000 04412nam a22005775i 4500
001 978-3-642-37583-5
003 DE-He213
005 20200421111850.0
007 cr nn 008mamaa
008 130919s2013 gw | s |||| 0|eng d
020 _a9783642375835
_9978-3-642-37583-5
024 7 _a10.1007/978-3-642-37583-5
_2doi
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aUMT
_2bicssc
072 7 _aCOM021000
_2bisacsh
082 0 4 _a005.74
_223
100 1 _aAndrienko, Gennady.
_eauthor.
245 1 0 _aVisual Analytics of Movement
_h[electronic resource] /
_cby Gennady Andrienko, Natalia Andrienko, Peter Bak, Daniel Keim, Stefan Wrobel.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXVIII, 387 p. 200 illus., 178 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- Conceptual framework -- Transformations of movement data -- Visual analytics infrastructure -- Visual analytics focusing on movers -- Visual analytics focusing on spatial events -- Visual analytics focusing on space -- Visual analytics focusing on time -- Discussion and outlook.
520 _aMany important planning decisions in society and business depend on proper knowledge and a correct understanding of movement, be it in transportation, logistics, biology, or the life sciences. Today the widespread use of mobile phones and technologies like GPS and RFID provides an immense amount of data on location and movement.  What is needed are new methods of visualization and algorithmic data analysis that are tightly integrated and complement each other to allow end-users and analysts to extract useful knowledge from these extremely large data volumes. This is exactly the topic of this book. As the authors show, modern visual analytics techniques are ready to tackle the enormous challenges brought about by movement data, and the technology and software needed to exploit them are available today. The authors start by illustrating the different kinds of data available to describe movement, from individual trajectories of single objects to multiple trajectories of many objects, and then proceed to detail a conceptual framework, which provides the basis for a fundamental understanding of movement data. With this basis, they move on to more practical and technical aspects, focusing on how to transform movement data to make it more useful, and on the infrastructure necessary for performing visual analytics in practice. In so doing they demonstrate that visual analytics of movement data can yield exciting insights into the behavior of moving persons and objects, but can also lead to an understanding of the events that transpire when things move. Throughout the book, they use sample applications from various domains and illustrate the examples with graphical depictions of both the interactive displays and the analysis results. In summary, readers will benefit from this detailed description of the state of the art in visual analytics in various ways. Researchers will appreciate the scientific precision involved, software technologists will find essential information on algorithms and systems, and practitioners will profit from readily accessible examples with detailed illustrations for practical purposes.
650 0 _aComputer science.
650 0 _aDatabase management.
650 0 _aData mining.
650 0 _aPattern recognition.
650 0 _aApplication software.
650 0 _aGeographical information systems.
650 1 4 _aComputer Science.
650 2 4 _aDatabase Management.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aGeographical Information Systems/Cartography.
650 2 4 _aPattern Recognition.
650 2 4 _aComputer Appl. in Administrative Data Processing.
700 1 _aAndrienko, Natalia.
_eauthor.
700 1 _aBak, Peter.
_eauthor.
700 1 _aKeim, Daniel.
_eauthor.
700 1 _aWrobel, Stefan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642375828
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-37583-5
912 _aZDB-2-SCS
942 _cEBK
999 _c56070
_d56070