processes

Pro-active Reasoning on

Formal and Informal

Structures

Utilization of Individual

Knowledge Workspaces

Formalization of User

Profiles, Task Models,and Information Needs

Configurable Generic

Analysis Modules &

Services

Models for Knowledge Life

Cycles

Handling of Cross-border

Knowledge

Metrics for Knowledge

Assessment

Multi-criteria Knowledge

Structuring

Methods for Successful Knowledge Management Introduction & Evaluation

Learning, Agent-based Ontology Negotiation, Automated Knowledge Exchange

Semantic Web Technologies, Web Service Applications, P2P

Research Roadmap for the DFKI Department Knowledge Management 2003-2010

24.06.03

Technology Roadmap

Knowledge Managementextension - 2010

• All objectives of the previous roadmap are still valid.• Main modifications/extensions comprise

– we envision new ways of interacting with information. Evolving documents reflect a kind of interaction dialog.

– We aim at a more comprehensive view on legality and privacy aspects of the workspace formalization and knowledge exchange. Means to create trust (in addition to quality and confidentiality) are a prominent result of that.

– Innovative approaches to a holistic interaction with and in complex knowledge spaces offer a new way to grasp represented knowledge. This aspect offers multiple opportunities for collaboration with the IVS department.

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Technology Roadmap


Main modifications comprise• We emphasize the mid-term vision of Knowledge as Commodity, the generic

Knowledge Market Place has been replaced by a specific e-Trading Plattform to be developed.

• The handling and representation of competences gained increased interest• Process aspects of knowledge quality are newly introduced• The identification of Personal Knowledge Workspaces as a prime resource for

acquisition and evolutionary organization of knowledge leads to new developments on the personal (PAM) and enterprise level (dialog-oriented ‘knowledge partners’)

• The development is towards increased service orientation and systematic evaluation/testing methods

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Technology Roadmap


Main modifications comprise• collaborative aspects, coupled with machine learning approaches, gain

increasing interest• Development is aimed - beyond static, representation-centered ontology

techniques - towards more active and autonomous services and responsibilities• Knowledge objects encompass operative knowledge with corresponding rule-

based, web-enabled representations• Collaboration, communication, and social roles fit with the vision of web-based,

semantically enhanced exchange.

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Glossary

Explanations / Extensions to Roadmap I

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Unintrusive Knowledge Acquisition

• Knowledge Acquisition and (partial) formalization is necessary in order to transform knowledge into an object of exchange and automatic processing. This has to be done as un-intrusive as possible, as the user considers additional formalization work to be a nuisance and tends to discard this as un-necessary burden.

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24.06.03

Evolutionary Knowledge Organization

• Acquired Knowledge has to be organized in suitable ways. This is done by representing explicit relations to formal models (Knowledge Organization). Possible models comprise descriptions of relevant objects and concepts (ontologies) and structures of the enterprise (all these are relatively stable), but also models of dynamic processes and their enactment in workflows. Creation and maintenance of the structuring models need to be done in an evolutionary way as a purely static approach is not suitable in continuously changing situation of an enterprise.

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• Knowledge has to be made available for application. This has to be done in accordance with individual and / or situation-specific needs.

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Ad-Hoc/Collaborative Work Organization

• Flexible structures of organizations and project-oriented cooperation across enterprise borders lead to new organization of work.In order to be able to deliver useful information support in these innovative situations, the structure and the organization of knowledge has to be adapted to changing and short-lived organizational structures.

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Attention-based Indexing

• Observation of the interaction between user and information elements helps to identify the degree of attention which is paid to different information elements. This is used to infer adequate indes structures.

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Collaborative Knowledge Evolution

• Interaction between members of a community lead to continuous re-interpretation of information elements, thus to the generation of new knowledge. These communication processes are to be observed and identified in order to infer structures (which can grow evolutionary) and knowledge elements (which can be formalized incrementally)

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Collaborative, Profile-Oriented Question Answering

• Profiles and structures deduced from community-internal interaction are used to infer the information need of the community members. Thus queries can be answered correctly and in accordance with the intentions of the group members. Collaborative Question Answering goes beyond pure information retrieval as the original information sources might be transformed to better suit the problem at hand.

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Communicating Ontology Agents

• Information exchange between multiple ontologies which have been created in different contexts requires suitable agent-based communication protocols.

• Basics completed in FRODO, work continues in EPOS

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• User‘s queries are answered based on a concept-based representation of information content, together with ontologies which represent background knowledge about the concepts.

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Context Identification by Observation

• The current work context is inferred from the observation of a user‘s actions. The context information is used to facilitate specific support.

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Context in Weak Workflow

• How can we employ dynamically modeled workflows (which are modified at runtime) as a useful context representation?

• Use of explicitly-modelled business processes and static workflows as context representation has been successfully investigated in KNOWMORE, DECOR etc.

• Now we are going to extend this approach towards dynamically modelled, weakly-structured workflows.

• Successfully done in FRODO, used in EPOS

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24.06.03

Document evolution

• User interacts with the document via multi-modal feedback: natural language annotation, mark-up and highlighting, feedback about suggested similar documents.

