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The dataset provided here is an output of the Track & Know project, shared with the scientific community. The dataset consists of mobility- and road network-related aggregates computed for each municipality in Tuscany (Italy), based on private cars GPS traces and the OpenStreetNetwork graph. The application that originated this dataset is the study of geographical transferability of mobility models, in order to understand under which conditions a model (e.g. to predict traffic) built in one area can be used in another one, or what kind of adjustment is needed. The dataset and the application mentioned above appeared in the following publication: Leonardo Longhi, Mirco Nanni. Car telematics big data analytics for insurance and innovative mobility services. In Journal of Ambient Intelligence and Humanized Computing (JAHC), p. 1-11, Springer, 2017. 10.1007/s12652-019-01632-4 The mobility indicators of the shared dataset have been inferred, as aggregation of geographical areas (10km x 10km, each corresponding to a municipality in Tuscany) of ca 107000 vehicles, from a proprietary data source.
Mobility, Insurance, Accident, Black box
Mobility, Insurance, Accident, Black box
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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