2017
AUTHORSLars Huettenberger , Christian Heine , Christoph Garth
ABSTRACTFor the scientific visualization and analysis of univariate (scalar) fields several topological approaches like contour trees and Reeb graphs were studied and compared to each other some time ago. In recent years, some of those approaches were generalized to multivariate fields. Among others, data structures like the joint contour net (JCN) and the Pareto set were introduced and improved in subsequent work. However, both methods utilized individual data sets as test cases for their proof-of-concept sections and partially lacked a complete comparison to other multivariate approaches. Hence, to better understand the relationship between those two data structures and to gain insights into general multivariate topology, we present a deeper comparison of JCNs and Pareto sets in which we integrate data sets applied in the original JCN and Pareto set papers. More... »
PAGES51-65
Topological Methods in Data Analysis and Visualization IV
ISBN
978-3-319-44682-0
978-3-319-44684-4
http://scigraph.springernature.com/pub.10.1007/978-3-319-44684-4_3
DOIhttp://dx.doi.org/10.1007/978-3-319-44684-4_3
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1085750072
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/2008/0104",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Statistics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Mathematical Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Kaiserslautern",
"id": "https://www.grid.ac/institutes/grid.7645.0",
"name": [
"University of Kaiserslautern"
],
"type": "Organization"
},
"familyName": "Huettenberger",
"givenName": "Lars",
"id": "sg:person.01057327407.69",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01057327407.69"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Swiss Federal Institute of Technology in Zurich",
"id": "https://www.grid.ac/institutes/grid.5801.c",
"name": [
"ETH Zurich"
],
"type": "Organization"
},
"familyName": "Heine",
"givenName": "Christian",
"id": "sg:person.01322065347.76",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322065347.76"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Kaiserslautern",
"id": "https://www.grid.ac/institutes/grid.7645.0",
"name": [
"University of Kaiserslautern"
],
"type": "Organization"
},
"familyName": "Garth",
"givenName": "Christoph",
"id": "sg:person.01245455273.74",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01245455273.74"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1111/j.1467-8659.2011.01959.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005468264"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/800057.808695",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013227068"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.comgeo.2008.12.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015864571"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/1377676.1377720",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018796063"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/cgf.12121",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020111909"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00453-003-1052-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026752183",
"https://doi.org/10.1007/s00453-003-1052-3"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0925-7721(02)00093-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033448965"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0925-7721(02)00093-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033448965"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1017/cbo9781139106962.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040377027"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-662-44900-4_8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043680839",
"https://doi.org/10.1007/978-3-662-44900-4_8"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.cagd.2012.03.023",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044461488"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.comgeo.2006.05.009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049692924"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/aima.1997.1650",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051159102"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/cgf.12636",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053104377"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvcg.2006.165",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061812631"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvcg.2008.33",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061813066"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvcg.2011.88",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061813716"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvcg.2012.115",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061813731"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvcg.2013.269",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061814139"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/visual.2001.964519",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094395897"
],
"type": "CreativeWork"
}
],
"datePublished": "2017",
"datePublishedReg": "2017-01-01",
"description": "For the scientific visualization and analysis of univariate (scalar) fields several topological approaches like contour trees and Reeb graphs were studied and compared to each other some time ago. In recent years, some of those approaches were generalized to multivariate fields. Among others, data structures like the joint contour net (JCN) and the Pareto set were introduced and improved in subsequent work. However, both methods utilized individual data sets as test cases for their proof-of-concept sections and partially lacked a complete comparison to other multivariate approaches. Hence, to better understand the relationship between those two data structures and to gain insights into general multivariate topology, we present a deeper comparison of JCNs and Pareto sets in which we integrate data sets applied in the original JCN and Pareto set papers.",
"editor": [
{
"familyName": "Carr",
"givenName": "Hamish",
"type": "Person"
},
{
"familyName": "Garth",
"givenName": "Christoph",
"type": "Person"
},
{
"familyName": "Weinkauf",
"givenName": "Tino",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-319-44684-4_3",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-319-44682-0",
"978-3-319-44684-4"
],
"name": "Topological Methods in Data Analysis and Visualization IV",
"type": "Book"
},
"name": "A Comparison of Joint Contour Nets and Pareto Sets",
"pagination": "51-65",
"productId": [
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-319-44684-4_3"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"0e43b02834517d726e5674239bb33f51403c3e595d0b0c5e0dc250dbd388d42e"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1085750072"
]
}
],
"publisher": {
"location": "Cham",
"name": "Springer International Publishing",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-319-44684-4_3",
"https://app.dimensions.ai/details/publication/pub.1085750072"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-15T17:17",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8678_00000279.jsonl",
"type": "Chapter",
"url": "http://link.springer.com/10.1007/978-3-319-44684-4_3"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1007/978-3-319-44684-4_3'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-44684-4_3'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-44684-4_3'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-44684-4_3'
This table displays all metadata directly associated to this object as RDF triples.
151 TRIPLES
23 PREDICATES
46 URIs
20 LITERALS
8 BLANK NODES