• Based on the interaction the document adapts itself to the situative needs of individuals– e.g. dynamic extension of background information and

integration into the original document

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24.06.03

Document Similarity Assessment

• Assess the similarity of documents by analyzing their content

– mostly done by the PROFILER development, currently no further basic research intended;

– application of the technique, however, continues in various projects (EPOS, ELENA, ...)

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Explication of Information Needs

• Development of explicit representations of context-specific information needs.

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Fact/Concept Extraction

• Identification and formal representation of relevant facts and concepts from documents.

• Cf. INKASS, AdREAD, ...

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Format Normalization

• Transform documents into standard representations

• ProFiler transforms to html

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Goal-Specific Abstracting

• Summarization of document content in accordance with individual and context-specific information needs

• partially done in AdREAD

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Hypermedia Fact Mining

• Identification / extraction of formalized knowledge from hypermedia elements;exploitation of text, image, sound etc. content; but also link structures between elements

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• Personal, task-specific support which takes context and individual interests into account.

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• Knowledge is transformed into / represented as an object which can be exchanged and traded.

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Knowledge e-Trading Platform

• Knowledge trading requires new trading tools and parameters. We develop suitable internet-based platforms; e.g. in the INKASS project.

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• Emphasizing/highlighting of document passages according to individual interest profiles

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Profile Observation & Learning

• User‘s interaction with information elements is observed; profiles are learned which represent the user‘s interests.

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Self-Organizing Archives

• Archives adapt to changes in their environment by modifying structures and / or content.

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Soft-Concept Capturing

• Terms/concepts in knowledge networks are fuzzy and short-lived in their interpretation. This fuzziness has to be represented (e.g. using Bayes networks), changes in concept definitions shall be identified automatically.

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• Standard process definitions are static, modern forms of work require task sequences to be handled as weak workflows

• We investigate process-oriented knowledge management on the basis of weak workflows

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Sustainable Ontologies

• Ontologies represent the shared conceptualization of a community. This can change over time. We develop methods and technology to adapt concept definitions and ontology structures to these changes in order to achieve long-term validity of ontologies.

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Teaching on demand

• Personalized collation, delivery and presentation of e-Learning material– cf. Activities in ELENA and ProFinder projects

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24.06.03

Text-supported Ontology Construction

• Interactive processes to create ontologies based on the analysis of available text corpora (which contain a group‘s shared understanding)

• cf. INKASS, FRODO, KNOWMORE

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24.06.03

Virtual Enterprise Environment

• Project-oriented cooperation across enterprise boundaries require new ways of information exchange and support. Concepts like ‚organization model‘, ‚role‘, ‚business process‘ are less static in the new environment.

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24.06.03

Glossary

Explanations / Extensions to Roadmap II

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24.06.03

Adaptive OM structuring

• OM structures adapt automatically to new situations.• An OM can adapt by

– changing the structures used for knowledge organization

– changing the information elements (its content)• this is supported by self-organizing documents

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Collaborative Information Retrieval

• Exploit the interactions / queries / feedback of a community in a retrieval process in order to improve the answering of individual queries.

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Competence Crawler

• Find competence profiles in websites; identification of competence profiles in the world-wide web

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24.06.03

Competence Learner

• Automatic creation of profiles which describe individual competencies

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Competence Mapping

• Comparison of competence description and requested competence profile; identification of competence profiles which are suitable for a specific job descripiton

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Concept Negotiation

• Exchange and negotiation between agents in order to find a common interpretation of concepts which differ in various ontologies; e.g. based on comparison of instances.

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• Knowledge inserted into an OM may only be accessible to users with suitable authorization

• Definition and representation of ‘levels of confidentiality; evaluation models for knowledge elements wrt. confidentiality.

• Can we hide sensitive parts of document automatically?

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Context Mining

• Identification of context descriptions in a data stream which represents the observed user interaction

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Context-specific individual knowledge delivery

• Context = user, task, role, group, enterprise ...• Including 2nd level context, e.g. organizational objectives,

market situation ...

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Co-operative OM societies

• Real world requires not one single OM, but collections of several different OMs which need to interact. Societies of cooperating OMs require– ontology societies (to reach interaction / understanding on the

concept level, including networks of cooperative, dynamically evolving ontology agents

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24.06.03

Evolutionary & collaborative Knowledge Organization

• Investigation of collaboration aspects of Evolutionary Knowledge Organization

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Experience gathering

• Implicit knowledge elements are observed and identified by handling expertise in the context of work activities and subsequently made explicit

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Holistic retrieval

• Virtual information spaces are made accessible via data glove gestures and/or multi-dimensional cluster presentation.

• Focus on goal-directed visualization of knowledge/content characteristics– combine ideas of DAU and mind map concepts with virtual

reality– innovative approach to interaction with information spaces

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24.06.03

Individualized Business Associate

• Our long-term research remains in the context of enterprises. We attempt to realize individualized / individualizable assistent systems. Thus this long-term vision.

