{"id":"https://openalex.org/W2565913955","doi":"https://doi.org/10.1109/bigdata.2016.7840700","title":"Addressing the big-earth-data variety challenge with the hierarchical triangular mesh","display_name":"Addressing the big-earth-data variety challenge with the hierarchical triangular mesh","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2565913955","doi":"https://doi.org/10.1109/bigdata.2016.7840700","mag":"2565913955"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7840700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ntrs.nasa.gov/api/citations/20160014543/downloads/20160014543.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046476658","display_name":"M. L. Rilee","orcid":"https://orcid.org/0000-0002-5478-7190"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michael L. Rilee","raw_affiliation_strings":["NASA GSFC, Greenbelt, MD, USA","Rilee Systems Technologies, Derwood, MD, USA"],"affiliations":[{"raw_affiliation_string":"NASA GSFC, Greenbelt, MD, USA","institution_ids":[]},{"raw_affiliation_string":"Rilee Systems Technologies, Derwood, MD, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024434501","display_name":"Kwo\u2010Sen Kuo","orcid":"https://orcid.org/0000-0001-7644-4140"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kwo-Sen Kuo","raw_affiliation_strings":["Bavesics, LLC, Bowie, MD, USA","NASA GSFC, Greenbelt, MD, USA","University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Bavesics, LLC, Bowie, MD, USA","institution_ids":[]},{"raw_affiliation_string":"NASA GSFC, Greenbelt, MD, USA","institution_ids":[]},{"raw_affiliation_string":"University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088254301","display_name":"Thomas L. Clune","orcid":"https://orcid.org/0000-0003-3320-0204"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas Clune","raw_affiliation_strings":["NASA GSFC, Greenbelt, MD, USA"],"affiliations":[{"raw_affiliation_string":"NASA GSFC, Greenbelt, MD, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051286262","display_name":"Amidu Oloso","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144891","display_name":"Science Systems and Applications (United States)","ror":"https://ror.org/03xec1444","country_code":"US","type":"company","lineage":["https://openalex.org/I4210144891"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amidu Oloso","raw_affiliation_strings":["NASA GSFC, Greenbelt, MD, USA","SSAI, Greenbelt, MD, USA"],"affiliations":[{"raw_affiliation_string":"NASA GSFC, Greenbelt, MD, USA","institution_ids":[]},{"raw_affiliation_string":"SSAI, Greenbelt, MD, USA","institution_ids":["https://openalex.org/I4210144891"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113801101","display_name":"Paul Brown","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120419","display_name":"Paradigm Pharmaceuticals (United States)","ror":"https://ror.org/02krbtc48","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120419"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul G. Brown","raw_affiliation_strings":["Paradigm4 Inc., Waltham, MA, USA"],"affiliations":[{"raw_affiliation_string":"Paradigm4 Inc., Waltham, MA, USA","institution_ids":["https://openalex.org/I4210120419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020745360","display_name":"Hongfeng Yu","orcid":"https://orcid.org/0000-0002-0596-8227"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongfeng Yu","raw_affiliation_strings":["University of Nebraska, Lincoln, NE, USA"],"affiliations":[{"raw_affiliation_string":"University of Nebraska, Lincoln, NE, USA","institution_ids":["https://openalex.org/I114395901"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5046476658"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2729,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81948508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"33","issue":null,"first_page":"1006","last_page":"1011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7903234958648682},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.7772554159164429},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.7266010642051697},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6618854999542236},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6480199098587036},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.6196818947792053},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4884304106235504},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.45597633719444275},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4483828544616699},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41999849677085876},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4189615547657013},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2818887531757355},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.22507494688034058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11728018522262573}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7903234958648682},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7772554159164429},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