Background: In Europe, a lot of data portals are emerging on the local, national or interregional levels. These portals have a common objective to share data and information to its citizens and businesses, and to make information more accessible. However, studies showed that people are still facing difficulties in finding and reusing public sector information. To facilitate data reuse, the information should be available in a machine-readable format and agreed metadata standard, so that interoperability and discoverability could be enhanced. Methods: This article focuses on the interoperability and harmonization of spatial and non-spatial data in the transport field. Both the open data and geospatial world have stable standards (such as DCAT and INSPIRE), and the GeoDCAT-AP is the first attempt in combining the two worlds. Through a case study approach, this article aims to provide insights in the implementation of this new standard and other interoperability cases in transport, such as the Data Tank data management system and a harmonized model for road network data.
Big data have also become a big challenge for cartographers, as the majority of big data may be localized. The use of visual analytics tools, as well as comprising interactive maps, stimulates inter-disciplinary actors to explore new ideas and decision-making methods. This paper deals with the evaluation of three map-based visual analytics tools by means of the eye-tracking method. The conceptual part of the paper begins with an analysis of the state-of-the-art and ends with the design of proof-of-concept experiments. The verification part consists of the design, composition, and realization of the conducted eye-tracking experiment, in which three map-based visual analytics tools were tested in terms of user-friendliness. A set of recommendations on GUI (graphical user interface) design and interactive functionality for map makers is formulated on the basis of the discovered errors and shortcomings in the assessed stimuli. The results of the verification were used as inputs for improving the three tested map-based visual analytics tools and might serve as a best practice for map-based visual analytics tools in general, as well as for improving the policy making cycle as elaborated by the European project PoliVisu (Policy Development based on Advanced Geospatial Data Analytics and Visualization).
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