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Objective This paper proposes a methodology for using mobile telephone network coverage data from the Mobile Coverage (GenCat) platform for detecting spatial and temporal patterns in multiple scales and at different geographical granularity levels (administrative and Urban Atlas classes). The paper outlines a Responsive Geographical Information Systems ("Responsive Mobile Coverage (RMC)") of a large number of point data of mobile networks integrating summarization techniques and dynamic visual models. Methodology For that purpose, an integrated framework of Exploratory Data Analysis (EDA) and GIS Cloud Computing is described and implemented using open source tools such as Jupyter (Python), ArcGIS Online and the ESRI Web AppBuilder for ArcGIS. The methodology was tested with data of Barcelona in August 2015. Conclusions The RMC framework presents capabilities to integrate additional information from the Catalonian Big Data landscape, and therefore, improve the access to Open data for public sector, private companies, citizens and scientists. The developed methods have potential for the definition and analysis of the distribution of aggregation indicators in cities, monitoring the precision of mobile networks in different administrative and urban contexts, and enabling citizens to make sense of such data for improving their scientific knowledge, daily life and fostering collective decision making. Originality The paper demonstrates that RMC can be a very useful tool for responsive visualization and improving different decision-making processes in Barcelona. We suggest an approach to data science, where the complete workflow takes place inside a Big Data paradigm, to produce reproducible results, using the best practices in scientific research.

Responsive Geographical Information Systems for Spatio-Temporal Analysis of Mobile Networks in Barcelona