Strands of Knowledge Maturing Support

In a nutshell

Knowledge maturing has several strands: content, process, semantics, and people. Each of them has different characteristics which lead to different forms of support.

Sub sections

Parent section

Concept of Knowledge Maturing

Key publication to cite

2009

Andreas {Schmidt, Knut Hinkelmann, Tobias Ley, Stefanie Lindstaedt, Ronald Maier, Uwe} Riss
{Conceptual Foundations for a Service-oriented Knowledge and Learning Architecture: Supporting Content, Process and Ontology Maturing}
In: {Schaffert, Sebastian and Tochtermann, Klaus and Pellegrini, Tassilo} (eds.): {Networked Knowledge - Networked Media: Integrating Knowledge Management, New Media Technologies and Semantic Systems}, {Springer}, 2009

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Abstract {Effective learning support in organizations requires a flexible and personalized toolset that brings together the individual and the organizational perspective on learning. Such toolsets need a service-oriented infrastructure of reusable knowledge and learning services as an enabler. This contribution focuses on conceptual foundations for such an infrastructure as it is being developed within the MATURE IP and builds on the knowledge maturing process model on the one hand, and the seeding-evolutionary growth-reseeding model on the other hand. These theories are used to derive maturing services, for which initial examples are presented.}

Similar to the diversity of knowledge, there are many aspects of knowledge maturing in organizations. A closer investigation reveals that four major strands can be distinguished:

  • Content. Explicit knowledge that is represented in books, presentations, wiki articles, or other documents evolves in co-development processes from personal notes via presentations and reports to text books and e-learning courses. Classical approaches to this strand introduce editorial and formal release processes, which limit participation and create time lags. From a knowledge maturing perspective, community-driven approaches to quality assurance as well as low barrier sharing and collaboration are in the focus.
  • Process. The knowledge how to produce or deliver products and services is the key competency of an organization. This starts from individual employee managing their tasks, via teams' collaboration pattern up to company-wide business processes. This knowledge how to do things is shared across the contributors, and can be both explicit and implicit. While most other approaches concentrate on formal process models and attempt to automate the respective processes, a knowledge maturing inspired perspective looks at the development of such models from individual practice and the importance of sharing expertise that cannot be easily formalized.
  • Semantics. Social systems require a shared understanding and shared vocabulary and continuously negotiate it as part of their interactions. This ranges from indexing the wealth of content to relate it to workplace practice to naming and labeling topics and competencies on a strategic level to be able to set goals for development and monitor them. Instead of experts or expert groups as proposed in many ontology engineering approaches, the knowledge maturing perspective concentrates on exploiting the continuous negotiation processes and tagging behavior.
  • People. Knowing who knows what and who can approaches for a specific topic is an essential element of learning and working. The development of this knowledge is closely related to individuals building their social networks, but also to the organization's systematic approaches to human resources development. From a knowledge maturing perspective, top-down competence management needs to be complemented with a bottom-up approach that is aligned with social networking interests of individuals.