A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

The paper analyses the characteristics of Volunteer Geographic Information (VGI) and the need to assure and assess its quality for a possible use and re-use. Ontologies and soft ontologies are presented as means to support quality assurance and assessment of VGI by highlighting their limitations. A proposal of a possibilistic approach using fuzzy ontology is finally illustrated that allows to model both imprecision and vagueness of domain knowledge and epistemic uncertainty affecting observations. A case study example is illustrated.

Optimal location and sizing of small hybrid systems in micro-grid system using Volunteer Geographic Information

<p><strong>Optimal location and sizing of small hybrid systems in micro-grid system using Volunteer Geographic Information</strong></p><p> </p><p>This study presents an optimization model for the optimal location and sizing of small hybrid systems in simulated micro-grids. By using an optimization model - in combination with COSMO-REA2 weather data - various micro-grids local energy systems are simulated using the Calliope energy simulation model. The Calliope optimization and simulation model is feed with GIS-data from different Volunteered Geographic Information projects, including OpenStreetMap. These allows to automatically allocate specific demand profiles to diverse OpenStreetMap building categories. Moreover, based on the characteristics of the OpenStreetMap data, a set of possible distributed energy resources) including renewables and fossil fueled generators are defined for each building category. The optimization model is applied for a set of scenarios based on different electricity prices and technological characteristics. This allows to assess the impact and profitability of the different technological options on the micro-grid configuration. Moreover, in order to assess the impact of each of the scenarios on the current distribution infrastructure, the results of the simulations are included on an existing model of the low and middle voltage network for Lower Bavaria, Germany. Finally, to facilitate their dissemination, the results of the simulation are stored in a PostgreSQL database, before they are delivered by a RESTful Laravel Server and displayed in an Angular Web-Application.</p>

Free and Open Source Tools for Volunteer Geographic Information and Geo-Crowdsourcing

The availability of new mobile devices (tablets and smartphones) equipped with many sensors is changing or, better, enriching the way we monitor and sense the world that surrounds us. The internet has permeated completely not only our scientific and technological development, but also our life. Only some years ago, we used geospatial data and GIS software installed within our computers. Nowadays, data and operators are provided via the net by means of distributed and shared geo-services and a simple and powerless mobile device is enough to connect them. The possibility of interaction has become not only faster and more user friendly but also active, being individuals and communities free of adding, deleting, and changing contents in real time in the new GeoWeb2.0. This chapter explores GeoWeb2.0.

Free and Open Source Tools for Volunteer Geographic Information and Geo-Crowdsourcing

The availability of new mobile devices (tablets and smartphones) equipped with many sensors is changing or, better, enriching the way we monitor and sense the world that surrounds us. The internet has permeated completely not only our scientific and technological development, but also our life. Only some years ago, we used geospatial data and GIS software installed within our computers. Nowadays, data and operators are provided via the net by means of distributed and shared geo-services and a simple and powerless mobile device is enough to connect them. The possibility of interaction has become not only faster and more user friendly but also active, being individuals and communities free of adding, deleting, and changing contents in real time in the new GeoWeb2.0. This chapter explores GeoWeb2.0.

Estimating traffic disruption patterns with volunteer geographic information

Accurate understanding and forecasting of traffic conditions is a key contemporary problem for local policymakers. Road networks are increasingly congested, yet data on usage patterns is often scarce or expensive to obtain, meaning that informed policy decision-making is difficult. This paper explores the extent to which traffic disruption can be estimated from static features of the volunteer geographic information site OpenStreetMap [OSM]. Kernel Density Estimates of OSM features are used as predictors for a linear regression of counts of traffic incidents at 6,500 separate points within the Oxfordshire road traffic network. For highly granular points of just 10m2, it is shown that more than half of variation in traffic outcomes can be explained with these static features alone. Furthermore, use of OSM’s granular point of interest data improves considerably on more aggregate categories which are typically used in studies of transportation and land use. Although the estimations are by no means perfect, they offer a good baseline model considering the data is free to obtain and easy to process.

Free and Open Source Tools for Volunteer Geographic Information and Geo-Crowdsourcing

The availability of new mobile devices (tablets and smartphones) equipped with many sensors is changing or, better, enriching the way we monitor and sense the world that surrounds us. The internet has permeated completely not only our scientific and technological development, but also our life. Only some years ago, we used geospatial data and GIS software installed within our computers. Nowadays, data and operators are provided via the net by means of distributed and shared geo-services and a simple and powerless mobile device is enough to connect them. The possibility of interaction has become not only faster and more user friendly but also active, being individuals and communities free of adding, deleting, and changing contents in real time in the new GeoWeb2.0. This chapter explores GeoWeb2.0.

CLASSIFICATION OF TRAFFIC RELATED SHORT TEXTS TO ANALYSE ROAD PROBLEMS IN URBAN AREAS

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the <i>classification of traffic related short texts to analyze road problems in urban areas</i>, a VGI data analysis is done over a social media’s publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.