City Research Online

A theoretical model for pattern discovery in visual analytics

Andrienko, N. ORCID: 0000-0003-3313-1560, Andrienko, G. ORCID: 0000-0002-8574-6295, Miksch, S. , Schumann, H. & Wrobel, S. (2020). A theoretical model for pattern discovery in visual analytics. Visual Informatics, 5(1), pp. 23-42. doi: 10.1016/j.visinf.2020.12.002


The word ‘pattern’ 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.

Publication Type: Article
Publisher Keywords: Visual analytics, data distribution, pattern, abstraction, data organisation, data arrangement, data variation, pattern discovery
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science > giCentre
SWORD Depositor:
[thumbnail of 1-s2.0-S2468502X20300930-main.pdf]
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (4MB) | Preview


Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email


Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login