The Data Collaboration Canvas: A Visual Framework for Systematically Identifying and Evaluating Organizational Data Collaboration Opportunities

Tim Geppert (), Alice Dal Fuoco (), Ninja Leikert-Boehm (), Stefan Deml (), David Sturzenegger () and Nico Ebert ()
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Tim Geppert: ZHAW Zurich University of Applied Sciences
Alice Dal Fuoco: PostFinance
Ninja Leikert-Boehm: ZHAW Zurich University of Applied Sciences
Stefan Deml: dq Technologies AG
David Sturzenegger: dq Technologies AG
Nico Ebert: ZHAW Zurich University of Applied Sciences

A chapter in Solutions and Technologies for Responsible Digitalization, 2025, pp 49-64 from Springer

Abstract: Abstract For organizations, the use of Big Data and data analytics provides the opportunity to gain competitive advantages and foster innovation. In most of these data-analytics initiatives, it is clear that data from external stakeholders could enrich the internal data assets and lead to enhanced outcomes. Currently, no framework is available that systematically guides practitioners in identifying and evaluating suitable inter-organizational data collaborations. This paper closes the gap by following an action design research approach to develop the Data Collaboration Canvas (DCC). The DCC was rigorously evaluated by practitioners from Swiss organizations in six different industries, instantiated in four workshops, and used to guide innovative data collaboration projects. This artifact gives practitioners a guideline for identifying data collaboration opportunities and an insight into the main factors that must be addressed before further pursuing a collaborative partnership.

Keywords: Data sharing; Data collaboration; DSR; Canvas (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-80122-8_4

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