Brief Background This codebook provides information on the EQI survey data, which is intended to provide scholars and policy makers with metrics about citizens' perceptions and experiences with governance in Europe. The survey has been thus far done in two rounds-2010 and 2013. The data file here provides the combined microdata for both years. The EQI survey data was originally funded by the EU Commission (REGIO) and published in a report by Charron, Lapuente and Rothstein (2010) and later by Charron, Dijkstra and Lapuente (2014) in Regional Studies. In 2013, the survey was redone ; this time funded by the EU Commission via ANTICORRP, a large collaborative research group of scholars across Europe 1. The survey provides unique data for researchers and policy makers in that it is mainly concerned with governance of public sector institutions at the sub-national level. Questions are posed to respondents about perceived and experience with corruption, impartiality of services and quality of public services in several public service sectors. As opposed to many other survey in Europe that allow crosscountry or regional comparisons, the EQI Sample and Method The survey, part of a European-wide anti-corruption research project, was conducted in both rounds by Efficience 3 (E3), a French market-research, survey company specializing in public opinion throughout Europe for researchers, politicians and advertising firms. E3 conducted the interviews

A wide range of measures are available to improve the safety of walking and cycling in American cities, both to reduce fatalities and injuries and to encourage walking and cycling.

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Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source, multi-temporal, and multi-scale earth observation data. In this paper, the latest developments in terms of processing big earth observation data for the purpose of improving the Global Human Settlement Layer (GHSL) data are presented. Two experiments with Sentinel-1 and Landsat data collections were run leveraging on the Joint Research Centre Earth Observation Data and Processing Platform. A comparative analysis of the results of built-up areas extraction from different remote sensing data and processing workflows shows how the information production supported by data-intensive computing infrastructure for optimization and multiple testing can improve the output information reliability and consistency within the GHSL scope. The paper presents the processing workflows and the results of the two main experiments, giving insights into the enhanced mapping capabilities gained by analyzing Sentinel-1 and Landsat data-sets, and the lessons learnt in terms of handling and processing big earth observation data.