The rise of digital footprints has created a number of promises and expectations for the study of territorial dynamics, particularly those of tourist cities. These footprints would make the observation of visitors' spatial practices possible and make up for the lack of information on these practices at an urban scale. Thus, many studies use data from social networks to study the touristic space at different geographical scales. These studies provide several types of visualisations based on this data, thus making it possible to represent and show a supposedly new touristic space-time-from the heat map to the dashboard, the digital footprints are displayed as processed, aggregated, calculated and smoothed. All these transformations-resulting from algorithmic black boxes that do not allow a precise understanding of the methodologies (often complex and approximate)-are often not very transparent. Consequently, the technicality and opacity of this data make necessary the development of critical approaches that allow the deconstruction of these new mapping registers. Based on data collected on a widely used social network, Instagram, we wish to question digital footprints as a potential tool to observe tourist practices, by going back through the data genealogy, from the map to the footprint. Our approach consists of going back to the initial data and their associated metadata, in order to explore two fundamental dimensions, conditions prerequisite for more complex explorations: time and space. Therefore, we collected a corpus of metadata from photographs published on Instagram between 2016 and 2018 in Biarritz, France, which we analyse following these two axes. Through this exploratory study, we will demonstrate that this data, though very rich, presents a certain number of limits, whether in terms of access to the data itself or its spatiotemporal precision.
Abstract. Arabesque is an application for the exploration and geovisualisation of origin-destination flows (or spatial networks), developed within the framework of the Univ. Gustave Eiffel (ex. IFSTTAR)-funded research project geographic flow visualisation (gflowiz) geoflowiz, in collaboration with the CNRS. It allows both the exploration and the filtering of OD data and their representation, with a strong emphasis on geographic information layering and features' semiology. The key-objective is to propose an easy way to produce a modern cartography (a geovisualisation) of thematic flows (e.g. bilateral flow volume), at several geographic scales, even from your own datasets. The objective of this article is to position Arabesque in the range of geoweb applications for producing flow maps, by comparing its functionalities with those of similar web applications – Magrit, Kepler.gl, flowmap.blue – pointing out their respective advantages and limitations. The analysis of its functionalities is compared on the same flow dataset – MOBSCO, i.e. a dataset describing the school mobility of French pupils and students on a given year – for a practical and empirical “validation” of its contributions. We demonstrate that the configurations and appearances of these tools’ visual output depend largely on the culture of their developers, and on the use and audiences for which they have been developed.
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