Reprojecting Visualizations for Advanced Interaction

Information

Abstract

Today, massive sets of complex and heterogeneous data are collected and stored and their effective use becomes more challenging. Traditional tools for analysis utilize automatic analysis methods, but often such methods are not sufficient any more. Interactive visual analysis (IVA) integrates the analytic capabilities of the computer and the user-guided analysis to facilitate knowledge discovery in these complex datasets [1-3]. IVA provides an interactive and iterative exploration and analysis framework where the user is able to utilize the strengths of human perception and cognition in the exploration and analysis of complex and heterogeneous data [4]. IVA employs a well-proven approach of coordinated multiple views [7] where different views are used to jointly visualize data and the user can correlate different views. When the user interactively selects (brushes) subset of the displayed data in one of the views, then the selected subset of the data items is consistently highlighted in all linked views [7-9]. All items that are not brushed are shown as context. The user knows the relation of brushed data items in the data subspace, and can explore and analyze the data in linked subspaces in order to understand complex and often hidden relationships between certain data aspects (brushing and linking) [5,10]. Nowadays, brushing is available as a feature in many data visualization systems and serves as an important mechanism for the interactive visual exploration and analysis of data. Interactive visual analysis has different levels of complexity [11]. At its basic level, IVA builds on the combination of different views and provides only one brush in a view, for interactively selecting features. Users are able to move/alter/extend the brush interactively in order to mark up interesting data parts, i.e., to do a feature localization, a local investigation or a multivariate analysis. The second IVA level allows complex, composite brushes that can span multiple views, constructed using different logical combination schemes. The user can iteratively start a deeper information drill-down to answer complex questions about the data. The third IVA level combines complex interaction and general information extraction mechanisms. Here exist two (partially complementary) approaches to extract deeply hidden implicit information from complex data sets: (i) first derive additional attribute(s) and then show & brush, and (ii) use an advanced brush to select `hidden¿ relations in the data. In other words the user can use an advanced brush on simple data (complex interaction) or a simple brush on complex data (complex interaction). During the complex data approach the user must complete several steps during IVA and this approach requires more viewing space (several views may be necessary). The advanced-brush approach can provide the same insight from information with using just a single step and using one view. But advanced brushes require complex interaction and uninformed users have to learn how to properly use such brushes for an effective IVA. On-demand data computation, such as interactive attribute aggregation and derivation can be provided to the user during IVA with the help of advanced derivation dialogs [11]. Advanced brushing can be also included in an IVA framework as an alternative or in addition to these data derivation approaches, but currently mechanisms are not available which allow the user to create an advanced brush on the fly. Structured representation of advanced-brushing space is required as a first step toward a creation of generic advanced brushes.

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BibTeX

@runmasterthesis{Sanjin_Rados_RV,
  title =      "Reprojecting Visualizations for Advanced Interaction",
  author =     "Sanjin Rados",
  abstract =   "Today, massive sets of complex and heterogeneous data are
               collected and stored and their effective use becomes more
               challenging. Traditional tools for analysis utilize
               automatic analysis methods, but often such methods are not
               sufficient any more. Interactive visual analysis (IVA)
               integrates the analytic capabilities of the computer and the
               user-guided analysis to facilitate knowledge discovery in
               these complex datasets [1-3]. IVA provides an interactive
               and iterative exploration and analysis framework where the
               user is able to utilize the strengths of human perception
               and cognition in the exploration and analysis of complex and
               heterogeneous data [4]. IVA employs a well-proven approach
               of coordinated multiple views [7] where different views are
               used to jointly visualize data and the user can correlate
               different views. When the user interactively selects
               (brushes) subset of the displayed data in one of the views,
               then the selected subset of the data items is consistently
               highlighted in all linked views [7-9]. All items that are
               not brushed are shown as context. The user knows the
               relation of brushed data items in the data subspace, and can
               explore and analyze the data in linked subspaces in order to
               understand complex and often hidden relationships between
               certain data aspects (brushing and linking) [5,10].
               Nowadays, brushing is available as a feature in many data
               visualization systems and serves as an important mechanism
               for the interactive visual exploration and analysis of data.
               Interactive visual analysis has different levels of
               complexity [11]. At its basic level, IVA builds on the
               combination of different views and provides only one brush
               in a view, for interactively selecting features. Users are
               able to move/alter/extend the brush interactively in order
               to mark up interesting data parts, i.e., to do a feature
               localization, a local investigation or a multivariate
               analysis. The second IVA level allows complex, composite
               brushes that can span multiple views, constructed using
               different logical combination schemes. The user can
               iteratively start a deeper information drill-down to answer
               complex questions about the data. The third IVA level
               combines complex interaction and general information
               extraction mechanisms. Here exist two (partially
               complementary) approaches to extract deeply hidden implicit
               information from complex data sets: (i) first derive
               additional attribute(s) and then show & brush, and (ii) use
               an advanced brush to select `hidden¿ relations in the data.
               In other words the user can use an advanced brush on simple
               data (complex interaction) or a simple brush on complex data
               (complex interaction). During the complex data approach the
               user must complete several steps during IVA and this
               approach requires more viewing space (several views may be
               necessary). The advanced-brush approach can provide the same
               insight from information with using just a single step and
               using one view. But advanced brushes require complex
               interaction and uninformed users have to learn how to
               properly use such brushes for an effective IVA. On-demand
               data computation, such as interactive attribute aggregation
               and derivation can be provided to the user during IVA with
               the help of advanced derivation dialogs [11]. Advanced
               brushing can be also included in an IVA framework as an
               alternative or in addition to these data derivation
               approaches, but currently mechanisms are not available which
               allow the user to create an advanced brush on the fly.
               Structured representation of advanced-brushing space is
               required as a first step toward a creation of generic
               advanced brushes.",
  URL =        "/research/publications/ongoing/Sanjin_Rados_RV/",
}