Visualization and Visual Analysis of Ensemble Data: A Survey

Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing visualization needs from a variety of disciplines. From the data analysis point of view, it can be observed that many ensemble visualization works fo...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on visualization and computer graphics Vol. 25; no. 9; pp. 2853 - 2872
Main Authors Wang, Junpeng, Hazarika, Subhashis, Li, Cheng, Shen, Han-Wei
Format Journal Article
LanguageEnglish
Published United States IEEE 01.09.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing visualization needs from a variety of disciplines. From the data analysis point of view, it can be observed that many ensemble visualization works focus on the same facet of ensemble data, use similar data aggregation or uncertainty modeling methods. However, the lack of reflections on those essential commonalities and a systematic overview of those works prevents visualization researchers from effectively identifying new or unsolved problems and planning for further developments. In this paper, we take a holistic perspective and provide a survey of ensemble visualization. Specifically, we study ensemble visualization works in the recent decade, and categorize them from two perspectives: (1) their proposed visualization techniques; and (2) their involved analytic tasks. For the first perspective, we focus on elaborating how conventional visualization techniques (e.g., surface, volume visualization techniques) have been adapted to ensemble data; for the second perspective, we emphasize how analytic tasks (e.g., comparison, clustering) have been performed differently for ensemble data. From the study of ensemble visualization literature, we have also identified several research trends, as well as some future research opportunities.
AbstractList Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing visualization needs from a variety of disciplines. From the data analysis point of view, it can be observed that many ensemble visualization works focus on the same facet of ensemble data, use similar data aggregation or uncertainty modeling methods. However, the lack of reflections on those essential commonalities and a systematic overview of those works prevents visualization researchers from effectively identifying new or unsolved problems and planning for further developments. In this paper, we take a holistic perspective and provide a survey of ensemble visualization. Specifically, we study ensemble visualization works in the recent decade, and categorize them from two perspectives: (1) their proposed visualization techniques; and (2) their involved analytic tasks. For the first perspective, we focus on elaborating how conventional visualization techniques (e.g., surface, volume visualization techniques) have been adapted to ensemble data; for the second perspective, we emphasize how analytic tasks (e.g., comparison, clustering) have been performed differently for ensemble data. From the study of ensemble visualization literature, we have also identified several research trends, as well as some future research opportunities.
Not provided.
Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing visualization needs from a variety of disciplines. From the data analysis point of view, it can be observed that many ensemble visualization works focus on the same facet of ensemble data, use similar data aggregation or uncertainty modeling methods. However, the lack of reflections on those essential commonalities and a systematic overview of those works prevents visualization researchers from effectively identifying new or unsolved problems and planning for further developments. In this paper, we take a holistic perspective and provide a survey of ensemble visualization. Specifically, we study ensemble visualization works in the recent decade, and categorize them from two perspectives: (1) their proposed visualization techniques; and (2) their involved analytic tasks. For the first perspective, we focus on elaborating how conventional visualization techniques (e.g., surface, volume visualization techniques) have been adapted to ensemble data; for the second perspective, we emphasize how analytic tasks (e.g., comparison, clustering) have been performed differently for ensemble data. From the study of ensemble visualization literature, we have also identified several research trends, as well as some future research opportunities.Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing visualization needs from a variety of disciplines. From the data analysis point of view, it can be observed that many ensemble visualization works focus on the same facet of ensemble data, use similar data aggregation or uncertainty modeling methods. However, the lack of reflections on those essential commonalities and a systematic overview of those works prevents visualization researchers from effectively identifying new or unsolved problems and planning for further developments. In this paper, we take a holistic perspective and provide a survey of ensemble visualization. Specifically, we study ensemble visualization works in the recent decade, and categorize them from two perspectives: (1) their proposed visualization techniques; and (2) their involved analytic tasks. For the first perspective, we focus on elaborating how conventional visualization techniques (e.g., surface, volume visualization techniques) have been adapted to ensemble data; for the second perspective, we emphasize how analytic tasks (e.g., comparison, clustering) have been performed differently for ensemble data. From the study of ensemble visualization literature, we have also identified several research trends, as well as some future research opportunities.
