Parallel Hierarchies: A Visualization for Cross-tabulating Hierarchical Categories

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Parallel Hierarchies: A Visualization for Cross-tabulating Hierarchical Categories. / Vosough, Zana; Hogräfer, Marius; Royer, Loïc A.; Groh, Rainer; Schulz, Hans-Jörg.

In: Computers & Graphics, Vol. 76, No. November, 11.2018, p. 1-17.

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Vosough, Zana ; Hogräfer, Marius ; Royer, Loïc A. ; Groh, Rainer ; Schulz, Hans-Jörg. / Parallel Hierarchies: A Visualization for Cross-tabulating Hierarchical Categories. In: Computers & Graphics. 2018 ; Vol. 76, No. November. pp. 1-17.

Bibtex

@article{a324de4bf0584e5da313294d8225bfa2,
title = "Parallel Hierarchies: A Visualization for Cross-tabulating Hierarchical Categories",
abstract = "The visualization of categorical datasets is an open field of research. While a number of standard diagramming techniques exist to investigate data distributions across multiple properties, these are rarely geared to take advantage of additional data properties – either given or derived. As a result, the data display is not as expressive as it could be when incorporating these properties, and it misses out on the potential of leveraging these properties for the data's interactive exploration. In this paper, we present the visualization technique Parallel Hierarchies that is specifically tailored to take hierarchical categorizations into account. With Parallel Hierarchies, it is possible to individually adjust the desired level of detail for each categorical data property through drill-down and roll-up operations. This enables the analyst to selectively change levels of detail as the data analysis progresses and new questions arise. We illustrate the utility of Parallel Hierarchies with a demographic and a biological use case, and we report on a qualitative user study evaluating this visualization technique in an industrial scenario.",
keywords = "Categorical data analysis, Interactive exploration, Tree visualization",
author = "Zana Vosough and Marius Hogr{\"a}fer and Royer, {Lo{\"i}c A.} and Rainer Groh and Hans-J{\"o}rg Schulz",
year = "2018",
month = "11",
doi = "10.1016/j.cag.2018.07.009",
language = "English",
volume = "76",
pages = "1--17",
journal = "Computers & Graphics",
issn = "0097-8493",
publisher = "Pergamon Press",
number = "November",

}

RIS

TY - JOUR

T1 - Parallel Hierarchies: A Visualization for Cross-tabulating Hierarchical Categories

AU - Vosough, Zana

AU - Hogräfer, Marius

AU - Royer, Loïc A.

AU - Groh, Rainer

AU - Schulz, Hans-Jörg

PY - 2018/11

Y1 - 2018/11

N2 - The visualization of categorical datasets is an open field of research. While a number of standard diagramming techniques exist to investigate data distributions across multiple properties, these are rarely geared to take advantage of additional data properties – either given or derived. As a result, the data display is not as expressive as it could be when incorporating these properties, and it misses out on the potential of leveraging these properties for the data's interactive exploration. In this paper, we present the visualization technique Parallel Hierarchies that is specifically tailored to take hierarchical categorizations into account. With Parallel Hierarchies, it is possible to individually adjust the desired level of detail for each categorical data property through drill-down and roll-up operations. This enables the analyst to selectively change levels of detail as the data analysis progresses and new questions arise. We illustrate the utility of Parallel Hierarchies with a demographic and a biological use case, and we report on a qualitative user study evaluating this visualization technique in an industrial scenario.

AB - The visualization of categorical datasets is an open field of research. While a number of standard diagramming techniques exist to investigate data distributions across multiple properties, these are rarely geared to take advantage of additional data properties – either given or derived. As a result, the data display is not as expressive as it could be when incorporating these properties, and it misses out on the potential of leveraging these properties for the data's interactive exploration. In this paper, we present the visualization technique Parallel Hierarchies that is specifically tailored to take hierarchical categorizations into account. With Parallel Hierarchies, it is possible to individually adjust the desired level of detail for each categorical data property through drill-down and roll-up operations. This enables the analyst to selectively change levels of detail as the data analysis progresses and new questions arise. We illustrate the utility of Parallel Hierarchies with a demographic and a biological use case, and we report on a qualitative user study evaluating this visualization technique in an industrial scenario.

KW - Categorical data analysis

KW - Interactive exploration

KW - Tree visualization

UR - https://parallelhierarchies.github.io/

UR - http://www.scopus.com/inward/record.url?scp=85052212432&partnerID=8YFLogxK

U2 - 10.1016/j.cag.2018.07.009

DO - 10.1016/j.cag.2018.07.009

M3 - Journal article

VL - 76

SP - 1

EP - 17

JO - Computers & Graphics

JF - Computers & Graphics

SN - 0097-8493

IS - November

ER -