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Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
 
 
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Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach [Hardcover]

Natalia Andrienko (Author), Gennady Andrienko (Author)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

3540259945 978-3540259947 December 21, 2005 1
Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. As something relevant is detected in data, new questions arise, causing specific parts to be viewed in more detail. So EDA has a significant appeal: it involves hypothesis generation rather than mere hypothesis testing. The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular. They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks. This typology is then applied to the description of existing approaches and technologies, resulting not just in recommendations for choosing methods but in a set of generic procedures for data exploration. Professionals practicing analysis will profit from tested solutions – illustrated in many examples – for reuse in the catalogue of techniques presented. Students and researchers will appreciate the detailed description and classification of exploration techniques, which are not limited to spatial data only. In addition, the general principles and approaches described will be useful for designers of new methods for EDA.

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Editorial Reviews

Review

"This book has the potential to become the authoritative reference on exploratory data analysis." Ian Bishop, Director of the Centre for Geographic Information Systems and Modelling, University of Melbourne, Australia

About the Author

  The three authors are affiliated with the Fraunhofer AIS (Institute for Autonomous Intelligent Systems), department SPADE (Spatial Decision Support; http://www.ais.fraunhofer.de/SPADE/)   Dr. Natalia Andrienko and Dr. Gennady Andrienko are research and technology managers of the SPADE team. They received their Master degrees in Computer Science from the Kiev State University in 1985 and 1986, respectively, and Ph.D. equivalents in Computer Science from Moscow State University in 1992 and 1993, respectively. They worked on knowledge-based systems research at the Mathematics Institute of the Moldavian Academy of Sciences (Kishinev, Moldova), then at the Institute on Mathematical Problems of Biology of the Russian Academy of Sciences (Pushchino Research Center, Russia). Since 1997, Drs. Andrienko have research positions at GMD (since 2001 united with the Fraunhofer Gesellschaft). They have been instrumental in numerous international R&D projects, including EU-funded projects CommonGIS, SPIN!, and GIMMI. They are authors of more than 100 refereed papers that have been published in international journals, books, and conference proceedings. They are active members of two commissions of the International Cartographic Association: Commission on Visualization and Virtual Reality and Commission on Maps and the Internet. Their research interests and experiences are: exploratory analysis of spatial and temporal data; interactive and dynamic computer graphics for data analysis and decision making, in particular, maps; automated knowledge-based cartographic visualisation.   Dr. Hans Voss is general manager of the SPADE team. He received his Diploma in Computer Science from Bonn University in 1981, and his Research Doctorate in Computer Science from University of Kaiserslautern in 1986. Since 1986 he is working at GMD (now Fraunhofer Institute AIS), Sankt Augustin, Germany. He was head of projects on real-time expert systems, on the product development of an expert system workbench Babylon, and on knowledge engineering in the context of diagnostic expert systems. From 1992 until 1998 he was head of the research area on Cooperative Design (about twenty researchers). He was coordinator of the EU-funded projects GeoMed-F and CommonGIS. In 1997, he co-founded the GMD spin-off company Dialogis GmbH, and acted as co-director during the first two years of its functioning. He is particularly interested in the integration of various technologies in order to support cooperative/competitive spatio-temporal planning and decision-making.

Product Details

  • Hardcover: 703 pages
  • Publisher: Springer; 1 edition (December 21, 2005)
  • Language: English
  • ISBN-10: 3540259945
  • ISBN-13: 978-3540259947
  • Product Dimensions: 9.5 x 6.3 x 1.7 inches
  • Shipping Weight: 2.8 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #2,429,854 in Books (See Top 100 in Books)

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3 of 4 people found the following review helpful:
5.0 out of 5 stars This is one of the best book I ever read on data analysis, June 14, 2006
By 
raj (State College, PA) - See all my reviews
This review is from: Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach (Hardcover)
Andrienkos' take a functional view of data and based on two components of data build a functional taxonomy of data analysis tasks. The authors have done a excellent job and provided lot of examples to support their arguments. The book is worth buying. Though I don't own one (My advisor is very generous to lend his copy), I definitely would like to buy one.
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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
synoptic tasks, aspectual behaviours, two referrers, display manipulation tools, entire reference set, local temporal behaviours, pattern search tasks, unmet visits, whole reference set, maximum bar height, dynamic query tools, behaviour slices, retinal variables, single numeric attribute, other referrer, second referrer, treemap display, visualisation principles, crime dataset, minimum attribute value, preparatory school education, overlaid representation, aspectual patterns, time graph display, visual comparison technique
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Lake Victoria, Random House, Principles of Selection, Time Wheel, Mondim de Basto, Information Visualization, Sao Joao da Pesqueira, Attribute Explorer, Sohn von Prinzessin, District of Columbia, Jacques Bertin, Ben Shneiderman, Information Seeking Mantra, John Tukey, New Mexico, References Characteristics Fig, Visualisation Display, Computer Society Press, Rudolf Arnheim, San Francisco, Association of American Geographers, Data Tool, Lecture Notes, Morgan Kaufmann
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