Author Li, Cheng
Shen, Han-Wei
Wang, Junpeng
Hazarika, Subhashis
Author_xml – sequence: 1
  givenname: Junpeng
  orcidid: 0000-0002-1130-9914
  surname: Wang
  fullname: Wang, Junpeng
  email: wang.7665@osu.edu
  organization: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
– sequence: 2
  givenname: Subhashis
  orcidid: 0000-0003-0575-9318
  surname: Hazarika
  fullname: Hazarika, Subhashis
  email: hazarika.3@osu.edu
  organization: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
– sequence: 3
  givenname: Cheng
  orcidid: 0000-0002-3114-9399
  surname: Li
  fullname: Li, Cheng
  email: li.4076@osu.edu
  organization: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
– sequence: 4
  givenname: Han-Wei
  surname: Shen
  fullname: Shen, Han-Wei
  email: shen.94@osu.edu
  organization: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29994615$$D View this record in MEDLINE/PubMed
https://www.osti.gov/biblio/1610947$$D View this record in Osti.gov
BookMark eNp9kU1v1DAQhi1URD_gByAkFNELlyzjj_ij4rJaSkGqxIHSq-U4E-Eqa5c4QVp-fb1ky6EHTjMaPe9o5n1PyVFMEQl5TWFFKZgPN7ebqxUDqldMN1wx-oycUCNoDQ3Io9KDUjWTTB6T05zvAKgQ2rwgx8wYIyRtTsjH25BnN4Q_bgopVi521TKp1tENuxxylfrqMmbctgNWn9zkLqp19X0ef-PuJXneuyHjq0M9Iz8-X95svtTX366-btbXtedKTjXnqFrlsHW-ZcJ4yVXXom6Nd5xpD7L3Al3TI1JohEHeo1Qd9wCCdcg5PyPvlr0pT8FmHyb0P32KEf1kqSxWCFWg9wt0P6ZfM-bJbkP2OAwuYpqzZSA1FyAbKOj5E_QuzWP5t1BMasGF5qxQbw_U3G6xs_dj2LpxZx_NK4BaAD-mnEfsbbnsr4_T6MJgKdh9THYfk93HZA8xFSV9onxc_j_Nm0UTEPEfrwU0xTP-AAynmvc
CODEN ITVGEA
CitedBy_id crossref_primary_10_1016_j_cag_2022_10_008
crossref_primary_10_1109_TVCG_2021_3140153
crossref_primary_10_1016_j_bdr_2021_100251
crossref_primary_10_1016_j_jbi_2021_103941
crossref_primary_10_1177_14738716221147289
crossref_primary_10_3389_fbinf_2022_793819
crossref_primary_10_1109_TVCG_2021_3061925
crossref_primary_10_1016_j_cag_2021_04_010
crossref_primary_10_1111_cgf_14333
crossref_primary_10_3390_ijgi9010019
crossref_primary_10_1016_j_cag_2022_01_007
crossref_primary_10_3390_a18010039
crossref_primary_10_1111_cgf_14537
crossref_primary_10_1109_MCG_2022_3176325
crossref_primary_10_3390_su151914340
crossref_primary_10_1109_TVCG_2022_3209379
crossref_primary_10_1111_cgf_13806
crossref_primary_10_1007_s12650_019_00608_y
crossref_primary_10_1016_j_energy_2022_125939
crossref_primary_10_1109_TVCG_2020_2994954
crossref_primary_10_1109_TVCG_2024_3357065
crossref_primary_10_1109_TVCG_2024_3350076
crossref_primary_10_1016_j_visinf_2025_02_001
crossref_primary_10_1016_j_cag_2022_04_005
crossref_primary_10_1177_14738716221126992
crossref_primary_10_1109_TVCG_2022_3189094
crossref_primary_10_1111_cgf_14386
crossref_primary_10_1016_j_visinf_2022_10_003
crossref_primary_10_1016_j_visinf_2022_10_002
crossref_primary_10_1109_TVCG_2023_3326855
crossref_primary_10_1111_cgf_14785
crossref_primary_10_1111_cgf_14544
crossref_primary_10_1109_TVCG_2024_3456393
crossref_primary_10_1111_cgf_14029
crossref_primary_10_1111_cgf_14548
crossref_primary_10_1002_itl2_284
crossref_primary_10_1109_TVCG_2022_3209464
crossref_primary_10_1098_rsta_2019_0431
crossref_primary_10_1007_s11242_023_02019_y
crossref_primary_10_1109_TVCG_2020_3030377
crossref_primary_10_1109_MCG_2022_3169554
crossref_primary_10_1080_17538947_2024_2431624
crossref_primary_10_1007_s00287_019_01222_w
