Characteristics of Citizen-contributed Geographic Information

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Current Internet applications have been increasingly incorporating citizen-contributed geographic information (CCGI) with much heterogeneous characteristics. Nevertheless, despite their differences, several terms are often being used interchangeably to define CCGI types, in the existing literature. As a result, the notion of CCGI has to be carefully specified, in order to avoid vagueness, and to facilitate the choice of a suitable CCGI dataset to be used for a given application. To address the terminological ambiguity in the description of CCGI types, we propose a typology of GI and a theoretical framework for the evaluation of GI in terms of data quality, number and type of contributors and cost of data collection per observation. We distinguish between CCGI explicitly collected for scientific or socially-oriented purposes. We review 27 of the main Internet-based CCGI platforms and we analyse their characteristics in terms of purpose of the data collection, use of quality assurance and quality control (QA/QC) mechanisms, thematic category, and geographic extents of the collected data. Based on the proposed typology and the analysis of the platforms, we conclude that CCGI differs in terms of data quality, number of contributors, data collection cost and the application of QA/QC mechanisms, depending on the purpose of the data collection

Characteristics of Citizen-contributed Geographic Information

Current Internet applications have been increasingly incorporating citizen-contributed geographic information (CCGI) with much heterogeneous characteristics. Nevertheless, despite their differences, several terms are often being used interchangeably to define CCGI types, in the existing literature. As a result, the notion of CCGI has to be carefully specified, in order to avoid vagueness, and to facilitate the choice of a suitable CCGI dataset to be used for a given application. To address the terminological ambiguity in the description of CCGI types, we propose a typology of GI and a theoretical framework for the evaluation of GI in terms of data quality, number and type of contributors and cost of data collection per observation. We distinguish between CCGI explicitly collected for scientific or socially-oriented purposes. We review 27 of the main Internet-based CCGI platforms and we analyse their characteristics in terms of purpose of the data collection, use of quality assurance and quality control (QA/QC) mechanisms, thematic category, and geographic extents of the collected data. Based on the proposed typology and the analysis of the platforms, we conclude that CCGI differs in terms of data quality, number of contributors, data collection cost and the application of QA/QC mechanisms, depending on the purpose of the data collection.JRC.H.6 - Digital Earth and Reference Dat

Social connections and remittance flows: an exploratory analysis of Facebook data

Remittances are a major source of finance for countries around the world and are increasingly important for sustainable development. However, the available data estimating international remittance flows is often criticised. This report makes a novel contribution to understanding the factors which influence the volume of bilateral remittance flows, and in doing so highlights a potential opportunity for the refinement of international remittance flow estimates. Specifically, the study uses innovative data from Facebook’s Social Connectedness Index to explain bilateral remittance flows. This data source is positively associated with remittance flows and the findings are robust and statistically significant. These findings have two key implications. Firstly, they show that, alongside data on migrant stocks, economic and geographic variables the connections between migrants and their countries and communities of origin make an important contribution to explaining bilateral remittance flows. Secondly, they illustrate how innovative data from non-traditional sources can provide new opportunities for analysing and estimating bilateral remittances.JRC.E.6 - Demography, Migration and Governanc

Anomaly Detection of Mobility Data with Applications to COVID-19 Situational Awareness

This work introduces a live anomaly detection system for high frequency and high-dimensional data collected at regional scale such as Origin Destination Matrices of mobile positioning data. To take into account different granularity in time and space of the data coming from different sources, the system is designed to be simple, yet robust to the data diversity, with the aim of detecting abrupt increase of mobility towards specific regions as well as sudden drops of movements. The methodology is designed to help policymakers or practitioners, and makes it possible to visualise anomalies as well as estimate the effect of COVID-19 related containment or lifting measures in terms of their impact on human mobility as well as spot potential new outbreaks related to large gatherings

Monitoring COVID-19-induced gender differences in teleworking rates using Mobile Network Data

The COVID-19 pandemic has created a sudden need for a wider uptake of home-based telework as means of sustaining the production. Generally, teleworking arrangements impacts directly worker's efficiency and motivation. The direction of this impact, however, depends on the balance between positive effects of teleworking (e.g. increased flexibility and autonomy) and its downsides (e.g. blurring boundaries between private and work life). Moreover, these effects of teleworking can be amplified in case of vulnerable groups of workers, such as women. The first step in understanding the implications of teleworking on women is to have timely information on the extent of teleworking by age and gender. In the absence of timely official statistics, in this paper we propose a method for nowcasting the teleworking trends by age and gender for 20 Italian regions using mobile network operators (MNO) data. The method is developed and validated using MNO data together with the Italian quarterly Labour Force Survey. Our results confirm that the MNO data have the potential to be used as a tool for monitoring gender and age differences in teleworking patterns. This tool becomes even more important today as it could support the adequate gender mainstreaming in the ``Next Generation EU'' recovery plan and help to manage related social impacts of COVID-19 through policymaking.Comment: added figure

Territorial differences in the spread of COVID-19 in European regions and US counties

This article explores the territorial differences in the onset and spread of COVID-19 and the excess mortality associated with the pandemic, across the European NUTS3 regions and US counties. Both in Europe and in the US, the pandemic arrived earlier and recorded higher Rt values in urban regions than in intermediate and rural ones. A similar gap is also found in the data on excess mortality. In the weeks during the first phase of the pandemic, urban regions in EU countries experienced excess mortality of up to 68pp more than rural ones. We show that, during the initial days of the pandemic, territorial differences in Rt by the degree of urbanisation can be largely explained by the level of internal, inbound and outbound mobility. The differences in the spread of COVID-19 by rural-urban typology and the role of mobility are less clear during the second wave. This could be linked to the fact that the infection is widespread across territories, to changes in mobility patterns during the summer period as well as to the different containment measures which reverse the causality between mobility and Rt

Migration Data using Social Media: a European Perspective

Migration is a top political priority for the European Union (EU). Data on international migrant stocks and flows are essential for effective migration management. In this report, we estimated the number of expatriates in 17 EU countries based on the number of Facebook Network users who are classified by Facebook as “expats”. To this end, we proposed a method for correcting the over- or under-representativeness of Facebook Network users compared to countries’ actual population. This method uses Facebook penetration rates by age group and gender in the country of previous residence and country of destination of a Facebook expat. The purpose of Facebook Network expat estimations is not to reproduce migration statistics, but rather to generate separate estimates of expatriates, since migration statistics and Facebook Network expats estimates do not measure the same quantities of interest. Estimates of social media application users who are classified as expats can be a timely, low-cost, and almost globally available source of information for estimating stocks of international migrants. Our methodology allowed for the timely capture of the increase of Venezuelan migrants in Spain. However, there are important methodological and data integrity issues with using social media data sources for studying migration-related phenomena. For example, our methodology led us to significantly overestimate the number of expats from Philippines in Spain and in Italy and there is no evidence that this overestimation may be valid. While research on the use of big data sources for migration is in its infancy, and the diffusion of internet technologies in less developed countries is still limited, the use of big data sources can unveil useful insights on quantitative and qualitative characteristics of migration.JRC.E.6 - Demography, Migration and Governanc