Paper Info
Title
Visual Querying of Semantically Enriched Movement Data.
Abstract
Visual data exploration is used to reveal unknown patterns that, however, need to be validated, refined, and extracted for a final presentation and reporting. We contribute VESPa, a pattern-based visual query language for event sequences. With VESPa, analysts can formulate hypotheses gained and query the data for matches. In an interative analysis loop the pattern can be altered with further restrictions to narrow down the result set. Our language allows for (1) hypothesis expression and refinement, (2) visual querying, and (3) knowledge externalization. We focus on semantically enrichend movement data, used in law enforcement, consumer, and traffic analysis. To evaluate the applicability we present two case studies as well as a user study consisting of comprehensive and composition tasks.
Year
DOI
Venue
2016
10.1007/978-3-319-64870-5_12
Communications in Computer and Information Science
Keywords
DocType
Volume
Visual query language,Semantic movement analysis
Conference
693
ISSN
Citations 
PageRank 
1865-0929
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Florian Haag18510.30
Robert Kruger2584.07
Thomas Ertl34417401.52