Managing Embedded Digital Ecosystems in Pandemic Big Data Contexts

Abstract

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.