Tomáš Mildorf

Design and Evaluation of WebGL-Based Heat Map Visualization for Big Point Data

Depicting a large number of points on a map may lead to overplotting and to a visual clutter. One of the widely accepted visualization methods that provides a good overview of a spatial distribution of a large number of points is a heat map. Interactions for efficient data exploration, such as zooming, filtering or parameters’ adjustments, are highly demanding on the heat map construction. This is true especially in the case of big data. In this paper, we focus on a novel approach of estimating the kernel density and heat map visualization by utilizing a graphical processing unit. We designed a web-based JavaScript library dedicated to heat map rendering and user interactions through WebGL. The designed library enables to render a heat map as an overlay over a background map provided by a third party API (e.g. Open Layers) in the scope of milliseconds, even for data size exceeding one million points. In order to validate our approach, we designed a demo application visualizing a car accident dataset in the Great Britain. The described solution proves fast rendering times (below 100 ms) even for dataset up to 1.5 million points and outperforms mainstream systems such as the Google Maps API, Leaflet heat map plugin or ESRI’s ArcGIS online. Such performance enables interactive adjustments of the heat map parameters required by various domain experts. The described implementation is a part of the WebGLayer open source information visualization library.

Open Data Platform for Data Integration, Visualisation and Map Design

The current trend in the EU is to open access to public sector information which is provided either for free or for marginal cost, and reuse it in various applications. Information technologies enable people to access, process and analyse spatial data from various sources, help to design on-demand maps and provide information for decision makers. However, the provision of data varies across different authorities, and combining heterogeneous data is not an easy task. We present an Open Data Platform that enables people to integrate, harmonise and visualise spatial planning and other data. The platform connects to the approach of real cartography and aims to enable non-cartographers to correctly design maps and gain new information in a user-friendly way based on modern technologies and robust data storage. This chapter mainly tackles the issues of heterogeneous data integration, harmonisation and visualisation. Ongoing research aims to explore new methods of data reuse and cartographic visualisation, following the trends of modern cartography.

The Plan4business Approach to Transfer Open Data into Real Estate Businesses

Spatial planning data including urban, regional, spatial or zoning plans are not aggregated so far. Creating time series or comparative analyses on these data sets is not yet possible. The EU funded project Plan4business develops a service platform that can serve to users as a full catalogue of spatial planning data linked with other data sources such as statistics, OpenStreetMap, Urban Atlas and Corine Land Cover that are published as Open Data. The Plan4business platform will offer to clients not only the data itself in an integrated, harmonised and thus ready-to-use form, but also rich analysis and visualisation services via an API and an interactive web frontend. The users include mainly citizens, local authorities and real estate agencies. This paper introduces the problems of data integration and selected technical components of the Plan4business platform supporting data reuse and analysis.

The HABITATS Approach to Build the INSPIRE Infrastructure

Different initiatives focused on spatial data in Europe should not be isolated but closely connected. The portfolio of such initiatives is very extensive. On the one hand, it covers all European activities such as INSPIRE or GMES, on the other hand, there are products of modern approaches based on neogeography and Volunteered Geographic Information (e.g. OpenStreetMap). Data are published by various regional or local authorities, non-governmental organisations, public bodies, research projects as well as by different commercial subjects. The focus of the HABITATS project was to build an environment that enables to share and combine data in order to reach new data, information and knowledge. On the basis of different pilots, HABITATS defined and tested harmonisation rules for spatial environmental data and designed the concept of Reference Laboratory as a tool for testing the interoperability and supporting unification of outputs cross different pilots.

Plan4All GeoPortal: web of spatial data

Plan4All project contributes on the harmonization of spatial data and related metadata in order to make them available through Web across a linked data platform. A prototype of a Web search European spatial data portal is already available at http://www.plan4all.eu. The key aim is to provide a methodology and present best practices towards the standardization of spatial data according to the INSPIRE principles and provide results that would be a reference material for linking data and data specification from the spatial planning point of view. The results include methodology and implementation of multilingual search for data and common portrayal rules for content providers. These are critical services for sharing and understanding spatial data across Europe. Plan4All paradigm shows that a clear applicable methodology for harmonization of spatial data on all different topics of interest can be achieve efficiently. Plan4All shows that it is possible to build Pan European Web access, to link spatial data and to utilize multilingual metadata providing a roadmap for linked spatial data across and hopefully beyond Europe. The proposed demonstration based on Plan4All experience aims to show experience, best practices and methods to achieve data harmonization and provision of linked spatial data on the Web.

SDI4Apps Points of Interest Knowledge Base

The SDI4Apps project has collected a large number of points of interest (POIs). The Smart Points of Interest (SPOI) represents a seamless and open resource of POIs covering all the world. Its principal target has been to provide information for cycling as Linked data together with other data sets containing road network. But the current version can be used for any purposes related to tourism. The article presents the data model for POIs as a basis for harmonization of external data sources into this data model. The current version of the SPOI data set includes a harmonized combination of selected OpenStreetMap data, GeoNames.org, experimental geo-ontologies developed at the University of West Bohemia and local data. The data model follows the recommendations for RDF data sets, semantic data, and Linked Data as well as the data model published in Points of Interest Core. The SPOI knowledge base complies with the 5-star rating system of Linked Open Data. The data model re-uses several important, respected and standardized formats and vocabularies such as XML, XML Schema, RDF, RDFS, SKOS (Simple Knowledge Organization System), GeoSPARQL or FOAF (Friend of a Friend).