Publications in Scientific Journals:

N. Andrienko, G. Andrienko, S. Miksch, H. Schumann, S Wrobel:
"A Theoretical Model for Pattern Discovery in Visual Analytics";
accepted for publication in Visual Informatics (2020).

English abstract:
The word `patternī frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable definition of the concept of a pattern in a data distribution as a combination of multiple interrelated elements of two or more data components that can be represented and treated as a unified whole. Our theoretical model describes how patterns are made by relationships existing between data elements. Knowing the types of these relationships, it is possible to predict what kinds of patterns may exist. We demonstrate how our model underpins and refines the established fundamental principles of visualisation. The model also suggests a range of interactive analytical operations that can support visual analytics workflows where patterns, once discovered, are explicitly involved in further data analysis.

German abstract:

Visual analytics, Data distribution, Pattern, Abstraction, Data organisation, Data arrangement, Data variation, Pattern discovery

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.