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The complexity of analytically reasoning to extract and identify useful knowledge from large masses of data requires that the design of visual analytics tools addresses challenges of facilitating human-data interaction (HDI). Designing data visualisation based on guidelines is fast and low-cost, but does not favour the engagement of people in the process. In this paper, we propose a design process to integrate design based on guidelines with participatory design practices. We investigate, and when necessary, adapt existing practices for each step of our design process. The process was evaluated on a design problem involving a visual analytics tool supporting decisions related to the production strategy in oil reservoirs with the participation of key stakeholders. The generated prototype was tested with adapted participatory evaluation practices. The obtained results indicate participants’ satisfaction with the design practices used and detected the fulfilment of users’ needs. The design process and the associated practices may serve as a basis for improving the HDI in other contexts.

Design Process for Human-Data Interaction: Combining Guidelines with Semio-participatory Techniques