crossref_primary_10_1109_TVCG_2022_3165345
crossref_primary_10_1016_j_cag_2023_06_006
crossref_primary_10_1109_TBDATA_2021_3092174
crossref_primary_10_1111_cgf_15084
crossref_primary_10_1007_s00371_024_03435_x
crossref_primary_10_1111_cgf_15083
crossref_primary_10_1109_TVCG_2020_3022359
crossref_primary_10_1111_cgf_14432
crossref_primary_10_1111_cgf_13985
crossref_primary_10_1109_TVCG_2022_3180899
crossref_primary_10_2139_ssrn_4188415
crossref_primary_10_1109_TVCG_2022_3209356
crossref_primary_10_1016_j_cag_2020_07_001
crossref_primary_10_1016_j_gvc_2020_200014
crossref_primary_10_1109_TVCG_2021_3101418
crossref_primary_10_3390_fire7070227
crossref_primary_10_1007_s12650_019_00612_2
crossref_primary_10_1007_s12650_024_00999_7
crossref_primary_10_5194_gmd_16_4617_2023
crossref_primary_10_1109_TBDATA_2023_3324482
crossref_primary_10_1016_j_epidem_2022_100574
crossref_primary_10_1109_TVCG_2024_3456338
crossref_primary_10_1007_s12650_021_00755_1
crossref_primary_10_1002_met_1916
crossref_primary_10_1109_ACCESS_2023_3286304
Cites_doi 10.1109/TVCG.2016.2607204
10.1109/VISUAL.2001.964550
10.1109/TVCG.2014.2346744
10.1111/j.1467-8659.2009.01677.x
10.1109/TVCG.2010.190
10.1109/PACIFICVIS.2016.7465251
10.1145/1838544.1838551
10.1109/TVCG.2010.20
10.1109/SC.2014.87
10.1109/TVCG.2016.2598830
10.1109/TVCG.2013.147
10.1109/TVCG.2015.2467198
10.1007/s003710050111
10.1109/LDAV.2015.7348068
10.1109/TVCG.2013.141
10.1111/cgf.12100
10.1111/cgf.12359
10.1111/j.1467-8659.2012.03112.x
10.1109/PacificVis.2012.6183556
10.1615/Int.J.UncertaintyQuantification.2012003966
10.1007/978-1-4471-6497-5_1
10.1145/637357.637361
10.1109/ICDMW.2009.55
10.1109/TVCG.2014.2346455
10.1111/j.1467-8659.2012.03096.x
10.1109/TVCG.2014.2346448
10.1111/cgf.12390
10.1109/TVCG.2009.155
10.1109/TVCG.2010.111
10.1109/TVCG.2010.181
10.1109/PACIFICVIS.2016.7465271
10.1145/2818517.2818531
10.1111/j.1467-8659.2011.01942.x
10.1111/cgf.12653
10.1109/TVCG.2016.2534560
10.1109/MCG.2005.71
10.1109/VAST.2015.7347635
10.1111/j.1467-8659.2011.01944.x
10.1109/TVCG.2015.2507569
10.1109/TVCG.2017.2745178
10.1109/VAST.2015.7347634
10.1109/MCG.2010.55
10.1109/LDAV.2011.6092313
10.1109/TVCG.2015.2410278
10.1109/PacificVis.2012.6183591
10.1109/VISUAL.2003.1250412
10.1109/TVCG.2013.144
10.1109/TVCG.2017.2744099
10.1109/PACIFICVIS.2016.7465272
10.1109/TVCG.2015.2507592
10.2481/dsj.3.153
10.1093/oso/9780198524847.001.0001
10.1016/S0097-8493(02)00055-9
10.1111/cgf.12649
10.1007/BF00547132
10.1177/1473871611416549
10.1109/TVCG.2006.76
10.1109/TVCG.2015.2498554
10.1109/TVCG.2013.92
10.3354/cr01213
10.1126/science.1115255
10.1109/TVCG.2016.2598868
10.1111/j.1467-8659.2012.03095.x
10.1017/S0022112095000462
10.1109/TVCG.2017.2743989
10.1109/TVCG.2011.203
10.1007/s12650-016-0388-0
10.1109/TVCG.2004.39
10.1007/s00791-002-0079-3
10.1109/PACIFICVIS.2016.7465256
10.1109/TVCG.2013.143
10.1109/PACIFICVIS.2011.5742374
10.1109/TVCG.2012.110
10.1109/MCG.2014.52
10.1109/WSC.2007.4419664
10.1109/TVCG.2016.2598870
10.1615/Int.J.UncertaintyQuantification.2012003934
10.1109/PACIFICVIS.2017.8031589
10.1088/1742-6596/180/1/012089
10.1109/MCG.2015.70
10.1109/TIP.2003.819861
10.1109/TVCG.2016.2598869
10.1111/j.1467-8659.2012.03097.x
10.1109/TVCG.2015.2467204
10.1109/PACIFICVIS.2017.8031586
10.1109/TVCG.2013.208
10.1109/TVCG.2014.2346755
10.1109/SciVis.2015.7429487
