Laatabi A. auteur aut IRD Becu N. auteur aut IRD Marilleau Nicolas auteur aut IRD Pignon-Mussaud C. auteur aut IRD Amalric M. auteur aut IRD Bertin X. auteur aut IRD Anselme B. auteur aut IRD Beck E. auteur aut IRD text journalArticle eng text/pdf reformatted digital access For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding model (LittoSIM) to new territories. From this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into ABMs specialized FRANCE 128 126 020 021 7 1 6 [19 + 2 p. h.t.] 2020 2332-2047 https://www.documentation.ird.fr/hor/fdi:010081709 2332-2047 [F B010081709] https://www.documentation.ird.fr/hor/fdi:010081709 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers21-03/010081709.pdf IRD - Base Horizon / Pleins textes 2021-03-19 2021-04-01 fdi:010081709 fre