MARC Record from harvard_bibliographic_metadata

LEADER: 02850nam a22004455a 4500
001 014277774-9
005 20150113020620.0
008 100301s2006 gw | s ||0| 0|eng d
020 $a9783540311904
020 $a9783540311904
020 $a9783540259947
024 7 $a10.1007/3-540-31190-4$2doi
035 $a(Springer)9783540311904
040 $aSpringer
050 4 $aQA76.76.A65
072 7 $aUB$2bicssc
072 7 $aCOM018000$2bisacsh
082 04 $a004$223
100 1 $aAndrienko, Natalia.$eauthor.
245 10 $aExploratory Analysis of Spatial and Temporal Data :$bA Systematic Approach /$cby Natalia Andrienko, Gennady Andrienko.
264 1 $aBerlin, Heidelberg :$bSpringer Berlin Heidelberg,$c2006.
300 $aXV, 703 p. 245 illus.$bonline resource.
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $atext file$bPDF$2rda
505 0 $aData -- Tasks -- Tools -- Principles -- Conclusion.
520 $aExploratory 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.
650 0 $aComputer science.
650 0 $aInformation storage and retrieval systems.
650 0 $aGeographical information systems.
650 14 $aComputer Science.
650 24 $aComputer Applications.
650 24 $aGeographical Information Systems/Cartography.
650 24 $aComputer Applications in Geosciences.
650 24 $aInformation Storage and Retrieval.
700 1 $aAndrienko, Gennady.$eauthor.
776 08 $iPrinted edition:$z9783540259947
988 $a20150113
906 $0VEN