10.1109/TVCG.2014.2307892
10.1109/TVCG.2015.2467958
10.1109/PACIFICVIS.2017.8031590
10.1109/TVCG.2010.247
10.1109/TVCG.2014.2346321
10.1109/TVCG.2016.2637333
10.1109/TVCG.2013.138
10.1109/TVCG.2015.2468093
10.1111/cgf.12898
10.1111/j.1467-8659.2009.01604.x
10.1109/TVCG.2010.171
10.1109/VIZSEC.2015.7312766
10.1007/s00357-003-0004-6
10.1109/MCG.2003.1231171
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019
CorporateAuthor The Ohio State Univ., Columbus, OH (United States)
CorporateAuthor_xml – name: The Ohio State Univ., Columbus, OH (United States)
DBID 97E
RIA
RIE
AAYXX
CITATION
NPM
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
7X8
OTOTI
DOI 10.1109/TVCG.2018.2853721
DatabaseName IEEE Xplore (IEEE)
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
PubMed
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
MEDLINE - Academic
OSTI.GOV
DatabaseTitle CrossRef
PubMed
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
MEDLINE - Academic
DatabaseTitleList
PubMed
Technology Research Database

MEDLINE - Academic
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
EISSN 1941-0506
EndPage 2872
ExternalDocumentID 1610947
29994615
10_1109_TVCG_2018_2853721
8405549
Genre orig-research
Research Support, U.S. Gov't, Non-P.H.S
Journal Article
GrantInformation_xml – fundername: Los Alamos National Laboratory
  grantid: 47145
  funderid: 10.13039/100008902
– fundername: U.S. Department of Energy
  grantid: DE-SC0007444; DE-DC0012495
  funderid: 10.13039/100000015
– fundername: UT-Battelle LLC
  grantid: 4000159447
– fundername: NSF
  grantid: IIS-1250752; IIS-1065025
GroupedDBID ---
-~X
.DC
0R~
29I
4.4
53G
5GY
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACIWK
AENEX
AGQYO
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
EJD
F5P
HZ~
IEDLZ
IFIPE
IPLJI
JAVBF
LAI
M43
O9-
OCL
P2P
PQQKQ
RIA
RIE
RNS
TN5
AAYXX
CITATION
5VS
AETIX
AGSQL
AI.
AIBXA
ALLEH
H~9
IFJZH
NPM
RIG
RNI
RZB
VH1
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
7X8
OTOTI
PQEST
RIC
ID FETCH-LOGICAL-c376t-33e7b7aebacb249c637dbe8b9ca328c06fc4ea5fee10549e3fe67d3c0042de333
IEDL.DBID RIE
ISSN 1077-2626
1941-0506
IngestDate Fri May 19 01:10:19 EDT 2023
Fri Jul 11 06:35:40 EDT 2025
Sun Jun 29 13:35:54 EDT 2025
Mon Jul 21 06:00:03 EDT 2025
Tue Jul 01 03:58:52 EDT 2025
Thu Apr 24 22:54:51 EDT 2025
Wed Aug 27 02:54:35 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 9
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-037
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c376t-33e7b7aebacb249c637dbe8b9ca328c06fc4ea5fee10549e3fe67d3c0042de333
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
SC0007444
USDOE Office of Science (SC)
ORCID 0000-0002-3114-9399
0000-0002-1130-9914
0000-0003-0575-9318
0000000305759318
0000000231149399
0000000211309914
PMID 29994615
PQID 2268434832
PQPubID 75741
PageCount 20
ParticipantIDs crossref_citationtrail_10_1109_TVCG_2018_2853721
proquest_journals_2268434832
ieee_primary_8405549
osti_scitechconnect_1610947
pubmed_primary_29994615
proquest_miscellaneous_2068340650
crossref_primary_10_1109_TVCG_2018_2853721
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2019-09-01
PublicationDateYYYYMMDD 2019-09-01
PublicationDate_xml – month: 09
  year: 2019
  text: 2019-09-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: New York