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Information squalls

• Dynamic presentation of information structures in 3D spatial visualizations in varying information dimensions– info dimensions might be freely configurable to suit individual

needs and relevance– are build upon knowledge/content features

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Interacting Ontologies

• Solution of complex reasoning tasks by exchange and interaction between ontologies, based on inter-agent communication.

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• Methodology to assess the value and/or quality of knowledge– cf. the approach/processes developed in the

MedCertain/MedCIRCLE projects

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Knowledge on the fly

• Necessary knowledge shall arrive ‘on ist own’ whenever and whereever it is needed

• No need for the user to search / browse

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• Definition of suitable processes for knowledge quality management – Quality of Organizational Memories and Knowledge Elements shall

be assessed.

– How to define ‘value of knowledge?

– How to knowledge elements age?

– How to guarantee a level of quality for stored knowledge (according to some knowledge quality model)?

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• Basis for Knowledge Quality Management• Which attributes can be used to describe knowledge quality?

– E.g. actuality, correctness, invariance wrt. context modifications - which equals transferrability, availability

• Which measurements do exist?• Precision/Recall• user feedback

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• Focus on the dynamic aspects of an OM:Situation-adapted oblivion, learning of new structures.– dynamic creation

– adaptation

– situation-specific access

– long-time maintenance

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Wide-Area Knowledge Services

• Transgression from individual and organizational memories to defined knowledge services which are offered across the world-wide web.

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Personal Adaptive Memory

• A personal assistant which continuously acquires and structures information and delivers them in situation-specific ways if needed.

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• Personal, inter-connected systems which exchange individual knowledge in a useful way, thus generating new knowledge. The system acts as a personal representative (aka speaker) in questions of knowledge.

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• The personal workspace (e.g. the PC) contains data and structures which reflect individual views, tasks, and information needs. By leveraging these into explicit representations of personal knowledge the personal knowledge workspace is created.

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Sharable Business Rules

• Enterprise-specific knowledge about information processing is explicitly coded in business rules. Standard formalisms (like RuleML) allow the exchange.

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Self-organizing Documents

• According to the actual user context, specific documents are created based on available collections and version managements (history).– The document adapts e.g. by hiding irrelevant parts according to

the actual need.

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• The combination of individual information support and automatic dialog / cooperation components results in a new vision of support for knowledge exploitation: autonomous components which are deeply integrated into concrete application contexts offer knowledge services and communicate both among themselves and with the user.

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Trend Scouting

• Meta level in ontology handling and maintenance:• Are there new concept lines to be identified?• Can we detect evolutionary directions?• What’s trendy?

• Analysis of document collections in order to identify current developments / trends

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Trust signets

• Develop means to signal, guarantee, and enforce trust-worthiness of information elements and knowledge chunks– may include the investigation of methodologies to build up

trust between parties

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Roadmaps 2002

Period 2002 - 2009

Topics which have been achieved in the last year

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2002

2004

Fact/ConceptExtraction

Context inWeak Workflow

FormatNormalization


Goal-SpecificAbstracting

Ad-Hoc/CollaborativeWork Organization

DocumentSimilarity Assessment

Self-OrganizingArchives

Knowledgee-Trading Platform

CollaborativeKnowledgeEvolution


EvolutionaryKnowledge Organization



Communicating OntologyAgents

Text-supported Ontology Construction

Profile Observation & Learning Collaborative, Profile-

OrientedQuestion Answering

Virtual Enterprise EnvironmentExplication of Information

Needs

SustainableOntologies


ContextIdentification by Observation

Attention-basedIndexing

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2005

2009

2007





IndividualizedBusiness Associate


Adaptive OM Structuring




Co-operativeOM Societies

Context-Specific Individual Knowledge Delivery


Soft-Concept CapturingHypermedia

Fact Mining

Trend Scouting

Knowledge “On the Fly”


Self-OrganizingDocuments


Collaborative Information RetrievalSharable

Business RulesConcept Negotiation

Wide-AreaKnowledge

ServicesInteracting Ontologies


Competence Mapping


Personal Adaptive MemoryCompetence Craw

ler

Context Mining



Competence Learner

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EvolutionaryKnowledge organization


Profile-mapping and Profile-

merging with vague

concepts

Learning of Individual

Workflow

Pro-active Reasoning on

Formal and Informal

Structures

Utilization of Individual

Knowledge Workspaces

Formalization of User

Profiles, Task Models,and Information Needs

Configurable Generic

Analysis Modules &

Services

Models for Knowledge Life

Cycles

Handling of Cross-border

Knowledge

Metrics for Knowledge

Assessment

Multi-criteria Knowledge

Structuring

Methods for Successful Knowledge Management Introduction & Evaluation

Learning, Agent-based Ontology Negotiation, Automated Knowledge Exchange

Semantic Web Technologies, Web Service Applications, P2P

Research Roadmap for the DFKI Department Knowledge Management 2002-2009

24.06.03

Schmierzettel

24.06.03Employment

on the fly

Mental models

Intention forecasting

Knowledge creation processes

Privacy & legalitycontext privacy

Multi Media

Holistic information interaction

Knowledge dependency

exploitation ???