Selected Topics on Complex Systems Informatics: Editorial Introduction to Issue 23 of CSIMQ

Kurt Sandkuhl

Abstract


Complex systems and their analysis, construction, management or application are the motivation of all articles in this issue of CSIMQ. Different perspectives exist on what actually causes “complexity” in systems. In systems theory, a widely spread view is that complex systems have many components with emergent behavior, i.e. the large number and the dynamics of components are decisive. In business informatics, the complexity of information systems is attributed to their socio-technical nature, which acknowledges the interaction between the human actors and the information technology in an enterprise. Understanding the context of complex systems or their components is supported by modeling and is a key aspect of preparing organizational solutions. Models do not remove the complexity of the real world but help to understand it and to design and develop solutions. All articles in this issue are in some respect concerned with models or modeling. The articles also reflect recent trends in industry and society, such as digital transformation and applications of artificial intelligence, and show that these trends will not necessarily reduce complexity in systems but rather require the combination of proven approaches, such as modeling, and new methods for managing this complexity.

Keywords:

Business Intelligence (BI); Big Data; Spatial Analysis; Anomaly Detection; Enterprise Architecture; Data Gap Analysis; Adaptive Architecture; Artificial Neural Networks; Business IT Alignment; Data Analytics

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DOI: 10.7250/csimq.2020-23.00

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