Persistent challenges in geovisualization – a community perspective

Peer-reviewed
Journal Article
Over four workshops, we collected community input on what people considered as persistent challenges in geovisualization with the participation of 72 experts from various sub-domains of geographic information science …
Author

Çöltekin, A., Bleisch, S., Andrienko, G., and Dykes, J.

Published

2017

Doi

[pdf]

Abstract

Over four workshops, we collected community input on what people considered as persistent challenges in geovisualization with the participation of 72 experts from various sub-domains of geographic information science and technology. We categorize and analyze this bottom-up input, and contrast it with the previously published research challenges based on five research agenda papers (top-down). We observe certain overlaps but also some interesting differences between the top-down and bottomup approaches. A synthesis of the two suggests three major issues as persistent challenges: (1) a better understanding of the scope of our domain, how it interacts with other domains, and how to make this happen, (2) a systematic understanding of human factors, (3) a ‘practicable’ set of guidelines that matches the visualization types to task types, and guides the practitioner to design geovisualizations that are appropriate and helpful to the user. Distinguishing persistent from important, we discuss why the identified challenges are persistent, and draw recommendations for action based on our observations and interpretations. We believe these findings will help building a stronger, bettergrounded research agenda for our community.

Figures

Participants answered to the survey questions using sticky notes.

The terminology in geovisualization since computers became commonplace.

Google N grams for ‘cartography’ (top), and other terms featured in Figure 1 (bottom). The rise of geographic visualization roughly corresponds with the fall or the stagnation of the other terms (‘geovisualization’ shows the same pattern).

Research themes as mentioned by all participants in all four workshops. Note that single statements within a category may overlap with more than one category.

Categories that emerged from the analysis of the five research agenda papers re-organized into themes.

Synthesized bottom-up and top-down findings on persistent research challenges, categorized based on their relationship to science.

BibTeX

@article{coltekin_persistentChallengesGeoVis_2017,
 abstract = {Over four workshops, we collected community input on what people considered as persistent challenges in geovisualization with the participation of 72 experts from various sub-domains of geographic information science and technology. We categorize and analyze this bottom-up input, and contrast it with the previously published research challenges based on five research agenda papers (top-down). We observe certain overlaps but also some interesting differences between the top-down and bottomup approaches. A synthesis of the two suggests three major issues as persistent challenges: (1) a better understanding of the scope of our domain, how it interacts with other domains, and how to make this happen, (2) a systematic understanding of human factors, (3) a ‘practicable’ set of guidelines that matches the visualization types to task types, and guides the practitioner to design geovisualizations that are appropriate and helpful to the user. Distinguishing persistent from important, we discuss why the identified challenges are persistent, and draw recommendations for action based on our observations and interpretations. We believe these findings will help building a stronger, bettergrounded research agenda for our community.},
 author = {Çöltekin, Arzu and Bleisch, Susanne and Andrienko, Gennady and Dykes, Jason},
 doi = {10.1080/23729333.2017.1302910},
 journal = {International Journal of Cartography},
 pages = {115--139},
 title = {Persistent challenges in geovisualization – a community perspective},
 url = {https://www.tandfonline.com/doi/full/10.1080/23729333.2017.1302910},
 volume = {3},
 year = {2017}
}