PublicationTitle IEEE transactions on visualization and computer graphics
PublicationTitleAbbrev TVCG
PublicationTitleAlternate IEEE Trans Vis Comput Graph
PublicationYear 2019
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref57
ref59
ref58
ref53
ref52
ref55
(ref56) 2017
hunt (ref94) 1988
ref51
ref50
ref46
ref45
ref41
ref44
ref43
senin (ref88) 2008
ref49
ref8
ref7
yu (ref120) 2010; 30
matkovi? (ref54) 2010
ref4
ref6
phadke (ref47) 2012
ref5
ester (ref86) 1996
ref100
ref101
ref40
ref35
ref34
ref37
ref36
ref31
ref30
ref33
ref32
liu (ref9) 2012
ref39
mahalanobis (ref90) 1936
ref38
otto (ref115) 2011
diggle (ref3) 2002
jarema (ref21) 2016; 24
ref24
ref23
cha (ref89) 2007; 1
ref26
ref25
ref20
ref28
ref27
ref29
ref13
ref12
ref15
ref14
ref97
ref96
ref99
ref11
ref98
ref10
matkovi? (ref22) 2009; 15
ref17
ref16
ref19
ref18
ref93
ref92
ref95
höllt (ref48) 2013
ref91
bishop (ref84) 2006
ref85
ref87
pfaffelmoser (ref66) 2013
höllt (ref103) 2013
ref82
(ref42) 2017
ref81
ref83
ref80
ref79
ref108
ref78
ref109
ref106
ref75
ref104
ref74
ref105
ref77
ref102
ref76
ref2
ref1
alabi (ref73) 2012
ref71
ref111
ref70
ref112
ref72
ref68
bürger (ref110) 2012
ref119
ref67
ref117
ref69
guo (ref107) 2013; 19
ref118
ref64
ref63
ref116
ref113
ref65
ref114
ref60
ref62
ref61
References_xml – ident: ref101
  doi: 10.1109/TVCG.2016.2607204
– ident: ref105
  doi: 10.1109/VISUAL.2001.964550
– ident: ref117
  doi: 10.1109/TVCG.2014.2346744
– start-page: 73
  year: 2012
  ident: ref9
  article-title: Gaussian mixture model based volume visualization
  publication-title: Proc IEEE Symp Large Data Anal Vis
– ident: ref85
  doi: 10.1111/j.1467-8659.2009.01677.x
– ident: ref14
  doi: 10.1109/TVCG.2010.190
– ident: ref19
  doi: 10.1109/PACIFICVIS.2016.7465251
– ident: ref57
  doi: 10.1145/1838544.1838551
– ident: ref113
  doi: 10.1109/TVCG.2010.20
– ident: ref67
  doi: 10.1109/SC.2014.87
– ident: ref25
  doi: 10.1109/TVCG.2016.2598830
– ident: ref99
  doi: 10.1109/TVCG.2013.147
– ident: ref29
  doi: 10.1109/TVCG.2015.2467198
– year: 2017
  ident: ref42
  article-title: National hurricane center, uncertainty cone.
– ident: ref28
  doi: 10.1007/s003710050111
– ident: ref55
  doi: 10.1109/LDAV.2015.7348068
– ident: ref49
  doi: 10.1109/TVCG.2013.141
– ident: ref69
  doi: 10.1111/cgf.12100
– start-page: 185
  year: 2013
  ident: ref48
  article-title: Visual analysis of uncertainties in ocean forecasts for planning and operation of off-shore structures
  publication-title: Proc IEEE Pacific Vis Symp
– ident: ref100
  doi: 10.1111/cgf.12359
– ident: ref24
  doi: 10.1111/j.1467-8659.2012.03112.x
– ident: ref60
  doi: 10.1109/PacificVis.2012.6183556
– ident: ref50
  doi: 10.1615/Int.J.UncertaintyQuantification.2012003966
– ident: ref26
  doi: 10.1007/978-1-4471-6497-5_1
– ident: ref1
  doi: 10.1145/637357.637361
– ident: ref23
  doi: 10.1109/ICDMW.2009.55
– ident: ref6
  doi: 10.1109/TVCG.2014.2346455
– ident: ref10
  doi: 10.1111/j.1467-8659.2012.03096.x
– ident: ref78
  doi: 10.1109/TVCG.2014.2346448
– ident: ref112
  doi: 10.1111/cgf.12390
– volume: 15
  start-page: 1351
  year: 2009
  ident: ref22
  article-title: Interactive visual analysis of complex scientific data as families of data surfaces
  publication-title: IEEE Trans Vis Comput Graph
