Managing Big Data in distributed environments in a critical research challenges which has driven the attention from the community. In this context, there are several issues to be faced-off, including (i) dealing with massive and heterogenous data, (ii) inconsistency problems, (iii) query optimization bottlenecks, and so forth. Clinical data represent a vibrant case of Big Data, due to both practical as well as methodologies challenges exposed by such data, also dictated by tight requirements of applications which manage them. Following these considerations, in this paper we present an architecture for the storage, exchange and use of health data for administrative and epidemiological purposes, that focuses on the patient, who in a safe and easy way can make use of their data for therapeutic and research purposes. This research is being conducted as part of the CCE Project, in order to experience a new kind of storage architecture and data exchange within the field of clinical oncology.

A framework for supporting the distributed management of big clinical data

Cuzzocrea Alfredo;
2014-01-01

Abstract

Managing Big Data in distributed environments in a critical research challenges which has driven the attention from the community. In this context, there are several issues to be faced-off, including (i) dealing with massive and heterogenous data, (ii) inconsistency problems, (iii) query optimization bottlenecks, and so forth. Clinical data represent a vibrant case of Big Data, due to both practical as well as methodologies challenges exposed by such data, also dictated by tight requirements of applications which manage them. Following these considerations, in this paper we present an architecture for the storage, exchange and use of health data for administrative and epidemiological purposes, that focuses on the patient, who in a safe and easy way can make use of their data for therapeutic and research purposes. This research is being conducted as part of the CCE Project, in order to experience a new kind of storage architecture and data exchange within the field of clinical oncology.
2014
9781631900471
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/312750
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