Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts

The embeddedness of ecosystems interpreted as the connectivity between data sources has been the research focus of ecosystem service providers. Heterogeneity of data sources,linked with embedded systems,is challenging in the ecosystem integration process. Big data is an added motiva...

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Main Authors: Nimmagadda, Shastri, Namugenyi, Christine, Mani, Neel, Reiners, Torsten
Format: Conference Paper
Published: 2020
Online Access:https://creativecommons.org/licenses/by-nc/3.0/nz/
http://hdl.handle.net/20.500.11937/81900
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author Nimmagadda, Shastri
Namugenyi, Christine
Mani, Neel
Reiners, Torsten
author_facet Nimmagadda, Shastri
Namugenyi, Christine
Mani, Neel
Reiners, Torsten
author_sort Nimmagadda, Shastri
building Curtin Institutional Repository
collection Online Access
description The embeddedness of ecosystems interpreted as the connectivity between data sources has been the research focus of ecosystem service providers. Heterogeneity of data sources,linked with embedded systems,is challenging in the ecosystem integration process. Big data is an added motivation in the ecosystem integration process. The purpose of the research is to provide an improved understanding of ecosystem inherent connectivity by integrating multiple ecosystems through their big data in a multidimensional repository system, with a focus on data analytics. We need an architecture to drive the composite congruence existing between disease-human-environment-business systems.We propose an Embedded Digital Ecosystem Architecture (EDEA), from which the associations hidden among big data sources of multiple ecosystems are analysed in new knowledge domains. We construe in our research that pandemic-related disease ecologies have connectivity with the human, environment and economic ecosystems,ascertaining the potential benefits of data science in embedded digital ecosystems’ research.
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spelling curtin-20.500.11937-819002021-02-05T03:54:23Z Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts Nimmagadda, Shastri Namugenyi, Christine Mani, Neel Reiners, Torsten The embeddedness of ecosystems interpreted as the connectivity between data sources has been the research focus of ecosystem service providers. Heterogeneity of data sources,linked with embedded systems,is challenging in the ecosystem integration process. Big data is an added motivation in the ecosystem integration process. The purpose of the research is to provide an improved understanding of ecosystem inherent connectivity by integrating multiple ecosystems through their big data in a multidimensional repository system, with a focus on data analytics. We need an architecture to drive the composite congruence existing between disease-human-environment-business systems.We propose an Embedded Digital Ecosystem Architecture (EDEA), from which the associations hidden among big data sources of multiple ecosystems are analysed in new knowledge domains. We construe in our research that pandemic-related disease ecologies have connectivity with the human, environment and economic ecosystems,ascertaining the potential benefits of data science in embedded digital ecosystems’ research. 2020 Conference Paper http://hdl.handle.net/20.500.11937/81900 https://creativecommons.org/licenses/by-nc/3.0/nz/ fulltext
spellingShingle Nimmagadda, Shastri
Namugenyi, Christine
Mani, Neel
Reiners, Torsten
Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title_full Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title_fullStr Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title_full_unstemmed Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title_short Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts
title_sort managing embedded digital ecosystems in pandemic big data contexts
url https://creativecommons.org/licenses/by-nc/3.0/nz/
http://hdl.handle.net/20.500.11937/81900