CLOSED: Geographic Data Science – Call for Papers

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Final submissions due: CLOSED
Publication date:
September/October 2017

Data science is an emerging area of work concerned with the task of extracting insight from large collections of data. Methods that scale to big data in terms of volume, variety, velocity, and veracity are of particular interest in data science. Data science methods and approaches address all stages of the transition from data to knowledge and action, including data acquisition, information extraction, aggregation and representation, data analysis, and knowledge extraction and explanation. Interactive visual interfaces support the human cognitive process by allowing analysts to look at a subject from different perspectives and at different scales and levels of detail, link diverse pieces of information, as well as direct and control the work of computational analytical tools. Visualization and visual analytics approaches play an essential role in data science.

Advances in sensor and positioning technologies in recent years have facilitated an unprecedented growth of spatially referenced data, thus leading to massive volumes of data containing complex, yet implicit spatial, temporal, and semantic interrelations that are waiting to be uncovered. Examples of big geographic data sources include GPS tracks collected from smartphones, aerial and terrestrial laser scanning, remote sensing imagery, weather data, and data streams from geosensor networks. Such data is often collected for a different purpose than the extraction of geographic information and knowledge. Nevertheless, exciting secondary uses and innovative applications of geographic knowledge discovery are now possible. Geographic analysis strongly has traditionally relied on the use of visual (mostly cartographic) representations. Yet, the properties of new data (including the volume, variety, and dynamic aspects) pose new challenges for geographic visualization and visual geoanalytics.

For this special issue, we are soliciting original contributions that combine algorithmic and visual approaches that make sense of large volumes of various types of spatial and spatiotemporal data. In particular, we are interested in case studies and applications of geographic data science methods that attempt to gain knowledge about complex phenomena. Topics of interest include but are not limited to the following:

  • Combining interactive geographic visualizations with computational analysis techniques from areas such as spatial statistics or data mining
  • Visual analytics support for spatial modeling, planning, forecasting, and decision making
  • Modeling uncertainty in spatial data and supporting uncertainty-aware analytical reasoning
  • Visual explorations and analysis of spatial (such as simulation) models and their parameter spaces
  • Support for collaborative analytical processes
  • Visual representation and communication of knowledge and models extracted through geographic analysis
  • Cognitive and perceptual aspects of visual geoanalytics
  • Infrastructures and architectures for visual analytics systems and services
  • Evaluation of visual analytics techniques and procedures for geographic data analysis

Guest Editors

Please direct any correspondence before submission to the guest editors:

  • Gennady Andrienko (gennady.andrienko@iais.fraunhofer.de), Fraunhofer Institute IAIS and City University London
  • Natalia Andrienko, Fraunhofer Institute IAIS and City University London
  • Robert Weibel, University of Zurich

Submission Guidelines

Nondepartment articles submitted to IEEE CG&A should not exceed 8,000 words, including the main text, abstract, keywords, bibliography, biographies, and table text, where a page is approximately 800 words. Articles should include no more than 10 figures or images. Each 1/4 page figure, image, and table counts for approx. 200 words. Note that all tables, images, and illustrations must be appropriately scaled and legible; larger elements should be accounted for accordingly with respect to word count. Please limit the number of references to the most relevant and ensure to delineate your work from relevant past articles in CG&A. Furthermore, avoid an excessive number of references to published work that might only be marginally relevant. Consider instead providing such pertinent background material in sidebars for non-expert readers. Visit the CG&A style and length guidelines at www.computer.org/web/peer-review/magazines. We also strongly encourage you to submit multimedia (videos, podcasts, and so on) to enhance your article. Visit the CG&A supplemental guidelines at www.computer.org/web/peer-review/magazines.

Please submit your paper using the online manuscript submission service at https://mc.manuscriptcentral.com/cs-ieee. When uploading your paper, select the appropriate special issue title under the category “Manuscript Type.” Also, include complete contact information for all authors. If you have any questions about submitting your article, contact the peer review coordinator at cga-ma@computer.org.