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Authors: Nikos Karacapilidis 1 ; Georgia Tsiliki 2 and Manolis Tzagarakis 1

Affiliations: 1 Computer Technology Institute and Press "Diophantus" and University of Patras, Greece ; 2 Biomedical Research Foundation and Academy of Athens, Greece

Keyword(s): Big Data, Data Mining, Decision Support Systems, Collaboration, Knowledge Visualization, Data and Information Quality, Situational Awareness, Biomedical Data.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Big Data ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Management and Quality ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Information Quality ; Knowledge-Based Systems ; Modeling and Managing Large Data Systems ; Symbolic Systems

Abstract: Biomedical researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, this paper reports on the development and practical use of an innovative web-based collaboration support service in a biomedical research context. The proposed service builds on the synergy between machine and human intelligence to facilitate and augment the underlying knowledge management, data mining and decision making processes. Evaluation results indicate that the service enables stakeholders to make more informed decisions, by displaying the aggregated information according to their needs.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Karacapilidis, N.; Tsiliki, G. and Tzagarakis, M. (2013). Enhancing Collaboration in Big Biomedical Data Settings - Knowledge Visualization, Data Mining and Decision Making Issues. In Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA; ISBN 978-989-8565-67-9; ISSN 2184-285X, SciTePress, pages 23-31. DOI: 10.5220/0004492100230031

@conference{data13,
author={Nikos Karacapilidis. and Georgia Tsiliki. and Manolis Tzagarakis.},
title={Enhancing Collaboration in Big Biomedical Data Settings - Knowledge Visualization, Data Mining and Decision Making Issues},
booktitle={Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA},
year={2013},
pages={23-31},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004492100230031},
isbn={978-989-8565-67-9},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA
TI - Enhancing Collaboration in Big Biomedical Data Settings - Knowledge Visualization, Data Mining and Decision Making Issues
SN - 978-989-8565-67-9
IS - 2184-285X
AU - Karacapilidis, N.
AU - Tsiliki, G.
AU - Tzagarakis, M.
PY - 2013
SP - 23
EP - 31
DO - 10.5220/0004492100230031
PB - SciTePress