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Communication Dans Un Congrès Année : 2016

Representation and Visualization of Imperfect Geohistorical Data About Natural Risks: A Qualitative Classification and Its Experimental Assessment

Résumé

Imperfections, often called ‘uncertainties’, exist in almost every spatio-temporal dataset, especially in historical data. They are of different types (unreliability, inaccuracy…) and concern every data dimension (space, time and theme). Based on previous work, this article proposes a synthesis qualitative classification of imperfection types. This classification has been assessed with domain experts (hydrologists, geophysicians and GIScientists working in a railway company) during an experiment, that gave positive results towards the use of this classification. Participants were also asked to evaluate the seriousness of each imperfection type in an analysis context. This evaluation has allowed to associate a quantitative index to each imperfection type and to visualize a quantity of imperfection attached to each spatial object in a map.
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Dates et versions

hal-01383634 , version 1 (19-10-2016)

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Cécile Saint-Marc, Marlène Villanova-Oliver, Paule-Annick Davoine, Cicely Pams Capoccioni, Dorine Chenier. Representation and Visualization of Imperfect Geohistorical Data About Natural Risks: A Qualitative Classification and Its Experimental Assessment. 19th AGILE Conference on Geographic Information Science, Jun 2016, Helsinki, Finland. ⟨10.1007/978-3-319-33783-8_14⟩. ⟨hal-01383634⟩
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