Contribution to a book

DZNE-2023-00422

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Data and Knowledge Management

Meigen, C.Extern* ; Dörpinghaus, J.DZNE* ; Weil, V. ; Schaaf, S.DZNE* ; Apke, A.

2022
Springer International Publishing Cham
ISBN: 978-3-031-08411-9

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Please use a persistent id in citations: doi:10.1007/978-3-031-08411-9_5

Abstract: Data and Knowledge Management, sometimes also called Information Management, is a core topic of Data Engineering and Data Mining. It is also an interdisciplinary field, touching economics (how efficient and expensive is the solution?), psychology (does one use this solution in a way that was intended?) and, of course, informatics. This chapter offers a theoretical overview on Data and Knowledge Management and thus provides a theoretic foundation for the following parts of this book. Moreover, if you implement or plan a solution in the field of data mining or data engineering, carefully consider the information given here. In other words: Besides the theory, this chapter provides a technical blueprint.

Keyword(s): Engineering—Data processing (LCSH) ; Bioinformatics (LCSH) ; Big data (LCSH) ; Computational intelligence (LCSH)

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Contributing Institute(s):

1. Clinical Research Coordination (AG Klockgether)
2. GenomMathematik in der Neuroepidemiologie (AG Becker)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)
2. 354 - Disease Prevention and Healthy Aging (POF4-354) (POF4-354)

Appears in the scientific report 2022

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