LEADER 04189oam 2200541 450 001 9910739460903321 005 20190911112726.0 010 $a3-642-37583-9 024 7 $a10.1007/978-3-642-37583-5 035 $a(OCoLC)859590676 035 $a(MiFhGG)GVRL6WJV 035 $a(EXLCZ)993710000000019118 100 $a20130403d2013 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aVisual analytics of movement /$fGennady Andrienko [and four others] 205 $a1st ed. 2013. 210 1$aHeidelberg [Germany] :$cSpringer,$d2013. 215 $a1 online resource (xviii, 387 pages) $cillustrations (some color) 225 0 $aGale eBooks 300 $aIncludes index. 311 0 $a3-642-37582-0 320 $aIncludes bibliographical references and index. 327 $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. 330 $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. 606 $aVisual analytics 606 $aInformation visualization 606 $aData mining 606 $aPattern perception 615 0$aVisual analytics. 615 0$aInformation visualization. 615 0$aData mining. 615 0$aPattern perception. 676 $a006.31 700 $aAndrienko$b Gennady$4aut$4http://id.loc.gov/vocabulary/relators/aut$01058322 702 $aAndrienko$b Natalia$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aBak$b Peter$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aKeim$b Daniel$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aWrobel$b Stefan$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910739460903321 996 $aVisual Analytics of Movement$93553476 997 $aUNINA