On a meaningful exploitation of machine and human reasoning to tackle data-intensive decision making

Authors:
Nikos Karacapilidis;Manolis Tzagarakis;Spyros Christodoulou
Affiliations:
Computer Technology Institute and Press "Diophantus", University of Patras, Rio Patras, Greece;Computer Technology Institute and Press "Diophantus", University of Patras, Rio Patras, Greece;Computer Technology Institute and Press "Diophantus", University of Patras, Rio Patras, Greece
Venue:
Intelligent Decision Technologies
Year:
2013

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Abstract

This paper deals with the "data deluge" issue in contemporary decision making settings; specifically, it reports on the development of an innovative platform that incorporates and orchestrates a set of interoperable Web services to facilitate and augment collaboration and decision making in data-intensive and cognitively-complex settings. The proposed approach exploits and builds on the most prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze and aggregate data existing in diverse, extremely large and rapidly evolving sources. At the same time, it remedies the shortcomings of current "big data" analytics technology and provides the appropriate ways to nurture and capture the human intelligence in order to extract the necessary insights. It can thus reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.