Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

The term Semantic Trajectories of Moving Objects (STMO) corresponds to a sequence of spatial-temporal points with associated semantic information (for example, annotations about locations visited by the user or types of transportation used). However, the growth of Big Data generated by users, such as data produced by social networks or collected by an electronic equipment with embedded sensors, causes the STMO to require services and standards for enabling data documentation and ensuring the quality of STMOs. Spatial Data Infrastructures (SDI), on the other hand, provide a shared interoperable and integrated environment for data documentation. The main challenge is how to lead traditional SDIs to evolve to an STMO document due to the lack of specific metadata standards and services for semantic annotation. This paper presents a new concept of SDI for STMO, named SDI4Trajectory, which supports the documentation of different types of STMO—holistic trajectories, for example. The SDI4Trajectory allows us to propose semi-automatic and manual semantic enrichment processes, which are efficient in supporting semantic annotations and STMO documentation as well. These processes are hardly found in traditional SDIs and have been developed through Web and semantic micro-services. To validate the SDI4Trajectory, we used a dataset collected by voluntary users through the MyTracks application for the following purposes: (i) comparing the semi-automatic and manual semantic enrichment processes in the SDI4Trajectory; (ii) investigating the viability of the documentation processes carried out by the SDI4Trajectory, which was able to document all the collected trajectories.

Geodesign as a support for proposing actions to fulfil the Sustainable Development Goals

This paper discusses the state of the art in Geodesign, as a result from the evolution in the use of geospatial data for shared and co-creative planning. The evolution of Geographic Information Systems (GIS) led to significant advances in geovisualization, the use of cartographic data via the Internet and the construction of SDIs (Spatial Data Infrastructures). These advances fostered the emergence of Geodesign as one of the foundations for territorial planning. The text will also introduce a Brazilian Geodesign platform, GISColab, developed according to the standards set by the Open Geospatial Consortium (OGC). The platform introduces layer creation resources via WPS (Web Processing Service), as well as tools for measuring the performance of participatory planning workshops, presently focusing on the UN’s Sustainable Development Goals (SDGs). We introduce case studies in which SDGs were explored in different ways: in post-workshop analyses conducted by coordinators and participants, as well as its application as a supportive tool for decision-making during the workshop, via WPS. Finally, we also discuss the inclusion of SDGs to raise awareness of its key themes and support opinion building, resulting in transformative learning experiences.

Interoperability at the core strategic in the Spatial Data Infrastructure of the Service Aerophotogrammetric of the Air Force of Chile

The Aerophotogrammetric Service (SAF) of the Chilean Air Force works permanently on the implementation of new methodologies and lines of research, fostering innovation in the field of earth sciences, remote sensing and geospatial information management. The above, with the aim of being at the technical and technological forefront in the country. Proof of this is the implementation of the SAF's Spatial Data Infrastructures, which has as one of its strategic axes the interoperability of geographic information, as it is considered a key factor in the correct exploitation of data, its access, availability and its potential use in decision making.

Knowledge Discovery Web Service for Spatial Data Infrastructures

The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge Discovery Web Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.