  doi: 10.1109/TVCG.2009.155
– start-page: 55
  year: 2013
  ident: ref66
  article-title: Visualizing contour distributions in 2d ensemble data
  publication-title: EuroVis - Short Papers
– ident: ref62
  doi: 10.1109/TVCG.2010.111
– ident: ref43
  doi: 10.1109/TVCG.2010.181
– ident: ref74
  doi: 10.1109/PACIFICVIS.2016.7465271
– ident: ref108
  doi: 10.1145/2818517.2818531
– ident: ref12
  doi: 10.1111/j.1467-8659.2011.01942.x
– ident: ref30
  doi: 10.1111/cgf.12653
– ident: ref106
  doi: 10.1109/TVCG.2016.2534560
– ident: ref33
  doi: 10.1109/MCG.2005.71
– ident: ref82
  doi: 10.1109/VAST.2015.7347635
– ident: ref72
  doi: 10.1111/j.1467-8659.2011.01944.x
– ident: ref8
  doi: 10.1109/TVCG.2015.2507569
– ident: ref83
  doi: 10.1109/TVCG.2017.2745178
– ident: ref63
  doi: 10.1109/VAST.2015.7347634
– start-page: 82 940p
  year: 2012
  ident: ref110
  article-title: Instant visitation maps for interactive visualization of uncertain particle trajectories
  publication-title: Proc IS&T/SPIE Electronic Imaging 97
– volume: 30
  start-page: 45
  year: 2010
  ident: ref120
  article-title: In situ visualization for large-scale combustion simulations
  publication-title: IEEE Comput Graph Appl
  doi: 10.1109/MCG.2010.55
– ident: ref2
  doi: 10.1109/LDAV.2011.6092313
– ident: ref64
  doi: 10.1109/TVCG.2015.2410278
– year: 2017
  ident: ref56
  article-title: Scientific visualization contest 2016
– ident: ref102
  doi: 10.1109/PacificVis.2012.6183591
– ident: ref76
  doi: 10.1109/VISUAL.2003.1250412
– year: 1988
  ident: ref94
  article-title: Eddies, streams, and convergence zones in turbulent flows
– start-page: 49
  year: 1936
  ident: ref90
  article-title: On the generalised distance in statistics
  publication-title: Proc Nat Inst Sci India
– volume: 19
  start-page: 2733
  year: 2013
  ident: ref107
  article-title: Coupled ensemble flow line advection and analysis
  publication-title: IEEE Trans Vis Comput Graph
  doi: 10.1109/TVCG.2013.144
– ident: ref13
  doi: 10.1109/TVCG.2017.2744099
– ident: ref77
  doi: 10.1109/PACIFICVIS.2016.7465272
– ident: ref18
  doi: 10.1109/TVCG.2015.2507592
– ident: ref38
  doi: 10.2481/dsj.3.153
– year: 2002
  ident: ref3
  publication-title: Analysis of Longitudinal Data
  doi: 10.1093/oso/9780198524847.001.0001
– start-page: 82 940b
  year: 2012
  ident: ref47
  article-title: Exploring ensemble visualization
  publication-title: Proc IS&T/SPIE Electronic Imaging 97
– volume: 1
  year: 2007
  ident: ref89
  article-title: Comprehensive survey on distance/similarity measures between probability density functions
  publication-title: city
– ident: ref59
  doi: 10.1016/S0097-8493(02)00055-9
– ident: ref52
  doi: 10.1111/cgf.12649
– ident: ref41
  doi: 10.1007/BF00547132
– ident: ref79
  doi: 10.1177/1473871611416549
– ident: ref93
  doi: 10.1109/TVCG.2006.76
– ident: ref16
  doi: 10.1109/TVCG.2015.2498554
– ident: ref104
  doi: 10.1109/TVCG.2013.92
– ident: ref39
  doi: 10.3354/cr01213
– ident: ref36
  doi: 10.1126/science.1115255
– ident: ref15
  doi: 10.1109/TVCG.2016.2598868
– ident: ref11
  doi: 10.1111/j.1467-8659.2012.03095.x
– start-page: 69
  year: 2013
  ident: ref103
  article-title: Extraction and visual analysis of seismic horizon ensembles
  publication-title: Proc Eurographics '05 (short papers)
