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Modelling of the complex societal problem of establishing a national energy sufficiency competence

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dc.contributor.author Roodt, JH
dc.contributor.author Leenen, L
dc.contributor.author Van Vuuren, JJ
dc.contributor.author Dawood, Zubeida C
dc.date.accessioned 2021-03-07T18:30:58Z
dc.date.available 2021-03-07T18:30:58Z
dc.date.issued 2020-07
dc.identifier.citation Roodt, J., Leenen, L., Van Vuuren, J. & Dawood, Z.C. 2020. Modelling of the complex societal problem of establishing a national energy sufficiency competence. http://hdl.handle.net/10204/11836 . en_ZA
dc.identifier.isbn 978-0-578-64709-8
dc.identifier.isbn 978-1-7281-6830-2
dc.identifier.uri http://hdl.handle.net/10204/11836
dc.description.abstract Complex societal problems require a multidisciplinary and multi-method approach to develop models that can support the development of solutions. General morphological analysis is a qualitative method to extract information from experts through facilitation and the use of customized software. Ontologies provide semantic representation of knowledge bases together with automated reasoning capabilities. These two approaches, combined with the use of concept maps, provide an integrated approach which can be used to understand complex and ill-structured problem domains and to aid in business modelling, strategy and scenario development and finally, decision-making. The resulting models are subjective constructs reflecting the knowledge and understanding of the analysts. Subsequent synthesis of new understanding and decisions rely on the robust validation and verification of the underlying logic and assumptions of the conceptual models. Morphological Analysis and ontological constructs are applied in terms of an integrated Morphological Ontology Design Engineering methodology (MODE), which is based on Design Science. The paper is developed around the opportunity of scoping the applied research competence required to support a nation's progress toward energy sufficiency. This paper presents a complex fused model for national energy sufficiency in New Zealand. The approach can be used to address other ill-structured complex societal problems. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri DOI: 10.23919/FUSION45008.2020.9190332 en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9190332 en_US
dc.source IEEE 23rd International Conference on Information Fusion (FUSION), Rustenburg, South Africa, 6-9 July 2020 en_US
dc.subject Energy sufficiency en_US
dc.subject Morphological analysis model en_US
dc.subject Morphological ontology design engineering en_US
dc.subject Ontologies en_US
dc.title Modelling of the complex societal problem of establishing a national energy sufficiency competence en_US
dc.type Conference Presentation en_US
dc.description.pages 8pp en_US
dc.description.note Copyright: 2020 IEEE. Due to copyright restrictions, the attached PDF file contains the abstract of the full-text item. For access to the full-text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9190332 en_US
dc.description.cluster Defence and Security
dc.description.impactarea Information Security Centre
dc.identifier.apacitation Roodt, J., Leenen, L., Van Vuuren, J., & Dawood, Z. C. (2020). Modelling of the complex societal problem of establishing a national energy sufficiency competence. http://hdl.handle.net/10204/11836 en_ZA
dc.identifier.chicagocitation Roodt, JH, L Leenen, JJ Van Vuuren, and Zubeida C Dawood. "Modelling of the complex societal problem of establishing a national energy sufficiency competence." <i>IEEE 23rd International Conference on Information Fusion (FUSION), Rustenburg, South Africa, 6-9 July 2020</i> (2020): http://hdl.handle.net/10204/11836 en_ZA
dc.identifier.vancouvercitation Roodt J, Leenen L, Van Vuuren J, Dawood ZC, Modelling of the complex societal problem of establishing a national energy sufficiency competence; 2020. http://hdl.handle.net/10204/11836 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Roodt, JH AU - Leenen, L AU - Van Vuuren, JJ AU - Dawood, Zubeida C AB - Complex societal problems require a multidisciplinary and multi-method approach to develop models that can support the development of solutions. General morphological analysis is a qualitative method to extract information from experts through facilitation and the use of customized software. Ontologies provide semantic representation of knowledge bases together with automated reasoning capabilities. These two approaches, combined with the use of concept maps, provide an integrated approach which can be used to understand complex and ill-structured problem domains and to aid in business modelling, strategy and scenario development and finally, decision-making. The resulting models are subjective constructs reflecting the knowledge and understanding of the analysts. Subsequent synthesis of new understanding and decisions rely on the robust validation and verification of the underlying logic and assumptions of the conceptual models. Morphological Analysis and ontological constructs are applied in terms of an integrated Morphological Ontology Design Engineering methodology (MODE), which is based on Design Science. The paper is developed around the opportunity of scoping the applied research competence required to support a nation's progress toward energy sufficiency. This paper presents a complex fused model for national energy sufficiency in New Zealand. The approach can be used to address other ill-structured complex societal problems. DA - 2020-07 DB - ResearchSpace DP - CSIR J1 - IEEE 23rd International Conference on Information Fusion (FUSION), Rustenburg, South Africa, 6-9 July 2020 KW - Energy sufficiency KW - Morphological analysis model KW - Morphological ontology design engineering KW - Ontologies LK - https://researchspace.csir.co.za PY - 2020 SM - 978-0-578-64709-8 SM - 978-1-7281-6830-2 T1 - Modelling of the complex societal problem of establishing a national energy sufficiency competence TI - Modelling of the complex societal problem of establishing a national energy sufficiency competence UR - http://hdl.handle.net/10204/11836 ER - en_ZA
dc.identifier.worklist 24189 en_US


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