Selected for CIST 2019-2023 quinquennial contract, this exploratory project is planned to last 2 years.
Beyond their descriptive and analytical functions, maps contribute to the formation of mental representations of space. This is particularly true of maps of world space, whose eminently political nature of cartographic projections and their role in representations have been widely demonstrated (Battersby & Montello, 2009). In previous works, we have also shown the role of the state mesh in representations of a world with compartmentalised phenomena (Vandermotten, 2003; Didelon-Loiseau 2013). Yet many simple phenomena, such as population densities or the distribution of wealth, have structures that are not, or not only, influenced by national borders. Representing them by breaking out of the national mesh makes it possible to show other structures in the world (other gradients, other discontinuities...) than those to which we are accustomed. Moreover, many "state" cartographic representations of the world are unsuitable and insufficient to grasp the richness of the phenomena linked to globalisation, which draw a much finer geography than that summarised by the state mesh. This cartography of a world 'without borders' presents important social issues since it would make it possible to go beyond the representations of a world organised exclusively by the territories of states to encourage the emergence of a global level of thought and representation. However, mapping these phenomena on a global scale also raises considerable theoretical and methodological issues in terms of representation of territorial information. The main challenges concern the collection and harmonisation of data, the choice of the most relevant representation meshes, the construction of map backgrounds and the analysis of data, which the interdisciplinary team we have set up (geomatics, geography, demography) will be able to carry out.
This project proposes to continue the theoretical and methodological reflection on the construction of a world map on a sub-national scale that we have begun to carry out (Didelon-Loiseau et al., 2017) beyond what has already been done in an exploratory perspective and which already constitutes an important methodological innovation in the representation and quantitative analysis of territorial information on a global scale. We will focus our reflection on ways of making this database available and, above all, useful to the greatest number of people interested in the mapping of demographic and social phenomena on a global scale, and in particular beyond researchers interested in the territorial structuring of social phenomena, to actors having to conduct reflections on this scale or to those interested in the structuring of cross-border phenomena. Our main objective is therefore to enable the integration of this database as a "project file" in the free online mapping application developed from 2017 at RIATE: Magrit. In addition to classic cartographic representation modes (proportional maps, choropleth maps), Magrit also offers more advanced representation modes (squares, smoothing, territorial discontinuities) which allow us to see territorial phenomena in a different way. In addition, Magrit offers a library of map collections (world, Europe, France) which constitute resources for users. In continuous development, this free application is open to contributions.
3 main concrete methodological objectives
- Finalise the database, configuring it in a manageable format, completing the metadata and stabilising the map backgrounds. The question of the database storage format will also arise.
- Collectively publish a data paper on the methodology of database construction and data representation.
- Integrate the database and the background map as a "project file" in Magrit. This involves the pre-production of a certain number of maps.
- These methodological productions will, of course, be complemented by papers (articles or conferences) of a more theoretical or thematic nature on the representation and analysis of sub-national data on a global scale.
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