The document outlines conceptual foundations for a service-oriented knowledge and learning architecture aimed at enhancing the agility of enterprises by fostering employee creativity and knowledge sharing. It introduces a knowledge maturing process model involving seeding, evolutionary growth, and reseeding services to create dynamic learning environments and emphasizes the importance of balancing top-down and bottom-up approaches. The goal is to design an infrastructure that supports the interconnection of various knowledge assets and enhances collaborative learning within organizations.

1. 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

2. 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

3. Motivation

4. 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

5. The MATURE Vision

6. 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

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

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

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

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

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

12. 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

13. 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

14. 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

15. 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

16. 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

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