Data scale as cartography: a semi-automatic approach for thematic web map creation

Degbelo, Auriol; Sarfraz, Saad; Kray, Christian

doi:10.1080/15230406.2019.1677176

Cited by 7 publications

(8 citation statements)

References 55 publications

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“…the knowledge can be encoded into a tree-like model via a transformation). An example of explicit decision tree is the decision tree to guide the choice of thematic map types by (Kraak et al, 2020), while the decision tree used in the AdaptiveMaps prototype to automate the creation of web maps (Degbelo et al, 2020) is implicit. Variable syntactics are also a good example of implicit decision trees.…”

Section: Exemplar Decision Trees From Cartographymentioning

confidence: 99%

“…The first is the decision tree selection area: this is where the user can choose a decision tree to be visualized (the selection area is not shown in Figure 3). As of this writing, the selection area provides two decision trees from Figure 1 as examples to start with: (Kraak et al, 2020) and (Degbelo et al, 2020). The user is also given the possibility of uploading additional decision trees, using the JSON-based format introduced in Section 3.1.…”

Section: Prototypementioning

confidence: 99%

“…For instance, creating maps through programming can be done using D3.js (Bostock et al, 2011), Vega-Lite (Satyanarayan et al, 2017), Florence (Poorthuis et al, 2020), Unfolding (Nagel et al, 2013), the mapmap.js API (Ledermann and Gartner, 2015), or programming languages such as R or Python. Creating maps through a user interface that suggests meaningful defaults can be done through tools/toolkits such as Descartes (Andrienko and Andrienko, 1999), SDG Viz (Gong, 2019), AdaptiveMaps (Degbelo et al, 2020), the GAV Toolkit (Van Ho et al, 2012), the Geoviz Toolkit (Hardisty and Robinson, 2011), and commercial solutions such as ArcGis Online 2 or Carto 3 .…”

Section: Introductionmentioning

confidence: 99%

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3d4dt: An Approach to Explore Decision Trees for Thematic Map Creation as an Interactive 3d Scene

Bagert¹,

Degbelo

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Several tools have been proposed to automatically create thematic maps. A common drawback of these tools is that they rarely provide means for users to explore their decision trees. Users may thus create maps or get some maps proposed, but not know why some suggestions of maps were made. To address this gap, this work introduces 3D4DT, an approach to explore decision trees as a three-dimensional interactive scene. The 3D4DT approach uses JSON as a machine-readable format to represent decision trees and maps JSON elements to user interface elements (e.g. radio buttons and cubes). A preliminary evaluation of 3D4DT has shown effectiveness gains in comparison to information displayed as text+picture, for a decision tree with a simple hierarchical structure. The contributions of this work are relevant to the design of more transparent software for automated thematic map creation.

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Section: Exemplar Decision Trees From Cartographymentioning

confidence: 99%

Section: Prototypementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3d4dt: An Approach to Explore Decision Trees for Thematic Map Creation as an Interactive 3d Scene

Bagert¹,

Degbelo

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…For example, Nagel et al (2013) developed a library, Unfolding, for writing interactive maps in Processing and Java, while Ledermann and Gartner (2015) provide a "cartographic" API for making maps with JavaScript (JS). More recently, Degbelo, Sarfraz, and Kray (2020) created AdaptiveMaps, a no-code semi-automatic approach to making thematic web maps that is based on Bertin's visual variables. This no-code or low-code approach also shares similarities with the full-stack (i.e., covering both spatial analysis and cartographic functionality) approaches to web cartography that commercial providers are now offering-CARTO, Mapbox, and Esri are primary examples of companies in this space.…”

Section: Th E Ecosystem Of Web Mappi Ng An D I Nteractive Data Visualizationmentioning

confidence: 99%

Florence: a Web-based Grammar of Graphics for Making Maps and Learning Cartography

Poorthuis

Zee

Guo

et al. 2020

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Online, web-based cartography workflows use a dizzying variety of software suites, libraries, and programming languages. This proliferation of mapmaking technologies, often developed from a software engineering rather than a cartographic foundation, creates a series of challenges for cartography education, research, and practice. To address these challenges, we introduce a JavaScript-based open-source framework for web-based cartography and data visualization. It is built on top of existing open web standards that are already in intensive use for online mapmaking today, but provides a framework that is firmly based on cartographic and visualization theory rather than software engineering concepts. Specifically, we adopt concepts from Bertin’s Semiology of Graphics and Wilkinson’s Grammar of Graphics to create a language with a limited number of core concepts and verbs that are combined in a declarative style of “writing” visualizations. In this paper, we posit a series of design guidelines that have informed our approach, and discuss how we translate these tenets into a software implementation and framework with specific use cases and examples. We frame the development of the software and the discussion specifically in the context of the use of such tools in cartography education. With this framework, we hope to provide an example of a software for web-based data visualization that is in sync with cartographic theories and objectives. Such approaches allow for potentially greater cartographic flexibility and creativity, as well as easier adoption in cartography courses.

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“…Why choriented: Choropleth and graduated symbol maps are well known and the most frequent in the context of open data geovisualization (see e.g. Degbelo, Sarfraz, and Kray, 2020). Nonetheless, as the number of classes grows, distinguishing between adjacent classes becomes increasingly challenging.…”

Section: Introductionmentioning

confidence: 99%

Choriented Maps: Visualizing SDG Data on Mobile Devices

Gorte,

Degbelo

2021

Preprint

Self Cite

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Choropleth maps and graduated symbol maps are often used to visualize quantitative geographic data. However, as the number of classes grows, distinguishing between adjacent classes increasingly becomes challenging. To mitigate this issue, this work introduces two new visualization types: choriented maps (maps that use colour and orientation as variables to encode geographic information) and choriented mobile (an optimization of choriented maps for mobile devices). The maps were evaluated in a graphical perception study featuring the comparison of SDG (Sustainable Development Goal) data for several European countries. Choriented maps and choriented mobile visualizations resulted in comparable, sometimes better effectiveness and confidence scores than choropleth and graduated symbol maps. Choriented maps and choriented mobile visualizations also performed well regarding efficiency overall and performed worse only than graduated symbol maps. These results suggest that the use of colour and orientation as visual variables in combination can improve the selectivity of map symbols and user performance during the exploration of geographic data in some scenarios.

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Data scale as cartography: a semi-automatic approach for thematic web map creation

Cited by 7 publications

References 55 publications

3d4dt: An Approach to Explore Decision Trees for Thematic Map Creation as an Interactive 3d Scene

3d4dt: An Approach to Explore Decision Trees for Thematic Map Creation as an Interactive 3d Scene

Florence: a Web-based Grammar of Graphics for Making Maps and Learning Cartography

Choriented Maps: Visualizing SDG Data on Mobile Devices

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