摘要
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.
基金
This research was supported by Fraunhofer Center for Machine Learning within the Fraunhofer Cluster for Cognitive Internet Technologies
by DFG within Priority Programme 1894(SPP VGI)
by EU in project SoBigData++
by SESAR in projects TAPAS and SIMBAD
by Austrian Science Fund(FWF)project KnowVA(grant P31419-N31).
