Blackboxing Data—Conceptualizing Data-Driven Exploration from a Business Perspective
Digitalization and data-driven exploration call for increasingly multi-modal management approaches. We outline what we perceive as a multi-decade conceptualization journey from a business perspective: Having started with modelling functions, data stores and dataflows, having moved towards business process modelling, having expanded to modelling of value creation and value appropriation, now also business conceptualizations for purpose-driven, informed decision-making are needed. We argue that conceptual data models inappropriately capture the essence of how business stakeholders analyze, design and manage data-driven exploration. To overcome this gap, we discuss the potential of various proposals from different fields to “black box” data exploration. In conclusion we outline a data blackboxing research agenda that includes ontology and taxonomy design, the derivation of appropriate analysis and modelling methods/techniques, case analysis and pattern discovery.
KeywordsMulti-model management Conceptual modelling Data-driven exploration
The author wants to acknowledge Michael Blaschkes contributions not only to earlier co-authored related work (Winter & Blaschke, 2018), but also to initial discussions and research on the topic of data blackboxing. Stephan Aier provided valuable feedback to an earlier version of this text.
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