– ident: ref95
  doi: 10.1017/S0022112095000462
– ident: ref111
  doi: 10.1109/TVCG.2017.2743989
– ident: ref51
  doi: 10.1109/TVCG.2011.203
– ident: ref109
  doi: 10.1007/s12650-016-0388-0
– ident: ref80
  doi: 10.1109/TVCG.2004.39
– ident: ref61
  doi: 10.1007/s00791-002-0079-3
– ident: ref81
  doi: 10.1109/PACIFICVIS.2016.7465256
– ident: ref7
  doi: 10.1109/TVCG.2013.143
– ident: ref97
  doi: 10.1109/PACIFICVIS.2011.5742374
– start-page: 82 940u
  year: 2012
  ident: ref73
  article-title: Comparative visualization of ensembles using ensemble surface slicing
  publication-title: Proc IS&T/SPIE Electronic Imaging 97
– ident: ref34
  doi: 10.1109/TVCG.2012.110
– ident: ref35
  doi: 10.1109/MCG.2014.52
– ident: ref44
  doi: 10.1109/WSC.2007.4419664
– ident: ref32
  doi: 10.1109/TVCG.2016.2598870
– start-page: 1
  year: 2008
  ident: ref88
  article-title: Dynamic time warping algorithm review
– ident: ref114
  doi: 10.1615/Int.J.UncertaintyQuantification.2012003934
– start-page: 87
  year: 2011
  ident: ref115
  article-title: Closed stream lines in uncertain vector fields
  publication-title: Proc 27th Spring Conf Comput Graph
– ident: ref75
  doi: 10.1109/PACIFICVIS.2017.8031589
– ident: ref45
  doi: 10.1088/1742-6596/180/1/012089
– ident: ref65
  doi: 10.1109/MCG.2015.70
– ident: ref87
  doi: 10.1109/TIP.2003.819861
– ident: ref40
  doi: 10.1109/TVCG.2016.2598869
– volume: 24
  start-page: 25
  year: 2016
  ident: ref21
  article-title: Comparative visual analysis of transport variability in flow ensembles
  publication-title: J WSCG
– ident: ref116
  doi: 10.1111/j.1467-8659.2012.03097.x
– ident: ref5
  doi: 10.1109/TVCG.2015.2467204
– ident: ref119
  doi: 10.1109/PACIFICVIS.2017.8031586
– ident: ref71
  doi: 10.1109/TVCG.2013.208
– start-page: 226
  year: 1996
  ident: ref86
  article-title: A density-based algorithm for discovering clusters in large spatial databases with noise
  publication-title: Proc Int'l Conf Knowledge Discovery and Data Mining
– ident: ref37
  doi: 10.1109/TVCG.2014.2346755
– ident: ref46
  doi: 10.1109/SciVis.2015.7429487
– year: 2006
  ident: ref84
  publication-title: Pattern Recognition and Machine Learning
– ident: ref20
  doi: 10.1109/TVCG.2014.2307892
– ident: ref70
  doi: 10.1109/TVCG.2015.2467958
– ident: ref118
  doi: 10.1109/PACIFICVIS.2017.8031590
– ident: ref68
  doi: 10.1109/TVCG.2010.247
– ident: ref98
  doi: 10.1109/TVCG.2014.2346321
– ident: ref58
  doi: 10.1109/TVCG.2016.2637333
– ident: ref92
  doi: 10.1109/TVCG.2013.138
– start-page: 1
  year: 2010
  ident: ref54
  article-title: Interactive visual analysis of families of surfaces: An application to car race and car setup
  publication-title: Proc Symp Vis Analytics Sci Technol
– ident: ref17
  doi: 10.1109/TVCG.2015.2468093
– ident: ref4
  doi: 10.1111/cgf.12898
– ident: ref96
  doi: 10.1111/j.1467-8659.2009.01604.x
– ident: ref53
  doi: 10.1109/TVCG.2010.171
– ident: ref31
  doi: 10.1109/VIZSEC.2015.7312766
– ident: ref91
  doi: 10.1007/s00357-003-0004-6
– ident: ref27
  doi: 10.1109/MCG.2003.1231171
SSID ssj0014489
Score 2.5860975
SecondaryResourceType review_article
Snippet Over the last decade, ensemble visualization has witnessed a significant development due to the wide availability of ensemble data, and the increasing...
Not provided.
