56,879 research outputs found
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
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
Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup
Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here
Exploration of Reaction Pathways and Chemical Transformation Networks
For the investigation of chemical reaction networks, the identification of
all relevant intermediates and elementary reactions is mandatory. Many
algorithmic approaches exist that perform explorations efficiently and
automatedly. These approaches differ in their application range, the level of
completeness of the exploration, as well as the amount of heuristics and human
intervention required. Here, we describe and compare the different approaches
based on these criteria. Future directions leveraging the strengths of chemical
heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure
Mapping Tasks to Interactions for Graph Exploration and Graph Editing on Interactive Surfaces
Graph exploration and editing are still mostly considered independently and
systems to work with are not designed for todays interactive surfaces like
smartphones, tablets or tabletops. When developing a system for those modern
devices that supports both graph exploration and graph editing, it is necessary
to 1) identify what basic tasks need to be supported, 2) what interactions can
be used, and 3) how to map these tasks and interactions. This technical report
provides a list of basic interaction tasks for graph exploration and editing as
a result of an extensive system review. Moreover, different interaction
modalities of interactive surfaces are reviewed according to their interaction
vocabulary and further degrees of freedom that can be used to make interactions
distinguishable are discussed. Beyond the scope of graph exploration and
editing, we provide an approach for finding and evaluating a mapping from tasks
to interactions, that is generally applicable. Thus, this work acts as a
guideline for developing a system for graph exploration and editing that is
specifically designed for interactive surfaces.Comment: 21 pages, minor corrections (typos etc.
Using high resolution displays for high resolution cardiac data
The ability to perform fast, accurate, high resolution visualization is fundamental
to improving our understanding of anatomical data. As the volumes of data
increase from improvements in scanning technology, the methods applied to rendering
and visualization must evolve. In this paper we address the interactive display of
data from high resolution MRI scanning of a rabbit heart and subsequent histological
imaging. We describe a visualization environment involving a tiled LCD panel
display wall and associated software which provide an interactive and intuitive user
interface.
The oView software is an OpenGL application which is written for the VRJuggler
environment. This environment abstracts displays and devices away from the
application itself, aiding portability between different systems, from desktop PCs to
multi-tiled display walls. Portability between display walls has been demonstrated
through its use on walls at both Leeds and Oxford Universities. We discuss important
factors to be considered for interactive 2D display of large 3D datasets,
including the use of intuitive input devices and level of detail aspects
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