TY - JOUR
T1 - Quantifying space, understanding minds
T2 - A visual summary approach
AU - Simpson, Mark
AU - Richter, Kai Florian
AU - Wallgrün, Jan Oliver
AU - Klippel, Alexander
N1 - Publisher Copyright:
© by the author(s).
PY - 2017
Y1 - 2017
N2 - This paper presents an illustrated, validated taxonomy of research that compares spatial measures to human behavior. Spatial measures quantify the spatial characteristics of environments, such as the centrality of intersections in a street network or the accessibility of a room in a building from all the other rooms. While spatial measures have been of interest to spatial sciences, they are also of importance in the behavioral sciences for use in modeling human behavior. A high correlation between values for spatial measures and specific behaviors can provide insights into an environment's legibility, and contribute to a deeper understanding of human spatial cognition. Research in this area takes place in several domains, which makes a full understanding of existing literature difficult. To address this challenge, we adopt a visual summary approach. Literature is analyzed, and recurring topics are identified and validated with independent inter-rater agreement tasks in order to create a robust taxonomy for spatial measures and human behavior. The taxonomy is then illustrated with a visual representation that allows for at-a-glance visual access to the content of individual research papers in a corpus. A public web interface has been created that allows interested researchers to add to the database and create visual summaries for their research papers using our taxonomy.
AB - This paper presents an illustrated, validated taxonomy of research that compares spatial measures to human behavior. Spatial measures quantify the spatial characteristics of environments, such as the centrality of intersections in a street network or the accessibility of a room in a building from all the other rooms. While spatial measures have been of interest to spatial sciences, they are also of importance in the behavioral sciences for use in modeling human behavior. A high correlation between values for spatial measures and specific behaviors can provide insights into an environment's legibility, and contribute to a deeper understanding of human spatial cognition. Research in this area takes place in several domains, which makes a full understanding of existing literature difficult. To address this challenge, we adopt a visual summary approach. Literature is analyzed, and recurring topics are identified and validated with independent inter-rater agreement tasks in order to create a robust taxonomy for spatial measures and human behavior. The taxonomy is then illustrated with a visual representation that allows for at-a-glance visual access to the content of individual research papers in a corpus. A public web interface has been created that allows interested researchers to add to the database and create visual summaries for their research papers using our taxonomy.
UR - http://www.scopus.com/inward/record.url?scp=85020508778&partnerID=8YFLogxK
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U2 - 10.5311/JOSIS.2017.14.292
DO - 10.5311/JOSIS.2017.14.292
M3 - Review article
AN - SCOPUS:85020508778
SN - 1948-660X
VL - 14
SP - 95
EP - 136
JO - Journal of Spatial Information Science
JF - Journal of Spatial Information Science
IS - 2017
ER -