Linking geosocial sensing with the socio-demographic fabric of smart cities

Technological advances have enabled new sources of geoinformation, such as geosocial media, and have supported the propagation of the concept of smart cities. This paper argues that a city cannot be smart without citizens in the loop, and that a geosocial sensor might be one component to achieve that. First, we need to better understand which facets of urban life could be detected by a geosocial sensor, and how to calibrate it. This requires replicable studies that foster longitudinal and comparative research. Consequently, this paper examines the relationship between geosocial media content and socio-demographic census data for a global city, London, at two administrative levels. It aims for a transparent study design to encourage replication, using Term Frequency—Inverse Document Frequency of keywords, rule-based and word-embedding sentiment analysis, and local cluster analysis. The findings of limited links between geosocial media content and socio-demographic characteristics support earlier critiques on the utility of geosocial media for smart city planning purposes. The paper concludes that passive listening to publicly available geosocial media, in contrast to pro-active engagement with citizens, seems of limited use to understand and improve urban quality of life

Modeling aggregated expertise of user contributions to assess the credibility of OpenStreetMap features + Erratum

The emergence of volunteered geographic information (VGI) during the past decade has fueled a wide range of research and applications. The assessment of VGI quality and fitness-of-use is still a challenge because of the non-standardized and crowdsourced data collection process, as well as the unknown skill and motivation of the contributors. However, the frequent approach of assessing VGI quality against external data sources using ISO quality standard measures is problematic because of a frequent lack of available external (reference) data, and because for certain types of features, VGI might be more up-to-date than the reference data. Therefore, a VGI-intrinsic measure of quality is highly desirable. This study proposes such an intrinsic measure of quality by developing the concept of aggregated expertise based on the characteristics of a feature's contributors. The article further operationalizes this concept and examines its feasibility through a case study using OpenStreetMap (OSM). The comparison of model OSM feature quality with information from a field survey demonstrates the successful implementation of this novel approach

Reproducible Research is like riding a bike

Reproducibility is a fundamental pillar in science but it has recently been described as hard and challenging to achieve, as stated in numerous editorials and papers, some of which alert on a “reproducibility crisis”. In this article we outline 1/ the approach taken to put Reproducible Research (RR) in the agenda of the GIScience community, 2/ first actions and initial lessons learned towards the discussion and adoption of RR principles and practices in the workflows and habits of researchers, and finally, we present 3/ our short-term strategy (two years) and specific actions to achieve the main goal of making RR an integral part of scientific workflows of the GIScience community