Mastering Data-Intensive Collaboration and Decision Making

Research and practical applications in the Dicode project

  • Nikos Karacapilidis

Part of the Studies in Big Data book series (SBD, volume 5)

Table of contents

  1. Front Matter
    Pages i-x
  2. Nikos Karacapilidis
    Pages 1-15
  3. Spyros Christodoulou, Nikos Karacapilidis, Manolis Tzagarakis, Vania Dimitrova, Guillermo de la Calle
    Pages 17-48
  4. Lydia Lau, Fan Yang-Turner, Nikos Karacapilidis
    Pages 49-70
  5. Dhavalkumar Thakker, Vania Dimitrova, Lydia Lau, Fan Yang-Turner, Dimoklis Despotakis
    Pages 71-87
  6. Natalja Friesen, Max Jakob, Jörg Kindermann, Doris Maassen, Axel Poigné, Stefan Rüping et al.
    Pages 89-118
  7. Manolis Tzagarakis, Nikos Karacapilidis, Spyros Christodoulou, Fan Yang-Turner, Lydia Lau
    Pages 119-139
  8. Guillermo de la Calle, Eduardo Alonso-Martínez, Martha Rojas-Vera, Miguel García-Remesal
    Pages 141-164
  9. Georgia Tsiliki, Sophia Kossida
    Pages 165-180
  10. Natalja Friesen, Jörg Kindermann, Doris Maassen, Stefan Rüping
    Pages 201-212
  11. Spyros Christodoulou, Manolis Tzagarakis, Nikos Karacapilidis, Fan Yang-Turner, Lydia Lau, Vania Dimitrova
    Pages 213-226

About this book


This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large, and rapidly evolving sources. The Dicode approach and services are fully explained, and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative “workbench” incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.


Cognitive Complexity Collaborative Decision Making Data Intensiveness Data Mining Analytics Data-Intensive Collaboration Dicode Project Knowledge Management Opinion Mining

Editors and affiliations

  • Nikos Karacapilidis
    • 1
  1. 1.University of Patras and Computer Technology Institute & Press "Diophantus"Rio PatrasGreece

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-02611-4
  • Online ISBN 978-3-319-02612-1
  • Series Print ISSN 2197-6503
  • Series Online ISSN 2197-6511
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences