Special Issue "Geovisual Analytics"

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A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (15 July 2012)

Special Issue Editor

Guest Editor
Dr. Brian M. Tomaszewski

Department of Information Sciences and Technologies, Rochester Institute of Technology, One Lomb Memorial Drive, Rochester, NY 14623, USA
Website | E-Mail
Interests: Geographic Information Science and Technology (GIS&T); geovisual analytics; context modeling and representation; crisis management

Special Issue Information

Dear Colleagues,

The continued proliferation of massive volumes of geographic data and information coupled with complex, multi-scale problems is necessitating the need for new analytic approaches and problem solving tools such as those offered by the field of Geovisual Analytics. The following quote taken from Tomaszewski et al. (2007:173) describes Geovisual Analytics:

Geovisual Analytics is an emerging interdisciplinary field that integrates perspectives from Visual Analytics (grounded in Information and Scientific Visualization) and Geographic Information Science (growing particularly on work in geovisualization, geospatial semantics and knowledge management, geocomputation, and spatial analysis). Geovisual Analytics tools help identify relevant geospatial information, data, and knowledge by supporting analytical process that meld innate human abilities of vision and cognition with computer-based visual interfaces that provide flexible connections to relevant data and supporting knowledge, and that are specifically designed to provide support for analytical reasoning. Often the activities that Geovisual Analytics is directed toward involve recognizing relevant information in enormous datasets that make what is relevant difficult to determine using traditional methods. Geovisual Analytics is an increasingly important tool for activities ranging from counter-terrorism and crisis management, through environmental science, to strategic business decision making.

This special issue is thus interested in reporting Geovisual Analytics research that advances understanding of following topics that include, but are not limited to:

  • Using sense making, cognition, and perception as foundations for tools that support reasoning for complex tasks
  • Addressing issues of analytical scale and the interplay between complexity and urgency that dictates and determines the scale
  • Synthesizing different types of information from different sources into unified representations to find meaning
  • Integrating views of large-scale information spaces, coordinated views of information in context, and overviews and details
  • Leveraging innate human abilities to reason about time and space
  • Evaluating the usability and utility of Geovisual Analytic systems
  • Geovisual Analytic computational methods

Geovisual Analytic application case studies and best practice submissions are also encouraged.

Brian M. Tomaszewski
Guest Editor

References:
Thomas, J. J. & Cook, K. A. 2005. Illuminating the Path: The Research and Development Agenda for Visual Analytics, Los Alametos, CA, IEEE.
Tomaszewski, B., Robinson, A. C., Weaver, C., Stryker, M. & Maceachren, A. M. Year. Geovisual Analytics and Crisis Management. In: B. VAN DE WALLE, BURGHARDT, P. & NIEUWENHUIS, C., eds. Proceedings of the 4th International Information Systems for Crisis Response and Management (ISCRAM) Conference, 2007 Delft, the Netherlands. 173-179.


Keywords

  • geovisual analytics
  • geographic information
  • geovisualization
  • information visualization
  • computational methods
  • evaluation

Published Papers (3 papers)

