103,242 research outputs found
Space for Two to Think: Large, High-Resolution Displays for Co-located Collaborative Sensemaking
Large, high-resolution displays carry the potential to enhance single display groupware collaborative sensemaking for intelligence analysis tasks by providing space for common ground to develop, but it is up to the visual analytics tools to utilize this space effectively. In an exploratory study, we compared two tools (Jigsaw and a document viewer), which were adapted to support multiple input devices, to observe how the large display space was used in establishing and maintaining common ground during an intelligence analysis scenario using 50 textual documents. We discuss the spatial strategies employed by the pairs of participants, which were largely dependent on tool type (data-centric or function-centric), as well as how different visual analytics tools used collaboratively on large, high-resolution displays impact common ground in both process and solution. Using these findings, we suggest design considerations to enable future co-located collaborative sensemaking tools to take advantage of the benefits of collaborating on large, high-resolution displays
Usability testing for improving interactive geovisualization techniques
Usability describes a product’s fitness for use according to a set of predefined criteria.
Whatever the aim of the product, it should facilitate users’ tasks or enhance their performance
by providing appropriate analysis tools. In both cases, the main interest is to satisfy users in
terms of providing relevant functionality which they find fit for purpose. “Testing usability
means making sure that people can find and work with [a product’s] functions to meet their
needs” (Dumas and Redish, 1999: 4). It is therefore concerned with establishing whether
people can use a product to complete their tasks with ease and at the same time help them
complete their jobs more effectively.
This document describes the findings of a usability study carried out on DecisionSite Map
Interaction Services (Map IS). DecisionSite, a product of Spotfire, Inc.,1 is an interactive
system for the visual and dynamic exploration of data designed for supporting decisionmaking.
The system was coupled to ArcExplorer (forming DecisionSite Map IS) to provide
limited GIS functionality (simple user interface, basic tools, and data management) and
support users of spatial data. Hence, this study set out to test the suitability of the coupling
between the two software components (DecisionSite and ArcExplorer) for the purpose of
exploring spatial data. The first section briefly discusses DecisionSite’s visualization
functionality. The second section describes the test goals, its design, the participants and data
used. The following section concentrates on the analysis of results, while the final section
discusses future areas of research and possible development
Designing Improved Sediment Transport Visualizations
Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects
Chromospheric polarimetry through multi-line observations of the 850 nm spectral region III: Chromospheric jets driven by twisted magnetic fields
We investigate the diagnostic potential of the spectral lines at 850 nm for
understanding the magnetism of the lower atmosphere. For that purpose, we use a
newly developed 3D simulation of a chromospheric jet to check the sensitivity
of the spectral lines to this phenomenon as well as our ability to infer the
atmospheric information through spectropolarimetric inversions of noisy
synthetic data. We start comparing the benefits of inverting the entire
spectrum at 850 nm versus only the Ca II 8542 A spectral line. We found a
better match of the input atmosphere for the former case, mainly at lower
heights. However, the results at higher layers were not accurate. After several
tests, we determined that we need to weight more the chromospheric lines than
the photospheric ones in the computation of the goodness of the fit. The new
inversion configuration allows us to obtain better fits and consequently more
accurate physical parameters. Therefore, to extract the most from multi-line
inversions, a proper set of weights needs to be estimated. Besides that, we
conclude again that the lines at 850 nm, or a similar arrangement with Ca II
8542 A plus Zeeman sensitive photospheric lines, poses the best observing
configuration for examining the thermal and magnetic properties of the lower
solar atmosphere.Comment: 14 pages, 11 figure
Visual and interactive exploration of point data
Point data, such as Unit Postcodes (UPC), can provide very detailed information at fine
scales of resolution. For instance, socio-economic attributes are commonly assigned to
UPC. Hence, they can be represented as points and observable at the postcode level.
Using UPC as a common field allows the concatenation of variables from disparate data
sources that can potentially support sophisticated spatial analysis. However, visualising
UPC in urban areas has at least three limitations. First, at small scales UPC occurrences
can be very dense making their visualisation as points difficult. On the other hand,
patterns in the associated attribute values are often hardly recognisable at large scales.
Secondly, UPC can be used as a common field to allow the concatenation of highly
multivariate data sets with an associated postcode. Finally, socio-economic variables
assigned to UPC (such as the ones used here) can be non-Normal in their distributions
as a result of a large presence of zero values and high variances which constrain their
analysis using traditional statistics.
This paper discusses a Point Visualisation Tool (PVT), a proof-of-concept system
developed to visually explore point data. Various well-known visualisation techniques
were implemented to enable their interactive and dynamic interrogation. PVT provides
multiple representations of point data to facilitate the understanding of the relations
between attributes or variables as well as their spatial characteristics. Brushing between
alternative views is used to link several representations of a single attribute, as well as
to simultaneously explore more than one variable. PVT’s functionality shows how the
use of visual techniques embedded in an interactive environment enable the exploration
of large amounts of multivariate point data
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