{"id":"https://openalex.org/W2507472450","doi":"https://doi.org/10.1145/2949550.2949583","title":"Estimating the Accuracy of User Surveys for Assessing the Impact of HPC Systems","display_name":"Estimating the Accuracy of User Surveys for Assessing the Impact of HPC Systems","publication_year":2016,"publication_date":"2016-07-17","ids":{"openalex":"https://openalex.org/W2507472450","doi":"https://doi.org/10.1145/2949550.2949583","mag":"2507472450"},"language":"en","primary_location":{"id":"doi:10.1145/2949550.2949583","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2949550.2949583","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2949583&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2949583&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006971182","display_name":"David Hart","orcid":"https://orcid.org/0000-0001-6393-0967"},"institutions":[{"id":"https://openalex.org/I107766831","display_name":"NSF National Center for Atmospheric Research","ror":"https://ror.org/05cvfcr44","country_code":"US","type":"facility","lineage":["https://openalex.org/I107766831","https://openalex.org/I1311060795","https://openalex.org/I2799356940","https://openalex.org/I4210141337","https://openalex.org/I4210150888"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David Hart","raw_affiliation_strings":["National Center for Atmospheric Research, Boulder, CO"],"affiliations":[{"raw_affiliation_string":"National Center for Atmospheric Research, Boulder, CO","institution_ids":["https://openalex.org/I107766831"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006215254","display_name":"Melissa Rishel","orcid":null},"institutions":[{"id":"https://openalex.org/I71966907","display_name":"University of Northern Colorado","ror":"https://ror.org/016bysn57","country_code":"US","type":"education","lineage":["https://openalex.org/I71966907"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Melissa Rishel","raw_affiliation_strings":["University of Northern Colorado, McKee, Greeley, CO"],"affiliations":[{"raw_affiliation_string":"University of Northern Colorado, McKee, Greeley, CO","institution_ids":["https://openalex.org/I71966907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020468749","display_name":"Doug Nychka","orcid":null},"institutions":[{"id":"https://openalex.org/I107766831","display_name":"NSF National Center for Atmospheric Research","ror":"https://ror.org/05cvfcr44","country_code":"US","type":"facility","lineage":["https://openalex.org/I107766831","https://openalex.org/I1311060795","https://openalex.org/I2799356940","https://openalex.org/I4210141337","https://openalex.org/I4210150888"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Doug Nychka","raw_affiliation_strings":["National Center for Atmospheric Research, Boulder, CO"],"affiliations":[{"raw_affiliation_string":"National Center for Atmospheric Research, Boulder, CO","institution_ids":["https://openalex.org/I107766831"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006971182"],"corresponding_institution_ids":["https://openalex.org/I107766831"],"apc_list":null,"apc_paid":null,"fwci":1.8864,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.9107878,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11891","display_name":"Big Data and Business Intelligence","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7511744499206543},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7339551448822021},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5543389916419983},{"id":"https://openalex.org/keywords/survey-data-collection","display_name":"Survey data collection","score":0.4962332844734192},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32355040311813354},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13772839307785034},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13181570172309875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7511744499206543},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7339551448822021},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5543389916419983},{"id":"https://openalex.org/C198477413","wikidata":"https://www.wikidata.org/wiki/Q7647069","display_name":"Survey data collection","level":2,"score":0.4962332844734192},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32355040311813354},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13772839307785034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13181570172309875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2949550.2949583","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2949550.2949583","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2949583&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2949550.2949583","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2949550.2949583","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2949583&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1859580011","display_name":"EAGER: Tracing the Use of Research Resources Using Persistent Citable Identifiers","funder_award_id":"1448480","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4101958040","display_name":"Management and Operation of National Center for Atmospheric Research, 2008-2018, and Supporting Activities","funder_award_id":"0753581","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7044180687","display_name":null,"funder_award_id":"ark:/85065/d7wd3xhc","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7369841305","display_name":null,"funder_award_id":"AGS-0753581,ACI-1448480","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8838565665","display_name":null,"funder_award_id":"AGS-0753581","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2507472450.pdf","grobid_xml":"https://content.openalex.org/works/W2507472450.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1834724147","https://openalex.org/W2004723162","https://openalex.org/W2011467533","https://openalex.org/W2016382728","https://openalex.org/W2022206544","https://openalex.org/W2027380885","https://openalex.org/W2059084416","https://openalex.org/W2091631842","https://openalex.org/W2101986949","https://openalex.org/W2121329116","https://openalex.org/W2166033483","https://openalex.org/W2173251738","https://openalex.org/W2266552780","https://openalex.org/W2490505125","https://openalex.org/W2993268668","https://openalex.org/W3123730459","https://openalex.org/W6996281411"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Each":[0],"year,":[1],"the":[2,26,32,54,57,63,84,89,97,114,118,128,137,141,144,151,156,160,175],"Computational":[3],"&":[4],"Information":[5],"Systems":[6],"Laboratory":[7],"(CISL)":[8],"conducts":[9],"a":[10,21,44,74],"survey":[11,58,90,133,142,176],"of":[12,23,34,56,65,88,99,150,167],"its":[13],"current":[14],"and":[15,29,48,86,107,170],"recent":[16],"user":[17],"community":[18],"to":[19,78,96,112,116,135,139,173],"gather":[20],"number":[22],"metrics":[24],"about":[25,127],"scientific":[27],"impact":[28],"outcomes":[30],"from":[31],"use":[33,166],"CISL's":[35],"high-performance":[36],"computing":[37],"systems,":[38],"particularly":[39],"peer-reviewed":[40],"publications.":[41,146],"However,":[42],"with":[43,132,155,163],"modest":[45],"response":[46],"rate":[47],"reliance":[49],"on":[50,83],"self-reporting":[51],"by":[52],"users,":[53],"accuracy":[55,85],"is":[59,62],"uncertain":[60],"as":[61],"degree":[64,138],"that":[66,76],"uncertainty.":[67],"To":[68],"quantify":[69,136],"this":[70],"uncertainty,":[71],"CISL":[72],"undertook":[73],"project":[75],"attempted":[77,111],"provide":[79],"statistically":[80],"supported":[81],"limits":[82],"precision":[87],"approach.":[91],"We":[92],"discovered":[93],"limitations":[94],"related":[95],"range":[98],"users'":[100],"HPC":[101,129,168],"usage":[102,119,130],"in":[103],"our":[104],"modeling":[105],"phase,":[106],"several":[108],"methods":[109],"were":[110],"adjust":[113],"model":[115],"fit":[117],"data.":[120],"The":[121],"resulting":[122],"statistical":[123,157],"models":[124],"leverage":[125],"data":[126],"associated":[131,162],"invitees":[134],"which":[140],"undercounts":[143],"relevant":[145],"A":[147],"qualitative":[148],"assessment":[149],"collected":[152],"publications":[153],"aligns":[154],"models,":[158],"reiterates":[159],"challenges":[161],"acknowledgment":[164],"for":[165],"resources,":[169],"suggests":[171],"ways":[172],"improve":[174],"results":[177],"further.":[178]},"counts_by_year":[{"year":2019,"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"}
