7,581 research outputs found
Interactive tag maps and tag clouds for the multiscale exploration of large spatio-temporal datasets
'Tag clouds' and 'tag maps' are introduced to represent geographically referenced text. In combination, these aspatial and spatial views are used to explore a large structured spatio-temporal data set by providing overviews and filtering by text and geography. Prototypes are implemented using freely available technologies including Google Earth and Yahoo! 's Tag Map applet. The interactive tag map and tag cloud techniques and the rapid prototyping method used are informally evaluated through successes and limitations encountered. Preliminary evaluation suggests that the techniques may be useful for generating insights when visualizing large data sets containing geo-referenced text strings. The rapid prototyping approach enabled the technique to be developed and evaluated, leading to geovisualization through which a number of ideas were generated. Limitations of this approach are reflected upon. Tag placement, generalisation and prominence at different scales are issues which have come to light in this study that warrant further work
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies
Grid is an infrastructure that involves the integrated and collaborative use
of computers, networks, databases and scientific instruments owned and managed
by multiple organizations. Grid applications often involve large amounts of
data and/or computing resources that require secure resource sharing across
organizational boundaries. This makes Grid application management and
deployment a complex undertaking. Grid middlewares provide users with seamless
computing ability and uniform access to resources in the heterogeneous Grid
environment. Several software toolkits and systems have been developed, most of
which are results of academic research projects, all over the world. This
chapter will focus on four of these middlewares--UNICORE, Globus, Legion and
Gridbus. It also presents our implementation of a resource broker for UNICORE
as this functionality was not supported in it. A comparison of these systems on
the basis of the architecture, implementation model and several other features
is included.Comment: 19 pages, 10 figure
Collaborative geographic visualization
DissertaçaÌo apresentada na Faculdade de CiĂȘncias e Tecnologia da Universidade Nova de
Lisboa para a obtençaÌo do grau de Mestre em Engenharia do Ambiente, perfil GestĂŁo e
Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative
visualization purposes.
Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment
Dynamic low-level context for the detection of mild traumatic brain injury.
Mild traumatic brain injury (mTBI) appears as low contrast lesions in magnetic resonance (MR) imaging. Standard automated detection approaches cannot detect the subtle changes caused by the lesions. The use of context has become integral for the detection of low contrast objects in images. Context is any information that can be used for object detection but is not directly due to the physical appearance of an object in an image. In this paper, new low-level static and dynamic context features are proposed and integrated into a discriminative voxel-level classifier to improve the detection of mTBI lesions. Visual features, including multiple texture measures, are used to give an initial estimate of a lesion. From the initial estimate novel proximity and directional distance, contextual features are calculated and used as features for another classifier. This feature takes advantage of spatial information given by the initial lesion estimate using only the visual features. Dynamic context is captured by the proposed posterior marginal edge distance context feature, which measures the distance from a hard estimate of the lesion at a previous time point. The approach is validated on a temporal mTBI rat model dataset and shown to have improved dice score and convergence compared to other state-of-the-art approaches. Analysis of feature importance and versatility of the approach on other datasets are also provided
Conceptual design framework for information visualization to support multidimensional datasets in higher education institutions
Information Visualization (InfoVis) enjoys diverse adoption and applicability because of its strength in solving the problem of information overload inherent in institutional data. Policy and decision makers of higher education institutions (HEIs)
are also experiencing information overload while interacting with studentsâ data, because of its multidimensionality. This constraints decision making processes, and therefore requires a domain-specific InfoVis conceptual design framework which
will birth the domainâs InfoVis tool. This study therefore aims to design HEI Studentsâ data-focused InfoVis (HSDI) conceptual design framework which
addresses the content delivery techniques and the systematic processes in actualizing the domain specific InfoVis. The study involved four phases: 1) a usersâ study to investigate, elicit and prioritize the studentsâ data-related explicit knowledge preferences of HEI domain policy. The corresponding studentsâ data dimensions are then categorised, 2) exploratory study through content analysis of InfoVis design literatures, and subsequent mapping with findings from the usersâ study, to propose the appropriate visualization, interaction and distortion techniques for delivering the domainâs explicit knowledge preferences, 3) conceptual development of the design framework which integrates the techniquesâ model with its design processâas identified from adaptation of software engineering and InfoVis design models, 4) evaluation of the proposed framework through expert review, prototyping, heuristics evaluation, and usersâ experience evaluation. For an InfoVis that will appropriately
present and represent the domain explicit knowledge preferences, support the studentsâ data multidimensionality and the decision making processes, the study found that: 1) mouse-on, mouse-on-click, mouse on-drag, drop down menu, push
button, check boxes, and dynamics cursor hinting are the appropriate interaction techniques,
2) zooming, overview with details, scrolling, and exploration are the appropriate distortion techniques, and 3) line chart, scatter plot, map view, bar chart and pie chart are the appropriate visualization techniques. The theoretical support to the proposed framework suggests that dictates of preattentive processing theory, cognitive-fit theory, and normative and descriptive theories must be followed for InfoVis to aid perception, cognition and decision making respectively. This study contributes to the area of InfoVis, data-driven decision making process, and HEI studentsâ data usage process
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