Choosing the best Visualization Approaches
User-friendly and efficient visualization of spatio-temporal data available via the mCLOUD
The Federal Ministry of Transport and Digital Infrastructure (BMVI) initiated the mCLOUD as a common open data discovery portal. This portal should improve the discoverability of their open data and those of its related projects and agencies.
In order to facilitate the efficient and user-friendly exploration of available data sets, it is essential to visualize the data as quickly and easily as possible. Fast and informative visualization of open data from the mCLOUD remains difficult, especially for spatiotemporal data. Usually this data must be downloaded and converted into common data formats before visual exploration is possible.
mVIZ conducts a preliminary study, in which a methodology is developed to support the selection and creation of user-friendly visualizations for data discoverable via the mCLOUD. A resulting guideline will describe the methodology and serve as a basis for the conception, extension or improvement of visualization tools or for their further development and integration into open data portals.
The project focuses in particular on the
- creation of an inventory of open spatiotemporal data in mCLOUD as well as an overview of available visualization and analysis tools
- development of a methodology for selecting appropriate visualizations for the spatio-temporal data
- development of a demonstrator for supporting the visualization of selected mCLOUD data.
The design and implementation of the demonstrator application is 52°North’s main contribution. It uses work from existing tools, such as the Helgoland Sensor Web Client.
52°North also supports the analysis of user requirements, available data sets, and appropriate data visualization approaches. We contribute to the evaluation of approaches for the interoperable integration of open spatio-temporal data sources and provide feedback on design rules for data visualization.
During 2019, 52°North mainly contributed to the analysis of requirements and the matching of available data sets to visualization methods. The demonstrator design was developed based on the outcomes of these activities. The implementation of this demo application will run until early 2020.