Agent-based models thrive in part due to the consideration of diverse information sources (e.g., theory and data) in the modelling process. However, practices for integrating data in agent-based models are diverse and depend on the disciplinary background that informs the nature of the collected data. A large number of models thus rely on qualitative data, in addition or as an alternative to quantitative input. As part of the ESSA Special Interest Group Qual2Rule, we aim to develop a better understanding of the current approaches for the inclusion of *qualitative data* undertaken within the community. We thus invite the agent-based modelling community (understood here in a loose sense) to offer some insight into their practices as part of an anonymous survey linked below, the results of which we are planning to discuss as part of this year’s Social Simulation Conference (SSC 2020) in Milan (http://ssc2020.behavelab.org/).

Note that the used survey tool is GDPR compliant, but may occasionally show some ads above or below the questionnaire items. We apologise for this inconvenience in advance.

Link to the survey: https://eSurv.org?u=qual2abm

In case of any questions or comments regarding this survey, please contact, Christopher Frantz (christopher.frantz@ntnu.no).