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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorReiners, Torsten
dc.contributor.authorBurke, Gary
dc.date.accessioned2017-11-24T05:24:50Z
dc.date.available2017-11-24T05:24:50Z
dc.date.created2017-11-24T04:48:40Z
dc.date.issued2017
dc.identifier.citationNimmagadda, S. and Reiners, T. and Burke, G. 2017. Big Data Guided Design Science Information System (DSIS) Development for Sustainability Management and Accounting. Procedia Computer Science. 112: pp. 1871-1880.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/58265
dc.identifier.doi10.1016/j.procs.2017.08.233
dc.description.abstract

Sustainability is a dynamic, complex and composite data relationship among geographically distributed human and environment ecosystems. The ecosystems may have strong interactions among their elements and processes, but with dynamic implicit boundaries. Multi-scalable and multidimensional ecosystems have significance based on a commonality of basic structural units and domains. We intend to develop a holistic information system for managing different ecosystems within a sustainability framework/context, using an empirical qualitative and quantitative interpretation and analysis of the measured observations. Design Science Research (DSR) approach is aimed at developing an information system using the volumes of unstructured Big Data observations. Collaborating multiple domains, interpreting and evaluating the commonality, uncovering the connectivity among multiple systems are key aspects of the study. The Design Science Information System (DSIS), evolved from DSR approach is used in solving the ecosystem issues associated with multiple domains, in which the sustainability challenges manifest. In this context, we propose a human-environment-economic ecosystem (HEES) framework consisting of human, environment and economic elements and processes. In broad terms, human, environment and economic domains are conceptualized as different players/agents that operate within a range of sustainability scenarios. This approach recognizes the existing constraints of the systems as well as the emerging knowledge of the boundaries of ecosystems and their connectivity. The connectivity and interaction among the systems are analyzed by data mining, visualization and interpretation artefacts within a sustainability policy framework.

dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleBig Data Guided Design Science Information System (DSIS) Development for Sustainability Management and Accounting
dc.typeConference Paper
dcterms.source.volume112
dcterms.source.startPage1871
dcterms.source.endPage1880
dcterms.source.issn1877-0509
dcterms.source.titleProcedia Computer Science
dcterms.source.seriesProcedia Computer Science
curtin.departmentSchool of Information Systems
curtin.departmentCurtin University Sustainability Policy Institute
curtin.accessStatusOpen access


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