Visual Analytics of Movement View Full Text


Ontology type: schema:Book      Open Access: True


Book Info

DATE

2013

GENRE

Monograph

AUTHORS

Gennady Andrienko , Natalia Andrienko , Peter Bak , Daniel Keim , Stefan Wrobel

PUBLISHER

Springer Nature

ABSTRACT

Many 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. More... »

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-37583-5

DOI

http://dx.doi.org/10.1007/978-3-642-37583-5

ISBN

978-3-642-37582-8 | 978-3-642-37583-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051205740


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0802", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Computation Theory and Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Fraunhofer IAIS, Sankt Augustin, Germany", 
          "id": "http://www.grid.ac/institutes/grid.469822.3", 
          "name": [
            "Fraunhofer IAIS, Sankt Augustin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Andrienko", 
        "givenName": "Gennady", 
        "id": "sg:person.0722772451.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0722772451.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fraunhofer IAIS, Sankt Augustin, Germany", 
          "id": "http://www.grid.ac/institutes/grid.469822.3", 
          "name": [
            "Fraunhofer IAIS, Sankt Augustin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Andrienko", 
        "givenName": "Natalia", 
        "id": "sg:person.015057153315.95", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015057153315.95"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "IBM Haifa Research Lab, Haifa, Israel", 
          "id": "http://www.grid.ac/institutes/grid.11447.37", 
          "name": [
            "IBM Haifa Research Lab, Haifa, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bak", 
        "givenName": "Peter", 
        "id": "sg:person.012332036023.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012332036023.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Konstanz, Konstanz, Germany", 
          "id": "http://www.grid.ac/institutes/grid.9811.1", 
          "name": [
            "University of Konstanz, Konstanz, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Keim", 
        "givenName": "Daniel", 
        "id": "sg:person.0635776571.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635776571.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fraunhofer IAIS, Sankt Augustin, Germany", 
          "id": "http://www.grid.ac/institutes/grid.469822.3", 
          "name": [
            "Fraunhofer IAIS, Sankt Augustin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wrobel", 
        "givenName": "Stefan", 
        "id": "sg:person.01133102365.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01133102365.69"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2013", 
    "datePublishedReg": "2013-01-01", 
    "description": "Many 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. \u00a0What 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.", 
    "genre": "monograph", 
    "id": "sg:pub.10.1007/978-3-642-37583-5", 
    "isAccessibleForFree": true, 
    "isbn": [
      "978-3-642-37582-8", 
      "978-3-642-37583-5"
    ], 
    "keywords": [
      "visual analytics", 
      "movement data", 
      "visual analytics techniques", 
      "algorithmic data analysis", 
      "large data volumes", 
      "software technologists", 
      "data volume", 
      "interactive display", 
      "analytics", 
      "useful knowledge", 
      "mobile phones", 
      "immense amount", 
      "sample application", 
      "single object", 
      "important planning decisions", 
      "available today", 
      "analytic techniques", 
      "objects", 
      "multiple trajectories", 
      "graphical depiction", 
      "data analysis", 
      "planning decisions", 
      "technology", 
      "essential information", 
      "enormous challenges", 
      "different kinds", 
      "accessible examples", 
      "RFID", 
      "algorithm", 
      "phones", 
      "software", 
      "technical aspects", 
      "infrastructure", 
      "individual trajectories", 
      "new method", 
      "things", 
      "visualization", 
      "widespread use", 
      "conceptual framework", 
      "logistics", 
      "today", 
      "GPS", 
      "data", 
      "framework", 
      "trajectories", 
      "analysts", 
      "business", 
      "information", 
      "example", 
      "knowledge", 
      "display", 
      "detailed illustration", 
      "practical purposes", 
      "detailed description", 
      "art", 
      "applications", 
      "challenges", 
      "decisions", 
      "researchers", 
      "precision", 
      "system", 
      "domain", 
      "topic", 
      "technique", 
      "kind", 
      "transportation", 
      "way", 
      "proper knowledge", 
      "movement", 
      "technologists", 
      "method", 
      "correct understanding", 
      "description", 
      "location", 
      "aspects", 
      "readers", 
      "authors", 
      "basis", 
      "practitioners", 
      "use", 
      "illustration", 
      "amount", 
      "analysis", 
      "purpose", 
      "persons", 
      "state", 
      "book", 
      "understanding", 
      "practice", 
      "insights", 
      "behavior", 
      "summary", 
      "exciting insights", 
      "volume", 
      "depiction", 
      "society", 
      "events", 
      "life", 
      "biology", 
      "scientific precision", 
      "fundamental understanding"
    ], 
    "name": "Visual Analytics of Movement", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1051205740"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-37583-5"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-37583-5", 
      "https://app.dimensions.ai/details/publication/pub.1051205740"
    ], 
    "sdDataset": "books", 
    "sdDatePublished": "2022-10-01T06:51", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/book/book_12.jsonl", 
    "type": "Book", 
    "url": "https://doi.org/10.1007/978-3-642-37583-5"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37583-5'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37583-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37583-5'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37583-5'


 

This table displays all metadata directly associated to this object as RDF triples.

