Mastering Data-Intensive Collaboration and Decision Making: The Dicode Project

• Published in: Knowledge Discovery, Knowledge Engineering and Knowledge Management Vol. 454; pp. 21 - 36
• Main Author: Karacapilidis, Nikos
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2015; Springer Berlin Heidelberg
• Series: Communications in Computer and Information Science
• Subjects: Artificial intelligence; Consortium Partner; Data mining; Decision Making Setting; Global Knowledge Economy; Information Overload; Information retrieval; Opinion Mining
• ISBN: 3662465485; 9783662465486
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-662-46549-3_2

Many collaboration and decision making settings are nowadays associated with huge, ever-increasing amounts of multiple types of data, which often have a low signal-to-noise ratio for addressing the problem at hand. The Dicode project aimed at facilitating and augmenting collaboration and decision making in such data-intensive and cognitively-complex settings. To do so, whenever appropriate, it built on prominent high-performance computing paradigms and proper data processing technologies to meaningfully search, analyze and aggregate data existing in diverse, extremely large, and rapidly evolving sources. At the same time, particular emphasis was given to the deepening of our insights about the proper exploitation of big data, as well as to collaboration and sense making support issues. This chapter reports on the overall context of the Dicode project, its scientific and technical objectives, the exploitation of its results and its potential impact.