{"id":"https://openalex.org/W4318147467","doi":"https://doi.org/10.1109/bigdata55660.2022.10020499","title":"Nine Questions to Evaluate a Data Science Team\u2019s Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study","display_name":"Nine Questions to Evaluate a Data Science Team\u2019s Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318147467","doi":"https://doi.org/10.1109/bigdata55660.2022.10020499"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020499","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020499","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059644651","display_name":"Jeffrey Saltz","orcid":"https://orcid.org/0000-0002-8913-1095"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jeffrey Saltz","raw_affiliation_strings":["Syracuse University"],"affiliations":[{"raw_affiliation_string":"Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059644651"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":0.2907,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64740741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2667","last_page":"2672"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12443","display_name":"Delphi Technique in Research","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12443","display_name":"Delphi Technique in Research","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.989300012588501,"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"}},{"id":"https://openalex.org/T10970","display_name":"Team Dynamics and Performance","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6788338422775269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5820196866989136},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4897644519805908},{"id":"https://openalex.org/keywords/delphi-method","display_name":"Delphi method","score":0.4892701804637909},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4674322009086609},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.44133463501930237},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.4297909140586853},{"id":"https://openalex.org/keywords/process-management","display_name":"Process management","score":0.38930052518844604},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.3255065381526947},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1953352391719818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.0961063802242279},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.09174373745918274}],"concepts":[{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6788338422775269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5820196866989136},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4897644519805908},{"id":"https://openalex.org/C60641444","wikidata":"https://www.wikidata.org/wiki/Q841602","display_name":"Delphi method","level":2,"score":0.4892701804637909},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4674322009086609},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44133463501930237},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.4297909140586853},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.38930052518844604},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3255065381526947},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1953352391719818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0961063802242279},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.09174373745918274},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020499","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020499","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1153687699","https://openalex.org/W1587794822","https://openalex.org/W2043436402","https://openalex.org/W2149236908","https://openalex.org/W2314130904","https://openalex.org/W2519706319","https://openalex.org/W2596631692","https://openalex.org/W2758323673","https://openalex.org/W2781488654","https://openalex.org/W2890794407","https://openalex.org/W2998701638","https://openalex.org/W3004963719","https://openalex.org/W3025589433","https://openalex.org/W3119305695","https://openalex.org/W3123348931","https://openalex.org/W3138971255","https://openalex.org/W3139190783","https://openalex.org/W4205131035","https://openalex.org/W4205591221","https://openalex.org/W4206155778","https://openalex.org/W4213366078","https://openalex.org/W4232488826","https://openalex.org/W6627525331","https://openalex.org/W6754307228"],"related_works":["https://openalex.org/W4247880953","https://openalex.org/W3086249470","https://openalex.org/W2935880430","https://openalex.org/W1996408511","https://openalex.org/W3204278764","https://openalex.org/W2032603375","https://openalex.org/W2359550725","https://openalex.org/W2463383507","https://openalex.org/W785495564","https://openalex.org/W2100127921"],"abstract_inverted_index":{"While":[0],"the":[1,14,86,91,95,108],"lack":[2],"of":[3,13,110],"an":[4,39,144],"effective":[5],"team":[6,52,76,96,104],"process":[7,53,105,117,133],"is":[8,43],"often":[9],"noted":[10],"as":[11,140,142],"one":[12],"key":[15,71],"drivers":[16],"for":[17,45,118],"data":[18,34,46,74,126,146],"science":[19,35,47,75,127,147],"project":[20,148],"inefficiencies":[21],"and":[22,55,97,114,136],"failures,":[23],"there":[24],"has":[25],"been":[26],"minimal":[27],"research":[28,122],"on":[29],"how":[30,125],"to":[31,49,79],"evaluate":[32,81],"a":[33,66,73,115],"team\u2019s":[36,92],"process.":[37,83],"Without":[38],"evaluation":[40,150],"framework,":[41],"it":[42],"difficult":[44],"teams":[48,128],"understand":[50],"their":[51,82,132],"strengths":[54],"weaknesses.":[56],"To":[57],"help":[58,80],"address":[59],"this":[60,62],"challenge,":[61],"exploratory":[63],"research,":[64],"via":[65],"Delpha":[67],"study,":[68],"identified":[69,88,103],"nine":[70],"questions":[72,89,106,139],"could":[77,123],"answer":[78],"In":[84],"short,":[85],"study":[87,101],"evaluating":[90],"communication":[93],"(within":[94],"with":[98],"stakeholders).":[99],"The":[100],"also":[102],"(e.g.,":[107],"use":[109],"iterations,":[111],"life":[112],"cycles":[113],"prioritization":[116],"potential":[119],"tasks).":[120],"Future":[121],"explore":[124],"can":[129],"best":[130],"improve":[131],"by":[134],"leveraging":[135],"refining":[137],"these":[138],"well":[141],"defining":[143],"overall":[145],"management":[149],"framework.":[151]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}