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Geovisto: a Toolkit for Generic Geospatial Data Visualization

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Geovisto: a Toolkit for Generic Geospatial Data Visualization Geovisto: A Toolkit for Generic Geospatial Data Visualization Jirˇ´ı Hynek1 a, Jakub Kachl´ık1 b and V´ıt Rusnˇak´ 2 c 1Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic 2Institute of Computer Science, Masaryk University, Brno, Czech Republic Keywords: Geospatial Data, Geovisualizations, Visual Authoring Tools. Abstract: Today’s requirements for visualization of geospatial data are continually rising. Visualization authoring tools provide only limited support for this purpose. The ability to create geovisualizations by non-programmers is often reliant on template editing or visualization authoring tools. However, these tools are often limited either in configuring visual parameters or interaction capabilities. In our work, we identify the main limitations of current tools. Then, we propose design requirements and describe the implementation of Geovisto—a toolkit combining capabilities of the React, Leaflet, and D3.js frameworks in order to provide tools for processing generic geospatial data and creating multilayered reusable map widgets. We demonstrate our approach on two usage scenarios from conceptually different application areas (DDoS attacks from a network monitoring system and COVID-19 pandemics open data). Finally, we discuss the pros and cons of our approach and outline our future work. 1 INTRODUCTION scuring data perspectives essential for the users (Deg- belo and Kauppinen, 2018). Many people worldwide use Google Maps or GPS With the growing popularity of the open data navigation applications like Waze, almost daily. concept, various geospatial data have become avail- Working with maps and interactive map visualiza- able to the general public. Nevertheless, creat- tions have become ubiquitous nowadays. They have ing meaningful geovisualizations, especially the in- many forms and usage scenarios, ranging from sim- teractive ones, predominantly requires programming ple choropleths used in newspaper articles to spe- skills. In the last decade, we can observe growing ef- cialized analytical applications for disaster manage- forts toward developing visualization authoring sys- ment (Huang et al., 2015) or ornitology (Xavier and tems enabling creation such interactive visualizations Dodge, 2014). These so-called geovisualizations for non-programmers (Grammel et al., 2013; Mei work with the geospatial data, which combines lo- et al., 2018). The shortcoming of these tools is that cation information, descriptive attributes (numerical they focus mainly on 2D charts, and there are only or textual), and optional temporal information (times- a few which target the geovisualizations. Moreover, tamp, duration). The geovisualizations has many they offer only limited capabilities in terms of input forms ranging from point markers placed on the car- data or support for multi-layer interaction. We real- tographic maps through visualizing connections be- ized that it would be useful to provide the users with a tween them to heatmaps or choropleths. The interac- tool that would visualize generic geospatial data, sup- tive geovisualizations offer the ability to display data port users in authoring their use cases, and let users in multiple layers and enable users to explore them analyze their data through a user-friendly interface. at different detail levels through zooming and pan- In our work, we address the area of geovisual- ning. The layers might be shown at once, enabling ization authoring tools and contribute to the research the reasoning and supporting analytical tasks. How- body with: a) the identification of limitations and ever, identifying the proper visualization method for shortcomings of existing tools, b) the prototype im- geospatial data is often tricky, which might lead to ob- plementation of Geovisto—a novel geovisualization authoring toolkit, and c) its demonstration via two us- a https://orcid.org/0000-0002-7292-6094 age scenarios. b https://orcid.org/0000-0002-0621-8778 c https://orcid.org/0000-0003-1493-2194 101 Hynek, J., Kachlík, J. and Rusnák,ˇ V. Geovisto: A Toolkit for Generic Geospatial Data Visualization. DOI: 10.5220/0010260401010111 In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP, pages 101-111 ISBN: 978-989-758-488-6 Copyright c 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved IVAPP 2021 - 12th International Conference on Information Visualization Theory and Applications The paper is structured as follows. Section 2 data, e.g., when the glyph symbol is replaced by overviews the related work and summarizes the short- small 2D charts (e.g., pie/donut/bar charts). When comings of current approaches of