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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 2/2015

01-06-2015 | Technical Contribution

Technology Roadmap Development for Big Data Healthcare Applications

Authors: Sonja Zillner, Sabrina Neururer

Published in: KI - Künstliche Intelligenz | Issue 2/2015

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Abstract

Big data applications indicate a wide range of opportunities to improve the overall quality and efficiency of healthcare delivery. The highest impact of big data applications is expected when data from various healthcare areas, such as clinical, administrative, financial, or outcome data, can be integrated. However, as of today, the realization of big data healthcare applications aggregating various kinds of data sources is still lacking behind. In order to foster the implementation of comprehensive big data applications, a clear understanding of short-term and long-term goals of envisioned big data scenarios is needed to forecast which emerging big data technologies are needed at what point in time. The contribution of this paper is to introduce the development of a technology roadmap for big data technologies in the healthcare domain. Beside the description of user needs and the technologies needed in order to satisfy those needs, the technology roadmap provides a basis to forecast technology developments and, thus, guidance in planning and coordinating technology developments accordingly.
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Footnotes
2
Beside the healthcare sector, several other industrial sectors, such as Energy, Transport, Finance, Manufacturing, Retail and the Public Sector are addressed within the project but not focus of this publication.
 
3
Desired situation refers to the year 2020.
 
4
The concepts of ‘known unknowns’ and ‘unknown unknows’ were initially quoted by Donald Rumsfeld.
 
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Metadata
Title
Technology Roadmap Development for Big Data Healthcare Applications
Authors
Sonja Zillner
Sabrina Neururer
Publication date
01-06-2015
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2/2015
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-014-0335-y

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