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.
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Meigen, C., Dörpinghaus, J., Weil, V., Schaaf, S., Apke, A. (2022). Data and Knowledge Management. In: Dörpinghaus, J., Weil, V., Schaaf, S., Apke, A. (eds) Computational Life Sciences. Studies in Big Data, vol 112. Springer, Cham. https://doi.org/10.1007/978-3-031-08411-9_5
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DOI: https://doi.org/10.1007/978-3-031-08411-9_5
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