Academic journal article Issues in Informing Science & Information Technology

A Framework for Using Questions as Meta-Tags to Enhance Knowledge Support Services as Part of a Living Lab Environment

Academic journal article Issues in Informing Science & Information Technology

A Framework for Using Questions as Meta-Tags to Enhance Knowledge Support Services as Part of a Living Lab Environment

Article excerpt

Introduction, Background, and Prior Research

This paper continues and expands on research which was presented in 2009 and 2012, in which van der Walt, Buitendag, Jansen Van Vuuren, and Zaaiman (2009) modeled a Living Lab (LL) around a factory concept. Buitendag, van der Walt, Malebane, and de Jager (2012) subsequently expanded the framework to include broader descriptions and presented various operations as services, collectively described as knowledge support services, to be included as part of the Knowledge Factory.

The research is based on a LL designed for an agricultural Community of Practice (CoP) which is also applicable to any knowledge intensive and dependent domains, such as Higher Education, or research and innovation organizations in the public and private sectors. Within the agricultural sector, extension officers often fulfill the role of knowledge agents. Extension offices are key enablers in the provision of knowledge and alternative methods, to persuade clients such as emergent farmers to apply new or improved practices out of their own free will. This includes actions of facilitation within the principles of help to self-help and to prepare clients to better handle future problem situations. Some of the knowledge-operation related problems identified by Buitendag and van der Walt (2011b, p. 70-72) include the following:

* Difficulty in accessing information.

* Lack of access to timeous knowledge.

* Duplication of knowledge resources.

* Inadequacy in interpreting current knowledge sources.

* Poor communication and dissemination of information and knowledge.

Demby (2012, p. 8) exclaimed that one of the biggest problems Africa faces with regard to agricultural extension is the fact that so little emphasis is placed on establishing and maintaining sound knowledge management tools and practices.

Amour (2011) highlighted a common problem experienced by many farmers seeking extension services, by stating that "appropriate advice must be offered to farmers efficiently and regularly Advice is like salt--only give it when asked for!"

From the problems listed it is evident that access to the correct and satisfactory knowledge relating to the questions posed is of cardinal importance for the successful functioning of agricultural extension services.

The predominant research question this article aims to address is as follows:

How can current Knowledge Object metadata models be enhanced to aid effective knowledge discovery in problem solving environments such as Living Labs?

In this paper we also aim to provide new insights, thoughts, and perspectives on the utilization of Learning Objects (LO), based on the LO Metadata standard. We revisit the concept of the Sharable Content Object (SCO) as part of the Sharable Content Reference Model (SCORM), and the classic Dublin Core (DC) metadata standard, based on a literature review. The authors provide their own interpretation of the concept of a Knowledge Object (KO) and highlight how the various activities of a LL may be supported by the implementation of KOs, based on the researchers' definition. We also provide a more detailed description of the functionality of the proposed Question and Answer service that utilize Knowledge Objects, based on questions. The subsequent description and framework proposed in the latter part of this paper are based on design and creation research principles.

Living Labs--An Overview and South African Perspective

Cunningham, Herselman, and Cunningham (2011) define a Living Lab as "systemic initiatives, which focus on creating multi-stakeholder collaboration in different stages of the research, development and innovation (RDI) process. The concept refers to a research and development methodology where innovation such as services, products and application enhancements are created and validated in collaborative, multi-contextual empirical real-world settings. …

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