SourceID osti
proquest
pubmed
crossref
ieee
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 2853
SubjectTerms Biological system modeling
Clustering
Computational modeling
Computer Science
Data analysis
Data management
Data models
Data visualization
Ensemble data
literature analysis
Task analysis
taxonomy
Uncertainty
Visualization
visualization and visual analysis
Title Visualization and Visual Analysis of Ensemble Data: A Survey
URI https://ieeexplore.ieee.org/document/8405549
https://www.ncbi.nlm.nih.gov/pubmed/29994615
https://www.proquest.com/docview/2268434832
https://www.proquest.com/docview/2068340650
https://www.osti.gov/biblio/1610947
Volume 25
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3Lb9YwDLe2neDAa8DKBgoSJ0S_dU2-NkFcpj2YkMaFbdotysOVEFuL9rVI8Ndj96UJDcSpVZuqaWwnPzf2zwBvKq-XmCOmhD6qlCY8neogTRqlM7EqtAp9utjp5-LkXH26XF6uwbs5FwYR--AzXPBpv5cfm9Dxr7JdckZo9TPrsE6O25CrNe8YkJthhvjCMs0JpY87mHuZ2T27OPjIQVx6kdPiRC4PMwATMFIFF8O9tRz19VXo0JB1_R1x9ivP8UM4nfo8BJx8W3StX4Rff9A5_u9HPYIHIwQV-4POPIY1rJ_A_VvEhJvw4eLrirMthxxN4eoohitiIjERTSWO6hVe-ysUh65178W--NLd_MCfT-H8-Ojs4CQd6yykgaaXNpUSS1869C548sZCIcvoUXsTnMx1yIoqKHTLCpHAmDIoKyzKKAMbfEQp5TPYqJsat0CoEI3TTKFTZMop4zPMc19yESztY1YmkE3DbcNIQs61MK5s74xkxrKwLAvLjsJK4O38yPeBgeNfjTd5hOeG4-AmsM0ytYQqmBo3cAxRaO0ec80r6tTOJGo7WvDK5kyDIxVNeAm8nm-T7fGGiqux6ahNVmipGOQm8HxQkfnNk4K9uLtH23CP-j1Gq-3ARnvT4UuCN61_1ev1bwi28YU
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwzV1Lb9QwELaqcgAOvMojtICR4IKUbWp7ExvBoeqDLX1c2Fa9ubYzkVDbBHWzoPJb-Cv8N2byUoWAWyVOWWW9Wif-PP7GnvmGsVeF12MQADGyjyJGg6djHaSJc-lMXqRahSZdbP8gnRyqj8fj4wX2Y8iFAYAm-AxG9LE5y8-rMKetslV0RnD1M10I5S5cfkMHbfZ-ZxNH87UQ21vTjUnc1RCIA06dOpYSMp858C549DRCKrPcg_YmOCl0SNIiKHDjAgCJhjIgC0izXAYCcw6StjvRwN9AnjEWbXbYcEaBjo1pIxqzWKBf0J2ZriVmdXq08YHCxvRI4HKIThZpDiMVUymV372yADYVXfBS4Xz-O8dt1rrtu-xn_5baEJfT0bz2o_D9NwHJ__U13mN3OpLN19tZcZ8tQPmA3b4ivbjE3h19nlE-aZuFyl2Z8_YO72VaeFXwrXIG5_4M-Kar3Vu-zj_NL77C5UN2eC3df8QWy6qEJ4yrkBunSSQoTZRTxicghM-ozJf2eZJFLOmH14ZOZp2qfZzZxt1KjCVwWAKH7cARsTfDT760GiP_arxEIzo07AYzYsuEIYu8icR_A0VJhdqukZq-wk6t9NCynY2aWUFCP1KhSY_Yy-FrtC50ZORKqObYJkm1VETjI_a4heTwzz2gn_65Ry_Yzcl0f8_u7RzsLrNb-AxdbN4KW6wv5vAMyVztnzdzirOT60bfL_35UhM
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Visualization+and+Visual+Analysis+of+Ensemble+Data%3A+A+Survey&rft.jtitle=IEEE+transactions+on+visualization+and+computer+graphics&rft.au=Wang%2C+Junpeng&rft.au=Hazarika%2C+Subhashis&rft.au=Li%2C+Cheng&rft.au=Shen%2C+Han-Wei&rft.date=2019-09-01&rft.issn=1941-0506&rft.eissn=1941-0506&rft.volume=25&rft.issue=9&rft.spage=2853&rft_id=info:doi/10.1109%2FTVCG.2018.2853721&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1077-2626&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1077-2626&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1077-2626&client=summon