Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2020-02-20

AUTHORS

Matthias Kraus , Matthias Miller , Juri Buchmüller , Manuel Stein , Niklas Weiler , Daniel A. Keim , Mennatallah El-Assady

ABSTRACT

Previous research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst’s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation. More... »

PAGES

253-284

Book

TITLE

Computer Vision, Imaging and Computer Graphics Theory and Applications

ISBN

978-3-030-41589-1
978-3-030-41590-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-41590-7_11

DOI

http://dx.doi.org/10.1007/978-3-030-41590-7_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1124960819


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "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": "University of Konstanz, Konstanz, Germany", 
          "id": "http://www.grid.ac/institutes/grid.9811.1", 
          "name": [
            "University of Konstanz, Konstanz, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kraus", 
        "givenName": "Matthias", 
        "id": "sg:person.014432047307.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014432047307.80"
        ], 
        "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": "Miller", 
        "givenName": "Matthias", 
        "id": "sg:person.014754037103.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014754037103.26"
        ], 
        "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": "Buchm\u00fcller", 
        "givenName": "Juri", 
        "id": "sg:person.013425771303.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013425771303.22"
        ], 
        "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": "Stein", 
        "givenName": "Manuel", 
        "id": "sg:person.016251627170.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016251627170.54"
        ], 
        "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": "Weiler", 
        "givenName": "Niklas", 
        "id": "sg:person.07706005023.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07706005023.18"
        ], 
        "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 A.", 
        "id": "sg:person.0635776571.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635776571.01"
        ], 
        "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": "El-Assady", 
        "givenName": "Mennatallah", 
        "id": "sg:person.07473106675.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07473106675.15"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2020-02-20", 
    "datePublishedReg": "2020-02-20", 
    "description": "Abstract\nPrevious research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst\u2019s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation.", 
    "editor": [
      {
        "familyName": "Cl\u00e1udio", 
        "givenName": "Ana Paula", 
        "type": "Person"
      }, 
      {
        "familyName": "Bouatouch", 
        "givenName": "Kadi", 
        "type": "Person"
      }, 
      {
        "familyName": "Chessa", 
        "givenName": "Manuela", 
        "type": "Person"
      }, 
      {
        "familyName": "Paljic", 
        "givenName": "Alexis", 
        "type": "Person"
      }, 
      {
        "familyName": "Kerren", 
        "givenName": "Andreas", 
        "type": "Person"
      }, 
      {
        "familyName": "Hurter", 
        "givenName": "Christophe", 
        "type": "Person"
      }, 
      {
        "familyName": "Tremeau", 
        "givenName": "Alain", 
        "type": "Person"
      }, 
      {
        "familyName": "Farinella", 
        "givenName": "Giovanni Maria", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-030-41590-7_11", 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-030-41589-1", 
        "978-3-030-41590-7"
      ], 
      "name": "Computer Vision, Imaging and Computer Graphics Theory and Applications", 
      "type": "Book"
    }, 
    "keywords": [
      "visual analytics", 
      "real-world scenarios", 
      "virtual reality", 
      "data world", 
      "visualization pipeline", 
      "visual analysis pipeline", 
      "information visualization", 
      "use cases", 
      "virtual environment", 
      "real world", 
      "structured analysis", 
      "analysis pipeline", 
      "solution approach", 
      "expert feedback", 
      "analytics", 
      "analyst's attention", 
      "crime scene investigation", 
      "actual data", 
      "pipeline", 
      "visualization", 
      "scenarios", 
      "viable medium", 
      "InfoVis", 
      "reality", 
      "further contribution", 
      "scene investigation", 
      "curse", 
      "weak spots", 
      "world", 
      "analysts", 
      "subject of analysis", 
      "database", 
      "environment", 
      "feedback", 
      "previous research", 
      "applicability", 
      "crucial dimension", 
      "correspondence", 
      "inconsistencies", 
      "attention", 
      "context", 
      "data", 
      "possible benefits", 
      "research", 
      "benefits", 
      "analysis", 
      "basic equality", 
      "dimensions", 
      "gap", 
      "contribution", 
      "circumstances", 
      "medium", 
      "immersion", 
      "spots", 
      "cases", 
      "subjects", 
      "argument", 
      "equality", 
      "discrepancy", 
      "stance", 
      "investigation", 
      "approach", 
      "paper"
    ], 
    "name": "Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline", 
    "pagination": "253-284", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1124960819"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-030-41590-7_11"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-030-41590-7_11", 
      "https://app.dimensions.ai/details/publication/pub.1124960819"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-10-01T07:01", 
    "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/chapter/chapter_93.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-030-41590-7_11"
  }
]
 

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.10.1007/978-3-030-41590-7_11'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-41590-7_11'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-41590-7_11'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-41590-7_11'


