Visualizing the Data City

Abstract

ResumenEl aumento de la demanda de movilidad en las ciudades ha conllevado una dinámica poco sostenible tanto a nivel social como ambiental. Para promover actuaciones hacía una movilidad sostenible es necesario el uso de fuentes de información dinámicas, con un alto detalle espacial y temporal (y de bajo coste) que permitan realizar diagnósticos eficientes de la situación de movilidad en nuestras ciudades. Las Tecnologías de Información y Comunicación y el Big Data aparecen como nuevas fuentes interactivas que responden a estas necesidades. En este artículo se realiza una revisión del estado del arte en el uso de estas nuevas fuentes de datos para el análisis de la movilidad urbana, contrastando su utilidad respecto a las fuentes tradicionales, clasificán-dolas, presentando las temáticas de investigación que ofrecen, y abordando los desafíos de cara al futuro.Palabras clave: movilidad, Smart Cities, TIC, redes sociales, Big Data. Abstract New sources and challenges for urban mobility studiesIncrement of mobility demand in cities has carried socially and environmentally an unsustainable dynamic. For a sustainable planning, dynamic, high spatial and temporal resolution, and low cost sources are needed. Information and Communication Technologies appear as new interactive sources able to meet these needs. In this article, a state of the art in these new data sources use for urban mobility analysis is implemented. These new technologies are contrasted with traditional sources, are classified, new investigation topics are presented, and future challenges are addressed.

Dynamic Accessibility using Big Data: The Role of the Changing Conditions of Network Congestion and Destination Attractiveness

“…Maps of tweet density can be obtained according to the age, gender and ethnic group of the tweeter, if this information can be inferred from the user identifier (Longley et al 2015). One approach to the analysis of the daily changes in the population distribution in the city is to map the spatial distribution of the tweets according to the time of day (Ciuccarelli et al 2014). In addition to the official statistics that show the population's place of residence, the spatialtemporal analysis of tweets is now making it possible to move beyond night-time geographies of residence to see how they compare with daytime activity patterns (Longley et al 2015).…”

Examining three roles of urban “portals” in their relationship with “places” using social media photographs

“…Since the early 2000s, the rapid development of smartphones and social networks has made tremendous amounts of people-generated image data available and thus facilitated the study of geographical, behavioral and socio-cultural patterns of people in urban environments (Hochman and Manovich, 2013;Ciuccarelli, Lupi and Simeone, 2014). People are increasingly sharing photographs of everyday lives on social media platforms, and thus they can contribute millions or even billions of data files to researchers' efforts in increasing sample size and in turn reducing selection bias.…”

Mapping Urban Practices Through Mobile Phone Data

“…It is necessary to present urban spaces through visual approaches that are able to capture their flows in the form of static or dynamic images (Ciuccarelli et al 2014).…”