Abstract Cartographic maps have been shown to provide cognitive benefits when interpreting data in relation to a geographic location. In visualization, the term map-like describes techniques that incorporate characteristics of cartographic maps in their representation of abstract data. However, the field of map-like visualization is vast and currently lacks a clear classification of the existing techniques. Moreover, choosing the right technique to support a particular visualization task is further complicated, as techniques are scattered across different domains, with each considering different characteristics as map-like. In this paper, we give an overview of the literature on map-like visualization and provide a hierarchical classification of existing techniques along two general perspectives: imitation and schematization of cartographic maps. Each perspective is further divided into four principal categories that group common map-like techniques along the visual primitives they affect. We further discuss this classification from a task-centered view and highlight open research questions.
%0 Journal Article
%1 hograefer2020state
%A Hogräfer, Marius
%A Heitzler, Magnus
%A Schulz, Hans-Jörg
%D 2020
%J Computer Graphics Forum
%K ddm map mk5.4 survey visualization
%N 3
%P 647-674
%R https://doi.org/10.1111/cgf.14031
%T The State of the Art in Map-Like Visualization
%U https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14031
%V 39
%X Abstract Cartographic maps have been shown to provide cognitive benefits when interpreting data in relation to a geographic location. In visualization, the term map-like describes techniques that incorporate characteristics of cartographic maps in their representation of abstract data. However, the field of map-like visualization is vast and currently lacks a clear classification of the existing techniques. Moreover, choosing the right technique to support a particular visualization task is further complicated, as techniques are scattered across different domains, with each considering different characteristics as map-like. In this paper, we give an overview of the literature on map-like visualization and provide a hierarchical classification of existing techniques along two general perspectives: imitation and schematization of cartographic maps. Each perspective is further divided into four principal categories that group common map-like techniques along the visual primitives they affect. We further discuss this classification from a task-centered view and highlight open research questions.
@article{hograefer2020state,
abstract = {Abstract Cartographic maps have been shown to provide cognitive benefits when interpreting data in relation to a geographic location. In visualization, the term map-like describes techniques that incorporate characteristics of cartographic maps in their representation of abstract data. However, the field of map-like visualization is vast and currently lacks a clear classification of the existing techniques. Moreover, choosing the right technique to support a particular visualization task is further complicated, as techniques are scattered across different domains, with each considering different characteristics as map-like. In this paper, we give an overview of the literature on map-like visualization and provide a hierarchical classification of existing techniques along two general perspectives: imitation and schematization of cartographic maps. Each perspective is further divided into four principal categories that group common map-like techniques along the visual primitives they affect. We further discuss this classification from a task-centered view and highlight open research questions.},
added-at = {2022-03-22T12:05:26.000+0100},
author = {Hogräfer, Marius and Heitzler, Magnus and Schulz, Hans-Jörg},
biburl = {https://www.bibsonomy.org/bibtex/2ff15228e63035566ed84eb2c72b5cb06/jaeschke},
doi = {https://doi.org/10.1111/cgf.14031},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.14031},
interhash = {63d24956d0642b5e2b71fbbd64300caf},
intrahash = {ff15228e63035566ed84eb2c72b5cb06},
journal = {Computer Graphics Forum},
keywords = {ddm map mk5.4 survey visualization},
number = 3,
pages = {647-674},
timestamp = {2022-03-22T12:05:54.000+0100},
title = {The State of the Art in Map-Like Visualization},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14031},
volume = 39,
year = 2020
}