 

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

203 TRIPLES      22 PREDICATES      88 URIs      80 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-030-41590-7_11 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 anzsrc-for:0806
4 schema:author N526b1872d45a447fa9cdab5e20a7c000
5 schema:datePublished 2020-02-20
6 schema:datePublishedReg 2020-02-20
7 schema:description Abstract Previous research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst’s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation.
8 schema:editor Ne41e5d8b538c4008b863e030e8aded40
9 schema:genre chapter
10 schema:isAccessibleForFree true
11 schema:isPartOf N81ade1c6c65141c98fb57cd532a868b2
12 schema:keywords InfoVis
13 actual data
14 analysis
15 analysis pipeline
16 analyst's attention
17 analysts
18 analytics
19 applicability
20 approach
21 argument
22 attention
23 basic equality
24 benefits
25 cases
26 circumstances
27 context
28 contribution
29 correspondence
30 crime scene investigation
31 crucial dimension
32 curse
33 data
34 data world
35 database
36 dimensions
37 discrepancy
38 environment
39 equality
40 expert feedback
41 feedback
42 further contribution
43 gap
44 immersion
45 inconsistencies
46 information visualization
47 investigation
48 medium
49 paper
50 pipeline
51 possible benefits
52 previous research
53 real world
54 real-world scenarios
55 reality
56 research
57 scenarios
58 scene investigation
59 solution approach
60 spots
61 stance
62 structured analysis
63 subject of analysis
64 subjects
65 use cases
66 viable medium
67 virtual environment
68 virtual reality
69 visual analysis pipeline
70 visual analytics
71 visualization
72 visualization pipeline
73 weak spots
74 world
75 schema:name Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline
76 schema:pagination 253-284
77 schema:productId N923d0fdf3d424b7f8ef2d12f5e05589d
78 Nbdf98f0fd0b84e11a032e9af6eac08bc
79 schema:publisher N6f34e58987a54ceebfacf6781509e5f7
80 schema:sameAs https://app.dimensions.ai/details/publication/pub.1124960819
81 https://doi.org/10.1007/978-3-030-41590-7_11
82 schema:sdDatePublished 2022-10-01T07:01
83 schema:sdLicense https://scigraph.springernature.com/explorer/license/
84 schema:sdPublisher N7feb2844c7e242228c12ac84d9569a7e
85 schema:url https://doi.org/10.1007/978-3-030-41590-7_11
86 sgo:license sg:explorer/license/
87 sgo:sdDataset chapters
88 rdf:type schema:Chapter
89 N022844b5eac64fad859bfc4403da3ca4 rdf:first sg:person.0635776571.01
90 rdf:rest N636552c43c004478ae67f90ab8c07458
91 N20ff4632d01d45179be9f9d3ead3f71e rdf:first sg:person.014754037103.26
92 rdf:rest Ncde001a9f33b48f383dc6addf2b7196c
93 N287c240033b44138b4ae9c083935fa44 rdf:first Nd307a921399e40eb8e6f58d876af59a0
94 rdf:rest Ncc2356ce20634fce9a3ec83235dad93f
95 N41bc286bc75245aa989808b06f15f907 schema:familyName Kerren
96 schema:givenName Andreas
97 rdf:type schema:Person
98 N4220c25180b348ec8cd2c458a8cd4c65 rdf:first sg:person.016251627170.54
99 rdf:rest Ndfdfda6882814947b085968a4c6c1f98
100 N45e068823123421eaecc2f7bd32d2082 schema:familyName Chessa
101 schema:givenName Manuela
102 rdf:type schema:Person
103 N526b1872d45a447fa9cdab5e20a7c000 rdf:first sg:person.014432047307.80
104 rdf:rest N20ff4632d01d45179be9f9d3ead3f71e
105 N636552c43c004478ae67f90ab8c07458 rdf:first sg:person.07473106675.15
106 rdf:rest rdf:nil
107 N6f09218b514e4a058615ddd2d38039f5 rdf:first Na523cdb1bef745fa98ab77a8a05a2686
108 rdf:rest N287c240033b44138b4ae9c083935fa44
109 N6f34e58987a54ceebfacf6781509e5f7 schema:name Springer Nature
110 rdf:type schema:Organisation
111 N7b10932a250c46688ad0f670a04682e1 schema:familyName Farinella
112 schema:givenName Giovanni Maria
113 rdf:type schema:Person
114 N7b25302e785248a581c875a387279bad schema:familyName Bouatouch
115 schema:givenName Kadi
116 rdf:type schema:Person
117 N7feb2844c7e242228c12ac84d9569a7e schema:name Springer Nature - SN SciGraph project
118 rdf:type schema:Organization
119 N81ade1c6c65141c98fb57cd532a868b2 schema:isbn 978-3-030-41589-1
120 978-3-030-41590-7
121 schema:name Computer Vision, Imaging and Computer Graphics Theory and Applications
