Visual matrix explorer for collaborative seriation
Innar Liiv, Rain Opik, Jaan Übi, John Stasko · Wiley Interdisciplinary Reviews Computational Statistics · 2011
Abstract In this article, we present a web‐based open source tool to support cross‐disciplinary collaborative seriation with the following goals: to compare different matrix permutations, to discover patterns from the data, annotate it, and accumulate knowledge. Seriation is an unsupervised data mining technique that reorders objects into a sequence along a one‐dimensional continuum to make sense of the whole series. Clustering assigns objects to groups, whereas seriation assigns objects to a position within a sequence. Seriation has been applied to a variety of disciplines including archaeology and anthropology; cartography, graphics, and information visualization; sociology and sociometry; psychology and psychometrics; ecology; biology and bioinformatics; cellular manufacturing; and operations research. Interestingly, across those different disciplines, there are several commonly emerging similar structural patterns. Visual Matrix Explorer allows users to explore and link those patterns, share an online workplace and instantly transmit changes in the system to other users.WIREs Comp Stat2012, 4:85–97. doi: 10.1002/wics.193 This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization