Publication | Open Access
Co-designing Data Experiments
13
Citations
33
References
2020
Year
Unknown Venue
EngineeringData VisualizationOptimal Experimental DesignData-driven DevelopmentData-driven InnovationData InfrastructureCollaborative Data ManagementData SourcesData ScienceManagementData IntegrationCo-designing Data ExperimentsCollaborative Data ScienceData ManagementDesignInformation ManagementDomain ExpertsExperiment DesignData PracticeCollaborative Data AnalysisDifferent Data SourcesKnowledge ManagementData Modeling
Today, organizations have to deal with multiple heterogeneous data sources from different systems and platforms to maintain and develop their services. Therefore, there is a need for tools to support organizations to determine what data sources can advance and innovate their services. This paper reports on how we addressed this need by designing and implementing two design tools – the Data Sphere and the Data Experiment Template – to support domain experts’ exploration with different data sources which they selected themselves. We find that (1) domain experts’ exploration of data sources make the cross-organizational dependency of data and data work visible; (2) the value of co-design becomes evident to address this dependency; and by that, (3) the data became ‘design things’, that means data are object of design that at the same time create a space for members of the organization to together explore how to use data to innovate their services.
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