Explainability of Industrial Decision Support System using Digital Design Thinking with Scene2-Model

To ensure the acceptance of decisions made in complex cyberphysical environments, orchestrated between human and machine actors, not only the developers need to understand how a decision is reached, but also the decisionmakers and stakeholders affected by the decisions. To this end this contribution discusses how highlevel visualisations can be derived to support the explanation of decisions using OMiLAB’s digital design thinking approach in an inverse manner.These visualisations will not be mere pictures, but diagrammatic models, containing additional information, which is understandable to machines, allowing to process them during an enrichment phase and interactively explain their involvement and impact to the users. The representation as conceptual models enables a) the cognitive perception by human actors, b) the machine interpretation for semantic lifting (focusing on elevating understandability) and c) further design iterations to adapt the system to become adequate and effective from a design but also operational perspective.