122 rdf:type schema:Book
123 N8555ca32530b4f2abe63f758c97d218b rdf:first N9311ebca3cd3454cb0caba1f1dee3986
124 rdf:rest Na0f27041f47045bca608b3a4e7c4e958
125 N8b851490305a44a4ae5c1add6c375e50 schema:familyName Cláudio
126 schema:givenName Ana Paula
127 rdf:type schema:Person
128 N923d0fdf3d424b7f8ef2d12f5e05589d schema:name doi
129 schema:value 10.1007/978-3-030-41590-7_11
130 rdf:type schema:PropertyValue
131 N9311ebca3cd3454cb0caba1f1dee3986 schema:familyName Paljic
132 schema:givenName Alexis
133 rdf:type schema:Person
134 Na0f27041f47045bca608b3a4e7c4e958 rdf:first N41bc286bc75245aa989808b06f15f907
135 rdf:rest N6f09218b514e4a058615ddd2d38039f5
136 Na523cdb1bef745fa98ab77a8a05a2686 schema:familyName Hurter
137 schema:givenName Christophe
138 rdf:type schema:Person
139 Nafa907e1b9d64586ae7fa4598b6552dd rdf:first N45e068823123421eaecc2f7bd32d2082
140 rdf:rest N8555ca32530b4f2abe63f758c97d218b
141 Nbdf98f0fd0b84e11a032e9af6eac08bc schema:name dimensions_id
142 schema:value pub.1124960819
143 rdf:type schema:PropertyValue
144 Nc6779fdbac5a498ebeaab24152c474f6 rdf:first N7b25302e785248a581c875a387279bad
145 rdf:rest Nafa907e1b9d64586ae7fa4598b6552dd
146 Ncc2356ce20634fce9a3ec83235dad93f rdf:first N7b10932a250c46688ad0f670a04682e1
147 rdf:rest rdf:nil
148 Ncde001a9f33b48f383dc6addf2b7196c rdf:first sg:person.013425771303.22
149 rdf:rest N4220c25180b348ec8cd2c458a8cd4c65
150 Nd307a921399e40eb8e6f58d876af59a0 schema:familyName Tremeau
151 schema:givenName Alain
152 rdf:type schema:Person
153 Ndfdfda6882814947b085968a4c6c1f98 rdf:first sg:person.07706005023.18
154 rdf:rest N022844b5eac64fad859bfc4403da3ca4
155 Ne41e5d8b538c4008b863e030e8aded40 rdf:first N8b851490305a44a4ae5c1add6c375e50
156 rdf:rest Nc6779fdbac5a498ebeaab24152c474f6
157 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
158 schema:name Information and Computing Sciences
159 rdf:type schema:DefinedTerm
160 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
161 schema:name Artificial Intelligence and Image Processing
162 rdf:type schema:DefinedTerm
163 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
164 schema:name Information Systems
165 rdf:type schema:DefinedTerm
166 sg:person.013425771303.22 schema:affiliation grid-institutes:grid.9811.1
167 schema:familyName Buchmüller
168 schema:givenName Juri
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013425771303.22
170 rdf:type schema:Person
171 sg:person.014432047307.80 schema:affiliation grid-institutes:grid.9811.1
172 schema:familyName Kraus
173 schema:givenName Matthias
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014432047307.80
175 rdf:type schema:Person
176 sg:person.014754037103.26 schema:affiliation grid-institutes:grid.9811.1
177 schema:familyName Miller
178 schema:givenName Matthias
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014754037103.26
180 rdf:type schema:Person
181 sg:person.016251627170.54 schema:affiliation grid-institutes:grid.9811.1
182 schema:familyName Stein
183 schema:givenName Manuel
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016251627170.54
185 rdf:type schema:Person
186 sg:person.0635776571.01 schema:affiliation grid-institutes:grid.9811.1
187 schema:familyName Keim
188 schema:givenName Daniel A.
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635776571.01
190 rdf:type schema:Person
191 sg:person.07473106675.15 schema:affiliation grid-institutes:grid.9811.1
192 schema:familyName El-Assady
193 schema:givenName Mennatallah
194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07473106675.15
195 rdf:type schema:Person
196 sg:person.07706005023.18 schema:affiliation grid-institutes:grid.9811.1
197 schema:familyName Weiler
198 schema:givenName Niklas
199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07706005023.18
200 rdf:type schema:Person
201 grid-institutes:grid.9811.1 schema:alternateName University of Konstanz, Konstanz, Germany
202 schema:name University of Konstanz, Konstanz, Germany
203 rdf:type schema:Organization
 




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


...