@PHDTHESIS {lampe11thesis,
author = "Ove Daae Lampe",
title = "Interactive Visual Analysis of Process Data",
school = "Department of Informatics, University of Bergen, Norway",
year = "2011",
month = "Sep",
abstract = "Data gathered from processes, or process data, contains many different aspectsthat a visualization system should also convey. Aspects such as, temporalcoherence, spatial connectivity, streaming data, and the need for in-situvisualizations, which all come with their independent challenges. Additionally,as sensors get more affordable, and the benefits of measurements get clearer weare faced with a deluge of data, of which sizes are rapidly growing. With allthe aspects that should be supported and the vast increase in the amount ofdata, the traditional techniques of dashboards showing the recent data becomesinsufficient for practical use. In this thesis we investigate how to extend the traditionalprocess visualization techniques by bringing the streaming process datainto an interactive visual analysis setting. The augmentation of process visualizationwith interactivity enables the users to go beyond the mere observation,pose questions about observed phenomena and delve into the data to mine forthe answers. Furthermore, this thesis investigates how to utilize frequency based,as opposed to item based, techniques to show such large amounts of data. Byutilizing Kernel Density Estimates (KDE) we show how the display of streamingdata benefit by the non-parametric automatic aggregation to interpret incomingdata put in context to historic data.",
pdf = "pdfs/lampe11thesis.pdf",
images = "images/lampe11thesis.png",
thumbnails = "images/lampe11thesis_thumb.png",
isbn = "978-82-308-1910-4"
}