A Visual Interface for Multivariate Temporal Data: Finding Patterns of Events across Multiple Histories

TLDR

Finding patterns of events over time is important for analyzing patient histories, Web logs, news stories, and criminal activities, and temporal patterns are defined as sequences of events with inter‑event time spans. This paper presents PatternFinder, an integrated interface for querying and visualizing temporal patterns in multivariate and categorical datasets. PatternFinder lets users specify event attributes and time spans to generate expressive pattern queries, and it supports a spectrum of query specificity from broad to fine‑grained. PatternFinder’s query capabilities, coupled with ball‑and‑chain and tabular visualizations, enable users to effectively query, explore, and analyze event patterns across entities such as patient histories, terrorist groups, and Web logs.

Abstract

Finding patterns of events over time is important in searching patient histories, Web logs, news stories, and criminal activities. This paper presents PatternFinder, an integrated interface for query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets. We define temporal patterns as sequences of events with inter-event time spans. PatternFinder allows users to specify the attributes of events and time spans to produce powerful pattern queries that are difficult to express with other formalisms. We characterize the range of queries PatternFinder supports as users vary the specificity at which events and time spans are defined. Pattern Finder's query capabilities together with coupled ball-and-chain and tabular visualizations enable users to effectively query, explore and analyze event patterns both within and across data entities (e.g. patient histories, terrorist groups, Web logs, etc.)