Special issue introduction: Spatial approaches to information search

Searching for information is a ubiquitous activity, performed in a variety of contexts and supported by rapidly evolving technologies. As a process, information search often has a spatial aspect: spatial metaphors help users refer to abstract contents, and geo-referenced information grounds entities in physical space. Although information search is a major research topic in computer science, GIScience and cognitive psychology, this intrinsic spatiality has not received enough attention. This article reviews research opportunities at the crossroad of three research strands, which are (1) computational, (2) geospatial, and (3) cognitive. The articles in this special issue focus on interface design for spatio-temporal information, on the search for qualitative spatial configurations, and on a big-data analysis of the spatial relation “near”.

[1]  N. Foo Conceptual Spaces—The Geometry of Thought , 2022 .

[2]  Ross Purves,et al.  Mining nearness relations from an n-grams Web corpus in geographical space , 2016, Spatial Cogn. Comput..

[3]  Werner Kuhn,et al.  Spatial discovery and the research library , 2016, Trans. GIS.

[4]  Peter Norvig,et al.  Artificial intelligence - a modern approach, 2nd Edition , 2003, Prentice Hall series in artificial intelligence.

[5]  Vanessa Murdock,et al.  Dynamic location models , 2014, SIGIR.

[6]  Heidelinde Hobel,et al.  Qualitative Spatial Configuration Search , 2016, Spatial Cogn. Comput..

[7]  Sara Irina Fabrikant,et al.  How does GIScience support spatio-temporal information search in the humanities? , 2016, Spatial Cogn. Comput..

[8]  Mary Hegarty,et al.  Spatial Search, Final Report , 2015 .

[9]  Christos Papadimitriou,et al.  Algorithms, complexity, and the sciences , 2014, Proceedings of the National Academy of Sciences.

[10]  Southern District of New York 14 November 2013 – Case No. 1 Decision of the U.S. District Court “Google Books” , 2014 .

[11]  May Yuan,et al.  Use of a Three‐Domain Repesentation to Enhance GIS Support for Complex Spatiotemporal Queries , 1999, Trans. GIS.

[12]  Thomas T. Hills,et al.  Cognitive search : evolution, algorithms, and the brain , 2012 .

[13]  Pamela Effrein Sandstrom,et al.  Information Foraging Theory: Adaptive Interaction with Information , 2010, J. Assoc. Inf. Sci. Technol..

[14]  Miguel P Eckstein,et al.  Visual search: a retrospective. , 2011, Journal of vision.

[15]  Gerhard Weikum,et al.  YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract , 2013, IJCAI.

[16]  Werner Kuhn,et al.  Core concepts of spatial information for transdisciplinary research , 2012, Int. J. Geogr. Inf. Sci..

[17]  Paul G. Brown,et al.  Overview of sciDB: large scale array storage, processing and analysis , 2010, SIGMOD Conference.

[18]  Krzysztof Janowicz,et al.  Linked Data - A Paradigm Shift for Geographic Information Science , 2014, GIScience.

[19]  Christopher B. Jones,et al.  Geographical information retrieval , 2008, Int. J. Geogr. Inf. Sci..

[20]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[21]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[22]  Björn-Olav Dozo,et al.  Quantitative Analysis of Culture Using Millions of Digitized Books , 2010 .

[23]  Paul P. Maglio,et al.  Spatial Metaphors of Web Use , 2014, Spatial Cogn. Comput..