.7266010642051697},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6618854999542236},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6480199098587036},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.6196818947792053},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4884304106235504},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.45597633719444275},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4483828544616699},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41999849677085876},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4189615547657013},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2818887531757355},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.22507494688034058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11728018522262573},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2016.7840700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:casi.ntrs.nasa.gov:20160014543","is_oa":true,"landing_page_url":"http://hdl.handle.net/2060/20160014543","pdf_url":"https://ntrs.nasa.gov/api/citations/20160014543/downloads/20160014543.pdf","source":{"id":"https://openalex.org/S4377196257","display_name":"NASA STI Repository (National Aeronautics and Space Administration)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210124779","host_organization_name":"National Aeronautics and Space Administration","host_organization_lineage":["https://openalex.org/I4210124779"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CASI","raw_type":"GSFC-E-DAA-TN34964"}],"best_oa_location":{"id":"pmh:oai:casi.ntrs.nasa.gov:20160014543","is_oa":true,"landing_page_url":"http://hdl.handle.net/2060/20160014543","pdf_url":"https://ntrs.nasa.gov/api/citations/20160014543/downloads/20160014543.pdf","source":{"id":"https://openalex.org/S4377196257","display_name":"NASA STI Repository (National Aeronautics and Space Administration)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210124779","host_organization_name":"National Aeronautics and Space Administration","host_organization_lineage":["https://openalex.org/I4210124779"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CASI","raw_type":"GSFC-E-DAA-TN34964"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2565913955.pdf","grobid_xml":"https://content.openalex.org/works/W2565913955.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W1523882855","https://openalex.org/W1673768625","https://openalex.org/W2070991879","https://openalex.org/W2119404740","https://openalex.org/W2128566145","https://openalex.org/W2146534064","https://openalex.org/W2585491945","https://openalex.org/W2996494375","https://openalex.org/W3007608309","https://openalex.org/W6774339629"],"related_works":["https://openalex.org/W997111777","https://openalex.org/W2792109275","https://openalex.org/W3043006947","https://openalex.org/W3215678666","https://openalex.org/W2737538696","https://openalex.org/W4231725381","https://openalex.org/W4281783369","https://openalex.org/W1543687422","https://openalex.org/W2489246169","https://openalex.org/W2997869646"],"abstract_inverted_index":{"We":[0],"have":[1],"implemented":[2],"an":[3,18,124],"updated":[4],"Hierarchical":[5],"Triangular":[6],"Mesh":[7],"(HTM)":[8],"as":[9],"the":[10,26,34,38,85,140],"basis":[11],"for":[12,21,64,104],"a":[13,60],"unified":[14],"data":[15,23,68,88,99,101,134],"model":[16],"and":[17,93,114,127,154],"indexing":[19,125],"scheme":[20],"geoscience":[22],"to":[24,74,130],"address":[25],"variety":[27,116],"challenge":[28,40,54],"of":[29,36,41,107],"Big":[30,42,61,146],"Earth":[31,65],"Data.":[32],"In":[33],"absence":[35],"variety,":[37],"volume":[39],"Data":[43,62,147],"is":[44,71,122,152,157],"relatively":[45],"easily":[46],"addressable":[47],"with":[48,59,78,169],"parallel":[49],"processing.":[50],"The":[51],"more":[52],"important":[53],"in":[55],"achieving":[56],"optimal":[57],"value":[58],"solution":[63],"Science":[66],"(ES)":[67],"analysis,":[69],"however,":[70],"being":[72],"able":[73],"achieve":[75],"good":[76],"scalability":[77],"variety.":[79],"With":[80,159],"HTM":[81,121,160],"unifying":[82],"at":[83],"least":[84],"three":[86],"popular":[87],"models,":[89],"i.e.":[90],"Grid,":[91],"Swath,":[92],"Point,":[94],"used":[95],"by":[96],"current":[97],"ES":[98,132],"products,":[100],"preparation":[102],"time":[103],"integrative":[105],"analysis":[106],"diverse":[108],"datasets":[109],"can":[110,118],"be":[111,119],"drastically":[112],"reduced":[113],"better":[115,155],"scaling":[117],"achieved.":[120],"also":[123],"scheme,":[126],"when":[128],"applied":[129],"all":[131],"datasets,":[133],"placement":[135],"alignment":[136],"(or":[137],"co-location)":[138],"on":[139],"shared":[141],"nothing":[142],"architecture,":[143],"which":[144],"most":[145,161],"systems":[148],"are":[149],"based":[150],"on,":[151],"guaranteed":[153],"performance":[156,171],"ensured.":[158],"geospatial":[162],"set":[163],"operations":[164,168],"become":[165],"integer":[166],"interval":[167],"further":[170],"advantages.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