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Research

Open AccessArticle A Web-Based Geovisual Analytical System for Climate Studies
Future Internet 2012, 4(4), 1069-1085; doi:10.3390/fi4041069
Received: 10 October 2012 / Revised: 20 November 2012 / Accepted: 10 December 2012 / Published: 14 December 2012
Cited by 5 | PDF Full-text (2695 KB) | HTML Full-text | XML Full-text
Abstract
Climate studies involve petabytes of spatiotemporal datasets that are produced and archived at distributed computing resources. Scientists need an intuitive and convenient tool to explore the distributed spatiotemporal data. Geovisual analytical tools have the potential to provide such an intuitive and convenient method
[...] Read more.
Climate studies involve petabytes of spatiotemporal datasets that are produced and archived at distributed computing resources. Scientists need an intuitive and convenient tool to explore the distributed spatiotemporal data. Geovisual analytical tools have the potential to provide such an intuitive and convenient method for scientists to access climate data, discover the relationships between various climate parameters, and communicate the results across different research communities. However, implementing a geovisual analytical tool for complex climate data in a distributed environment poses several challenges. This paper reports our research and development of a web-based geovisual analytical system to support the analysis of climate data generated by climate model. Using the ModelE developed by the NASA Goddard Institute for Space Studies (GISS) as an example, we demonstrate that the system is able to (1) manage large volume datasets over the Internet; (2) visualize 2D/3D/4D spatiotemporal data; (3) broker various spatiotemporal statistical analyses for climate research; and (4) support interactive data analysis and knowledge discovery. This research also provides an example for managing, disseminating, and analyzing Big Data in the 21st century. Full article
(This article belongs to the Special Issue Geovisual Analytics)
Open AccessArticle Virtual Astronaut for Scientific Visualization—A Prototype for Santa Maria Crater on Mars
Future Internet 2012, 4(4), 1049-1068; doi:10.3390/fi4041049
Received: 16 July 2012 / Revised: 5 December 2012 / Accepted: 10 December 2012 / Published: 13 December 2012
Cited by 1 | PDF Full-text (4320 KB) | HTML Full-text | XML Full-text
Abstract
To support scientific visualization of multiple-mission data from Mars, the Virtual Astronaut (VA) creates an interactive virtual 3D environment built on the Unity3D Game Engine. A prototype study was conducted based on orbital and Opportunity Rover data covering Santa Maria Crater in Meridiani
[...] Read more.
To support scientific visualization of multiple-mission data from Mars, the Virtual Astronaut (VA) creates an interactive virtual 3D environment built on the Unity3D Game Engine. A prototype study was conducted based on orbital and Opportunity Rover data covering Santa Maria Crater in Meridiani Planum on Mars. The VA at Santa Maria provides dynamic visual representations of the imaging, compositional, and mineralogical information. The VA lets one navigate through the scene and provides geomorphic and geologic contexts for the rover operations. User interactions include in-situ observations visualization, feature measurement, and an animation control of rover drives. This paper covers our approach and implementation of the VA system. A brief summary of the prototype system functions and user feedback is also covered. Based on external review and comments by the science community, the prototype at Santa Maria has proven the VA to be an effective tool for virtual geovisual analysis. Full article
(This article belongs to the Special Issue Geovisual Analytics)
Open AccessArticle How Can We Study Learning with Geovisual Analytics Applied to Statistics?
Future Internet 2012, 4(1), 22-41; doi:10.3390/fi4010022
Received: 21 November 2011 / Revised: 13 December 2011 / Accepted: 19 December 2011 / Published: 30 December 2011
Cited by 1 | PDF Full-text (1431 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
It is vital to understand what kind of processes for learning that Geovisual Analytics creates, as certain activities and conditions are produced when employing Geovisual Anlytic tools in education. To understand learning processes created by Geovisual Analytics, first requires an understanding of the
[...] Read more.
It is vital to understand what kind of processes for learning that Geovisual Analytics creates, as certain activities and conditions are produced when employing Geovisual Anlytic tools in education. To understand learning processes created by Geovisual Analytics, first requires an understanding of the interactions between the technology, the workplace where the learning takes place, and learners’ specific knowledge formation. When studying these types of interaction it demands a most critical consideration from theoretical perspectives on research design and methods. This paper first discusses common, and then a more uncommon, theoretical approach used within the fields of learning with multimedia environments and Geovisual Analytics, the socio-cultural theoretical perspective. The paper next advocates this constructivist theoretical and empirical perspective when studying learning with multiple representational Geovisual Analytic tools. To illustrate, an outline of a study made within this theoretical tradition is offered. The study is conducted in an educational setting where the Open Statistics eXplorer platform is used. Discussion of our study results shows that the socio-cultural perspective has much to offer in terms of what kind of understanding can be reached in conducting this kind of studies. Therefore, we argue that empirical research to analyze how specific communities use various Geovisual Analytics to evaluate information is best positioned in a socio-cultural theoretical perspective. Full article
(This article belongs to the Special Issue Geovisual Analytics)

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