Taggle: Combining Overview and Details in Tabular Data
Visualizations

J 2020

Taggle: Combining Overview and Details in Tabular Data Visualizations

FURMANOVÁ, Katarína; Samuel GRATZL; Holger STITZ; Thomas ZICHNER; Miroslava JAREŠOVÁ et al.

Základní údaje

Originální název

Taggle: Combining Overview and Details in Tabular Data Visualizations

Autoři

FURMANOVÁ, Katarína ; Samuel GRATZL; Holger STITZ; Thomas ZICHNER; Miroslava JAREŠOVÁ; Alexander LEX a Marc STREIT

Vydání

Information Visualization, 2020, 1473-8716

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 0.956

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/20:00115101

Organizační jednotka

Fakulta informatiky

Klíčová slova anglicky

visualization; tabular data

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 22. 4. 2021 19:14, RNDr. Katarína Furmanová, Ph.D.

Anotace

V originále

Most tabular data visualization techniques focus on overviews, yet many practical analysis tasks are concerned with investigating individual items of interest. At the same time, relating an item to the rest of a potentially large table is important. In this work, we present Taggle, a tabular visualization technique for exploring and presenting large and complex tables. Taggle takes an item-centric, spreadsheet-like approach, visualizing each row in the source data individually using visual encodings for the cells. At the same time, Taggle introduces data-driven aggregation of data subsets. The aggregation strategy is complemented by interaction methods tailored to answer specific analysis questions, such as sorting based on multiple columns and rich data selection and filtering capabilities. We demonstrate Taggle by a case study conducted by a domain expert on complex genomics data analysis for the purpose of drug discovery.

Citovat

FURMANOVÁ, Katarína; Samuel GRATZL; Holger STITZ; Thomas ZICHNER; Miroslava JAREŠOVÁ; Alexander LEX a Marc STREIT. Taggle: Combining Overview and Details in Tabular Data Visualizations. Information Visualization. 2020, roč. 19, č. 2, s. 114-136. ISSN 1473-8716. Dostupné z: https://doi.org/10.1177/1473871619878085.

@article{1551978,
   author = {Furmanová, Katarína and Gratzl, Samuel and Stitz, Holger and Zichner, Thomas and Jarešová, Miroslava and Lex, Alexander and Streit, Marc},
   article_number = {2},
   doi = {https://doi.org/10.1177/1473871619878085},
   keywords = {visualization; tabular data},
   language = {eng},
   issn = {1473-8716},
   journal = {Information Visualization},
   title = {Taggle: Combining Overview and Details in Tabular Data Visualizations},
   url = {https://journals.sagepub.com/doi/full/10.1177/1473871619878085},
   volume = {19},
   year = {2020}
}

TY  - JOUR
ID  - 1551978
AU  - Furmanová, Katarína - Gratzl, Samuel - Stitz, Holger - Zichner, Thomas - Jarešová, Miroslava - Lex, Alexander - Streit, Marc
PY  - 2020
TI  - Taggle: Combining Overview and Details in Tabular Data Visualizations
JF  - Information Visualization
VL  - 19
IS  - 2
SP  - 114-136
EP  - 114-136
SN  - 14738716
KW  - visualization
KW  - tabular data
UR  - https://journals.sagepub.com/doi/full/10.1177/1473871619878085
N2  - Most tabular data visualization techniques focus on overviews, yet many practical analysis tasks are concerned with investigating individual items of interest. At the same time, relating an item to the rest of a potentially large table is important. In this work, we present Taggle, a tabular visualization technique for exploring and presenting large and complex tables. Taggle takes an item-centric, spreadsheet-like approach, visualizing each row in the source data individually using visual encodings for the cells. At the same time, Taggle introduces data-driven aggregation of data subsets. The aggregation strategy is complemented by interaction methods tailored to answer specific analysis questions, such as sorting based on multiple columns and rich data selection and filtering capabilities. We demonstrate Taggle by a case study conducted by a domain expert on complex genomics data analysis for the purpose of drug discovery.
ER  -

FURMANOVÁ, Katarína; Samuel GRATZL; Holger STITZ; Thomas ZICHNER; Miroslava JAREŠOVÁ; Alexander LEX a Marc STREIT. Taggle: Combining Overview and Details in Tabular Data Visualizations. \textit{Information Visualization}. 2020, roč.~19, č.~2, s.~114-136. ISSN~1473-8716. Dostupné z: https://doi.org/10.1177/1473871619878085.

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