geovisualization the dataset contains information, not for single loca- authoring tools. Section 3 presents the design require- tions but the whole regions, choropleth maps (or filled ments and propose the solution. Section 4 shows the maps) are the best option. The color fill of the re- real prototype of the solution and Section 5 demon- gion represents value (1 c)). Another type of spatial strates its applicability on two usage scenarios. Fi- visualization is heatmaps (or density maps) that are nally, Section 6 discusses the advantages, disadvan- common, e.g., from weather maps showing the mea- tages and outlines future research directions, and Sec- sured temperature or precipitation (1 f)). A particu- tion 7 summarizes the paper. lar category is geovisualizations showing routes and paths. Well-known from navigations, the basic path maps show direction between two points. However, in the case of flight monitoring websites or computer 2 RELATED WORK network visualizations, we can naturally extend the point-to-point to multipoint connections, also known Listing all geovisualization types is far beyond the as spider maps (1 d)). Finally, by adding the tempo- scope of this paper. Thus, we first introduce only ral dimension, we can visualize flow maps, enabling the most common two-dimensional ones. Next, we traffic visualization on the edges (1 e)). present the visualization authoring methods with a particular focus on authoring tools and their limita- tions. 2.2 Geovisualization Authoring Most of the web mapping applications available Approaches to the general public (e.g., Google Maps, Bing Maps, Open Street Maps) contain only the basic features We can distinguish three general approaches for au- such as route planning or adding own point mark- thoring the interactive visualizations for informative ers. Moreover, their spatial analytical functionality or analytical purposes: a) programming, b) template is often severely limited or non-existent. Similarly, editing, c) authoring tools and applications. the geographic information systems (e.g., QGIS 1 Programmatic approaches are the most demand- or ArcGIS 2 focus rather on map-making than map ing in terms of users’ skills and learning curve but use. However, both categories can provide the car- offer the most versatility for fine-tuning of visual tographic layers through public APIs, which can be appearance and interaction capabilities. The frame- used in the visualization authoring process. works for developing interactive visualizations are usually designed for use in web applications. D3 (Bo- 2.1 Geovisualization Types stock et al., 2011) is one of the most popular im- perative frameworks nowadays, and many other li- Geovisualizations often take advantage of combining braries use it. It allows mapping the input data to multiple layers where each layer presents only a sub- a Document Object Model (DOM) and transforms it set of data. The standard base layer is a cartographic via data-driven operations. ProtoVis (Bostock and map that provides a spatial context. Further, we list Heer, 2009) toolkit, also leveraging the imperative the most common types of geospatial data visualiza- paradigm, is based on the idea of decomposing visu- tion. alizations into hierarchies of visual primitives whose Point distribution maps represent the simplest visual properties are data functions. The declarative geovisualizations that serve for visualizing datasets paradigm frameworks represent Vega (Satyanarayan of elements containing only the location information et al., 2015) and Vega-lite (Satyanarayan et al., 2017). (1 a)). If the elements contain the location and one They both provide a set of building blocks for inter- descriptive numerical value, they could be plotted as active visualization designs. They differ in the level (proportional) symbol maps (1 b)). The symbol can of abstraction and primary use cases. Vega-lite is a be a circle or a glyph whose physical size determines high-level grammar build on top of Vega and was de- the value. Symbol maps are also useful when the el- signed for rapid prototyping of standard chart types. ement has two or three descriptive attributes since we Backward-compatibility allows programmers to im- can distinguish their size, shape, and color. More ad- plement more advanced use cases in Vega if needed. vanced modifications enable us to show even more Template editing is the exact opposite of program- matic approaches. It is a well-established way to cre- 1https://qgis.org/en/site/ ate simple charts in spreadsheet applications such as 2https://www.arcgis.com/index.html Microsoft Excel or Apache OpenOffice. The main 102 Geovisto: A Toolkit for Generic Geospatial Data Visualization Figure 1: Common geovisualization types: a) point distribution maps; b) proportional
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