Conceptual Foundations for a Service-Oriented Knowledge & Learning Architecture: Supporting Content, Process, and Ontology Maturing Andreas Schmidt Knut Hinkelmann Stefanie Lindstaedt Tobias Ley Ronald Maier Uwe Riss http://mature-ip.eu I-KNOW 2008 Special Track on Knowledge Services September 3, 2008

Outline Motivation why we need a service-oriented knowledge & learning architecture Conceptual foundations Knowledge maturing process model Seeding-Evolutionary Growth-Reseeding model Implications Maturing services: seeding, growth, reseeding Conclusions MATURE - Continuous Social Learning in Knowledge Networks

Motivation

why we need a service-oriented knowledge & learning architecture

Conceptual foundations

Knowledge maturing process model

Seeding-Evolutionary Growth-Reseeding model

Implications

Maturing services: seeding, growth, reseeding

Conclusions

Motivation

Motivation Agility of enterprises as a key success factor requires Leveraging the employees‘ creativity and hands-on experience Improving the sharing of knowledge within and across company borders Support with a new form of organizational guidance Instead of top-down approaches we need a balance of top-down and bottom-up developments for learning support Bring together the efficiency of organizations and the engagement and user empowerment MATURE - Continuous Social Learning in Knowledge Networks

Agility of enterprises as a key success factor requires

Leveraging the employees‘ creativity and hands-on experience

Improving the sharing of knowledge within and across company borders

Support with a new form of organizational guidance

Instead of top-down approaches we need a balance of top-down and bottom-up developments for learning support

Bring together the efficiency of organizations and the engagement and user empowerment

The MATURE Vision

Need for service-oriented infrastructure Such mashup toolsets like the PLME and OLME have to be flexible and extensible This will only work with a service-oriented infrastructure that provides basic and rather generic functionality But how should such an infrastructure look like? What are conceptual foundations? MATURE - Continuous Social Learning in Knowledge Networks

Such mashup toolsets like the PLME and OLME have to be flexible and extensible

This will only work with a service-oriented infrastructure that provides basic and rather generic functionality

But how should such an infrastructure look like? What are conceptual foundations?

MATURE - Continuous Social Learning in Knowledge Networks http://mature-ip.eu Conceptual Foundations

Knowledge Maturing Process Model MATURE - Continuous Social Learning in Knowledge Networks Based on [Schmidt, 2005] and [Maier & Schmidt, 2007]

Knowledge Maturing Process Model (2) MATURE - Continuous Social Learning in Knowledge Networks content maturing ontology maturing (incl. competencies) process maturing

Seeding – Evolutionary Growth - Reseeding Model for design processes in communities by Fischer Seeding Evolutionary Growth Reseeding MATURE - Continuous Social Learning in Knowledge Networks

Model for design processes in communities by Fischer

Seeding

Evolutionary Growth

Reseeding

MATURE - Continuous Social Learning in Knowledge Networks Implications on the service architecture

Maturing Services We need services that Interconnect different tools for different types of knowledge assets Support the flow between the different levels We call such services maturing services . MATURE - Continuous Social Learning in Knowledge Networks

We need services that

Interconnect different tools for different types of knowledge assets

Support the flow between the different levels

We call such services maturing services .

Maturing Services: Seeding Service enable the user to set up and initialize knowledge units and structures within a community associative network based on document similarities user models based on social network analysis recommendation based on user model and associative network MATURE - Continuous Social Learning in Knowledge Networks

enable the user to set up and initialize knowledge units and structures within a community

associative network based on document similarities

user models based on social network analysis

recommendation based on user model and associative network

Maturing Services: Growth Services Allows users to add new knowledge units (e.g. documents or users), to adapt their characteristics (e.g. the users’ competencies) to provide comments to change the system behaviour. based on the Web2.0 paradigm User-generated content Exploiting collective usage data MATURE - Continuous Social Learning in Knowledge Networks

Allows users

to add new knowledge units (e.g. documents or users),

to adapt their characteristics (e.g. the users’ competencies)

to provide comments

to change the system behaviour.

based on the Web2.0 paradigm

User-generated content

Exploiting collective usage data

Maturing Services: Reseeding Services allow the user to analyse and visualize the collective activities of the community to negotiate between conceptualizations of different users and to change the underlying structures and functionalities . MATURE - Continuous Social Learning in Knowledge Networks

allow the user

to analyse and visualize the collective activities of the community

to negotiate between conceptualizations of different users and

to change the underlying structures and functionalities .

Conclusions Maturing services enable the creation of learning environments as a set of loosely coupled tools. The knowledge maturing process model structures the learning landscape (from informal to formal) and focuses on the dynamics, the interaction and transitions between different forms of learning and knowledge. The SER model inspires types of system invention The approach create a flexible and dynamic knowledge and learning architecture combines bottom-up, end-user driven activities with organizational guidance. MATURE - Continuous Social Learning in Knowledge Networks

Maturing services enable the creation of learning environments as a set of loosely coupled tools.

The knowledge maturing process model

structures the learning landscape (from informal to formal) and

focuses on the dynamics, the interaction and transitions between different forms of learning and knowledge.

The SER model inspires types of system invention

The approach

create a flexible and dynamic knowledge and learning architecture

combines bottom-up, end-user driven activities with organizational guidance.

MATURE More information on http://mature-ip.eu MATURE - Continuous Social Learning in Knowledge Networks

More information on http://mature-ip.eu