Visualization methods for time-dependent data - an overview

Müller, Hausi A.; Schumann,

doi:10.1109/wsc.2003.1261490

Cited by 113 publications

(89 citation statements)

References 14 publications

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“…Alexopoulos (2006) presents a comprehensive review of methods for the analysis of outputs from simulation experimentation. Müller and Schumann (2003) investigate methods for the visualization of time-dependent data that can be used to investigate aspects of simulation modelling and give an overview of dynamic presentation techniques and event-based visualization. Kuljis and Paul (2000) review the implications of the World Wide Web with respect to the development of simulation modelling software and applications.…”

Section: Studies Of Simulation Modelling Literaturementioning

confidence: 99%

Simulation modelling is 50! Do we need a reality check?

Taylor

Eldabi

Riley

et al. 2009

Journal of the Operational Research Society

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Simulation modelling is a fascinating research field. The techniques and tools of simulation modelling have been used to research and investigate the behaviour of various systems in a wide range of areas such as commerce, computer networks, defence, health, manufacturing and transportation. Indeed, the study of the use of these techniques and tools, and the development of new forms of these, are a rich source of research in their own right. Simulation modelling is about to reach the 50th anniversary of the development of GSP (General Simulation Program), the first simulation modelling language (Tocher and Owen, 1960). There have been several historical accounts of simulation modelling research. To complement these, we have performed a review of the recent history of simulation modelling. This study targeted three leading journals dedicated to this field. These are the ACM Transactions of Modeling and Computer Simulation, Simulation: Transactions of The Society for Modeling and Simulation International and Simulation Modelling Practice and Theory (formerly Simulation Practice and Theory). The study covered the first 6 years of this century (2000)(2001)(2002)(2003)(2004)(2005) and included 576 papers. The key observation of this work was the relative lack of 'real world' involvement in simulation modelling research and an even greater lack of evidence of 'real world' benefit, arguably very alarming outcomes for an applied field. To further investigate this observation two additional surveys were carried out, one to study if real world papers appeared in the more widely known OR/MS literature (837 papers in 12 journals) and one to study if such papers appeared in Manufacturing and Logistics, an application area closely associated with simulation modelling (1077 papers in 10 journals). The results of these surveys confirmed our observations. We ask if this is the natural evolution of a field that has existed for half a century or an indication of a worrying problem? This paper reports on our findings and discusses whether or not simulation modelling research urgently needs to face a 'reality check.'

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Section: Studies Of Simulation Modelling Literaturementioning

confidence: 99%

Simulation modelling is 50! Do we need a reality check?

Taylor

Eldabi

Riley

et al. 2009

Journal of the Operational Research Society

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“…Following Frank's time model [25], Muller and Schumann [8] suggested an approach to categorizing data as a precursor to creating a time-based visualization. From this, some key parameters were identified as being necessary to create a real-time IDS visualization:…”

Section: B Attribute Mappingmentioning

confidence: 99%

“…1, when a number of alerts are recorded in a log file, each line can be described as a discrete event mapped on a vertical "ordinally scaled time-axis [8]", meaning that the sequence of events is clear, but that the interval period between events is not explicitly encoded in the presentation of the data.…”

Section: Introductionmentioning

confidence: 99%

Pianola - Visualization of Multivariate Time-Series Security Event Data

Thomson¹,

Graham

Kennedy

2013

2013 17th International Conference on Information Visualisation

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Abstract-Monitoring log files for network intrusions is unwieldy. To build a mental model of the log, an analyst is required to recognise continuous timelines and attack patterns from a dataset that is essentially limited to an ordered list of events. Information Visualization techniques arrange data into directly perceivable visual patterns that may alleviate some overheads associated with interpreting these datasets and improve the ability of users, especially those in resourcestretched Small and Medium sized Businesses (SMBs), to make sense of activity patterns in Intrusion Detection System (IDS) event logs. To this end, we discuss existing network security visualizations for IDS logs and after examining the strengths and drawbacks of those applications we have prototyped a visualization tool, Pianola, that arranges events on multiple timelines to reveal patterns both in time and across a network. The tool was evaluated against the traditional use of commandline interface (CLI)-based tools for analyzing network security events and displayed significant improvements in both recognition and detection of attacks and reduction in the users' subjective workload, measured using the NASA Task Load index (TLX).

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“…One of the most commonly researched data types is temporal and timeline data, and various approaches to visualize it exist (see [2] and [14] for an overview). Although application scenarios often involve spatial and scientific information, there are also visualizations for non-spatial and biographical data, such as the LifeLines [15], a prominent example for general-purpose creation of personal timelines in medical or legal domains (which was extended by PatternFinder [7] that focused on event-based patterns).…”

Section: General Information Visualizationmentioning

confidence: 99%

Interactive exploration of music listening histories

Dias

Fonseca

Gonçalves

2012

Proceedings of the International Working Conference on Advanced Visual Interfaces

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Over the past years, music listening histories have become easily accessible due to the expansion of online lifelogging services. These histories represent the sequence of songs listen by users over time. Although this data contains intrinsic users' tastes and listening behaviors, it has been mainly used to personalize recommendations. Tools to help users exploring and reasoning about the information contained in the listening history, only recently have started to emerge. In this paper we describe a new visualization and exploration tool that allows users to interactively browse their listening histories, while leading them to identify listening trends and habits. Our solution combines a rich-featured timeline-based visualization, a set of synchronized-views and an interactive filtering mechanism to provide a flexible, effective and easy to use system for the analysis and knowledge exploration of listening histories. This was complemented with brushing and highlighting techniques to uncover listening trends about artists, albums and songs. Experimental evaluation with users revealed that they were able to complete all the requested tasks with a low error rate, and that they found the solution flexible and easy to use. Additionally, users were able to infer about their main life events and listening changes, which indicates that our combination of visualization techniques is effective in conveying relevant information about the listening habits.

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Visualization methods for time-dependent data - an overview

Cited by 113 publications

References 14 publications

Simulation modelling is 50! Do we need a reality check?

Simulation modelling is 50! Do we need a reality check?

Pianola - Visualization of Multivariate Time-Series Security Event Data

Interactive exploration of music listening histories

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