About the Thematic Network in Spatial Cognition (TNSC)


The Thematic Network in Spatial Cognition (TNSC) is suppported by the National Science Foundation's Science Across Virtual Institutes (SAVI)

What is SAVI?
"Science Across Virtual Institutes (SAVI) is a mechanism to foster interaction among scientists, engineers and educators around the globe. It is based on the knowledge that excellence in STEM (science, technology, engineering and mathematics) research and education exists in many parts of the world, and that scientific advances can be accelerated by scientists and engineers working together across international borders. Virtual institutes that connect researchers with shared interests and goals will have a great impact on solving important societal challenges."
~from the National Science Foundation website's SAVI homepage

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The Spatial Intelligence and Learning Center (SILC) is collaborating with a network of international partners in establishing a multidisciplinary Thematic Network in Spatial Cognition (TNSC). Once fully established, the TNSC would involve cooperating institutions from around the world, organized into national networks. Each national network would have a lead institution within its country. SILC, headquartered at Temple University, is serving as the organizational lead for the TNSC in the United States through 2015.  In Germany, the TNSC is currently headquartered at the University of Bremen, and also involves the Universities of Freiburg, Giessen, Münster, and Weimar. The Australian Research Network on Spatial Cognition is currently headquartered at the University of Melbourne, and the British network at the University of Leeds. The full structure potentially involves many countries and can be seen below.

The overall aim of the Thematic Network is to establish an interdisciplinary scientific field, similar to the scientific study of human language, which includes a recognized set of focal problem areas that can be described in a mutually intelligible interdisciplinary vocabulary. Spatial cognition is a diverse and far-flung field with many exciting theoretical and translational research directions ripe to be drawn together synergistically.  Spatial cognition is central to many vital human activities, including navigation and wayfinding, tool use and design, and scientific and mathematical thinking. Research on spatial cognition draws on many disciplines, including cognitive science, computer science, geography, geographic information science, neuroscience, linguistics, psychometrics, and robotics. Its findings and insights have relevance for education in science, technology, engineering and mathematics, as well as in a wide range of professional fields, including medicine and dentistry, urban planning and traffic modeling, and architecture and design. However, despite the fact that the different disciplines and research traditions address common problems, they often use different terminology and different methodologies, which can impede communication and progress. For example, the vocabulary terms of “space syntax”, which was invented as a tool for architects, are quite different from the analytic categories used by neuroscientists, who analyze place cells, head direction cells, grid cells and boundary cells. And neither system maps precisely onto the spatial ontologies discussed in computer science or geographic information science.

To address these issues, we will support

Ultimately we aim for

  • ♦ a regular conference with a society responsible for convening the conference; for the immediate future, the SFB/TR8 will plan SC14 and SILC will plan SC16—see http://sc2012.informatik.uni-freiburg.de/   for information about SC12 held in August 2012
  • ♦ a  recognized journal central to the field; we are currently working with Spatial Cognition and Computation.

2011 Spatial Network Members USA2011 Spatial Network Members worldwide

Figure 1. Spatial Network members in the United States and world-wide.

[Please, click on either graphic to see a larger image.]

TNSC Nodal Structure

Figure 2: Shows the nodal structure of the network.

[Please, click on the graphic to see a larger image.]