Knowledge Structuring for Sustainable Development and the Hozo Tool

Knowledge Structuring for Sustainable Development and the Hozo Tool

Jenny S. Huang (iFOSSF, USA), Kouji Kozaki (Osaka University, Japan) and Terukazu Kumazawa (Research Institute for Humanity and Nature, Japan)
DOI: 10.4018/978-1-5225-0905-9.ch008
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The search for more actionable knowledge lies at the core of Sustainability Science and its implicit desire to improve the lives of various stakeholders without disrupting the balance of Nature and efficient use of all available resources. In this chapter, the authors have examined current shortfalls in knowledge-centric research and proposed the creation of an Ontology-based open-source tool to create a more practical approach for researchers to facilitate both thought and decision-making process in order to solve pressing issues with place-based actions. The effectiveness of the Hozo Tool is then examined and validated using four case studies in an attempt to both refine the current models and propose the necessary steps to create a more holistic knowledge ecosystem – one that might ultimately facilitate broader collaboration worldwide.
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Sustainability Science is still a relatively new field, there is currently no well-established curriculum or infrastructure to facilitate multi-stakeholder knowledge creation and action. As a result, many of the Sustainable Development projects are still taking a silo approach – one in which researchers and scholars attempt to gain knowledge first and then figure out how that knowledge can be transformed into community action. In other words, many development projects take a top-down approach, one where end-user needs are not fully explored until much later in the process. The SEED Framework (Huang, Hsueh, & Reynolds, 2013) argues for a different approach: that is, creating a framework to foster an environment that channels the creativity of the community towards discovering opportunities for development. It assumes a knowledge-based approach that leverages global intelligence and then refines it for place-based applications and new-knowledge development. Its global and local multi/interdisciplinary development model can be implemented using the following six iterative steps for a knowledge driven innovation lifecycle.

Figure 1.

Community focused innovation and knowledge ecosystem

Huang, Hsueh, & Reynolds, 2013.

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