Relating the spatial component and users interests to improve applications based on questions, petitions and participatory processes

Nowadays, participatory processes attending the need for real democracy and transparency in governments and collectives are more needed than ever. Immediate participation through channels like social networks enable people to give their opinion and become pro-active citizens, seeking applications to interact with each other. The application described in this dissertation is a hybrid channel of communication of questions, petitions and participatory processes based on Public Participation Geographic Information System (PPGIS), Participation Geographic Information System (PGIS) and ‘soft’ (subjective data) Geographic Information System (SoftGIS) methodologies. To achieve a new approach to an application, its entire design is focused on the spatial component related with user interests. The spatial component is treated as main feature of the system to develop all others depending on it, enabling new features never seen before in social actions (questions, petitions and participatory processes). Results prove that it is possible to develop a working application mainly using open source software, with the possibility of spatial and subject filtering, visualizing and free download of actions within application. The resulting application empowers society by releasing soft data and defines a new breaking approach, unseen so far.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Information provision improvement with a geofencing event-bases system

Nowadays there is a big percentage of the population, specially young users, which are smartphone users and there is a lot of information to be provided within the applications, information provision should be done carefully and should be accurate, otherwise an overload of information will be produced, and the user will discard the app which is providing the information. Mobile devices are becoming smarter and provide many ways to filter information. However, there are alternatives to improve information provision from the side of the application. Some examples are, taking into account the local time, considering the battery level before doing an action and checking the user location to send personalized information attached to that location. SmartCampus and SmartCities are becoming a reality and they have more and more data integrated every day. With all this amount of data it is crucial to decide when and where is the user going to receive a notification with new information. Geofencing is a technique which allows applications to deliver information in a more useful way, in the right time and in the right place. It consists of geofences, physical regions delimited by boundaries, and devices that are eligible to receive the information assigned to the geofence. When devices cross one of these geofences an alert is pushed to the mobile device with the information.