ICIC   25583
INSTITUTO DE CIENCIAS E INGENIERIA DE LA COMPUTACION
Unidad Ejecutora - UE
artículos
Título:
Cross-table linking and brushing: interactive visual analysis of multiple tabular data sets
Autor/es:
BÜHLER, KATJA; BEHAM, MICHAEL; MATKOVIK, KRESIMIR; GANUZA, MARÍA LUJÁN; SPLECHTNA, RAINER; PANDZIK, IGOR SUNDAY; GRACANIN, DENIS
Revista:
VISUAL COMPUTER
Editorial:
SPRINGER
Referencias:
Lugar: Berlin; Año: 2018 vol. 34 p. 1087 - 1098
ISSN:
0178-2789
Resumen:
Studying complex problems often requires identifying and exploring connections and dependencies among several, seemingly unrelated, data sets. Those data sets are often represented as data tables. We propose a novel approach to studying such data sets using linking and brushing across multiple data tables in a coordinated multiple views system. We first identify possible mappings from a subset of one data set to a subset of another data set. That collection of mappings is then used to specify linking among data sets and to support brushing across data sets. Brushing in one data set is then mapped to a brush in the destination data set. If the brush is refined in the destination data set, the inverse mapping, or a back-link, is used to determine the refined brush in the original data set. Brushing and back-links make it possible to efficiently create and analyze complex queries interactively in an iterative process. That process is further supported by a user interface that keeps track of the mappings, links and brushes. The proposed approach is evaluated using three data sets.