188 TRIPLES      20 PREDICATES      126 URIs      118 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-37583-5 schema:about anzsrc-for:08
2 anzsrc-for:0802
3 anzsrc-for:0806
4 schema:author N189caf49ae7444ab964c567a58e287a4
5 schema:datePublished 2013
6 schema:datePublishedReg 2013-01-01
7 schema:description Many 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.
8 schema:genre monograph
9 schema:isAccessibleForFree true
10 schema:isbn 978-3-642-37582-8
11 978-3-642-37583-5
12 schema:keywords GPS
13 RFID
14 accessible examples
15 algorithm
16 algorithmic data analysis
17 amount
18 analysis
19 analysts
20 analytic techniques
21 analytics
22 applications
23 art
24 aspects
25 authors
26 available today
27 basis
28 behavior
29 biology
30 book
31 business
32 challenges
33 conceptual framework
34 correct understanding
35 data
36 data analysis
37 data volume
38 decisions
39 depiction
40 description
41 detailed description
42 detailed illustration
43 different kinds
44 display
45 domain
46 enormous challenges
47 essential information
48 events
49 example
50 exciting insights
51 framework
52 fundamental understanding
53 graphical depiction
54 illustration
55 immense amount
56 important planning decisions
57 individual trajectories
58 information
59 infrastructure
60 insights
61 interactive display
62 kind
63 knowledge
64 large data volumes
65 life
66 location
67 logistics
68 method
69 mobile phones
70 movement
71 movement data
72 multiple trajectories
73 new method
74 objects
75 persons
76 phones
77 planning decisions
78 practical purposes
79 practice
80 practitioners
81 precision
82 proper knowledge
83 purpose
84 readers
85 researchers
86 sample application
87 scientific precision
88 single object
89 society
90 software
91 software technologists
92 state
93 summary
94 system
95 technical aspects
96 technique
97 technologists
98 technology
99 things
100 today
101 topic
102 trajectories
103 transportation
104 understanding
105 use
106 useful knowledge
107 visual analytics
108 visual analytics techniques
109 visualization
110 volume
111 way
112 widespread use
113 schema:name Visual Analytics of Movement
114 schema:productId N03483bd2f52a49a0b7d01018b7b12234
115 N47daa092c4444406b4a5583250e6d8f2
116 schema:publisher Neb24bd7f27524d589b3ca7ad13547ad1
117 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051205740
118 https://doi.org/10.1007/978-3-642-37583-5
119 schema:sdDatePublished 2022-10-01T06:51
120 schema:sdLicense https://scigraph.springernature.com/explorer/license/
121 schema:sdPublisher N59521fc09eb048d0a32b959de3ab8867
122 schema:url https://doi.org/10.1007/978-3-642-37583-5
123 sgo:license sg:explorer/license/
124 sgo:sdDataset books
125 rdf:type schema:Book
126 N03483bd2f52a49a0b7d01018b7b12234 schema:name doi
127 schema:value 10.1007/978-3-642-37583-5
128 rdf:type schema:PropertyValue
129 N189caf49ae7444ab964c567a58e287a4 rdf:first sg:person.0722772451.05
130 rdf:rest N9975ffcd382a4a418d769fb8d98e8039
131 N3bdfab76ff6d487f81975e53603c0c91 rdf:first sg:person.01133102365.69
132 rdf:rest rdf:nil
133 N47daa092c4444406b4a5583250e6d8f2 schema:name dimensions_id
134 schema:value pub.1051205740
135 rdf:type schema:PropertyValue
136 N521c61f514234c1994e3635e45d8ba8e rdf:first sg:person.0635776571.01
137 rdf:rest N3bdfab76ff6d487f81975e53603c0c91
138 N59521fc09eb048d0a32b959de3ab8867 schema:name Springer Nature - SN SciGraph project
139 rdf:type schema:Organization
140 N6c250ac120fe47a3af0f06d0a7000ad0 rdf:first sg:person.012332036023.01
141 rdf:rest N521c61f514234c1994e3635e45d8ba8e
142 N9975ffcd382a4a418d769fb8d98e8039 rdf:first sg:person.015057153315.95
143 rdf:rest N6c250ac120fe47a3af0f06d0a7000ad0
144 Neb24bd7f27524d589b3ca7ad13547ad1 schema:name Springer Nature
145 rdf:type schema:Organisation
146 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
147 schema:name Information and Computing Sciences
148 rdf:type schema:DefinedTerm
149 anzsrc-for:0802 schema:inDefinedTermSet anzsrc-for:
150 schema:name Computation Theory and Mathematics
151 rdf:type schema:DefinedTerm
152 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
153 schema:name Information Systems
154 rdf:type schema:DefinedTerm
155 sg:person.01133102365.69 schema:affiliation grid-institutes:grid.469822.3
156 schema:familyName Wrobel
157 schema:givenName Stefan
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01133102365.69
159 rdf:type schema:Person
160 sg:person.012332036023.01 schema:affiliation grid-institutes:grid.11447.37
161 schema:familyName Bak
162 schema:givenName Peter
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012332036023.01
164 rdf:type schema:Person
165 sg:person.015057153315.95 schema:affiliation grid-institutes:grid.469822.3
166 schema:familyName Andrienko
167 schema:givenName Natalia
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015057153315.95
169 rdf:type schema:Person
170 sg:person.0635776571.01 schema:affiliation grid-institutes:grid.9811.1
171 schema:familyName Keim
172 schema:givenName Daniel
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635776571.01
174 rdf:type schema:Person
175 sg:person.0722772451.05 schema:affiliation grid-institutes:grid.469822.3
176 schema:familyName Andrienko
177 schema:givenName Gennady
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0722772451.05
179 rdf:type schema:Person
180 grid-institutes:grid.11447.37 schema:alternateName IBM Haifa Research Lab, Haifa, Israel
181 schema:name IBM Haifa Research Lab, Haifa, Israel
182 rdf:type schema:Organization
183 grid-institutes:grid.469822.3 schema:alternateName Fraunhofer IAIS, Sankt Augustin, Germany
184 schema:name Fraunhofer IAIS, Sankt Augustin, Germany
185 rdf:type schema:Organization
186 grid-institutes:grid.9811.1 schema:alternateName University of Konstanz, Konstanz, Germany
187 schema:name University of Konstanz, Konstanz, Germany
188 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...