{"id":"https://openalex.org/W4200130791","doi":"https://doi.org/10.1186/s40537-021-00546-3","title":"Performance-efficient distributed transfer and transformation of big spatial histopathology datasets in the cloud","display_name":"Performance-efficient distributed transfer and transformation of big spatial histopathology datasets in the cloud","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4200130791","doi":"https://doi.org/10.1186/s40537-021-00546-3"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-021-00546-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00546-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00546-3","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00546-3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003945581","display_name":"Esma Yildirim","orcid":"https://orcid.org/0000-0001-9485-3714"},"institutions":[{"id":"https://openalex.org/I47807954","display_name":"Queensborough Community College, CUNY","ror":"https://ror.org/03a4vma36","country_code":"US","type":"education","lineage":["https://openalex.org/I47807954"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Esma Yildirim","raw_affiliation_strings":["Department of Mathematics and Computer Science, Queensborough Community College of CUNY, New York, USA"],"raw_orcid":"https://orcid.org/0000-0001-9485-3714","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Queensborough Community College of CUNY, New York, USA","institution_ids":["https://openalex.org/I47807954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5003945581"],"corresponding_institution_ids":["https://openalex.org/I47807954"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18970978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"8","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9980000257492065,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9170287847518921},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7685889005661011},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7023330926895142},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5706678032875061},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46489468216896057},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.45968127250671387},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.41428685188293457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36950036883354187},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35918128490448},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2933042645454407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9170287847518921},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7685889005661011},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7023330926895142},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5706678032875061},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46489468216896057},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.45968127250671387},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.41428685188293457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36950036883354187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35918128490448},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2933042645454407},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-021-00546-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00546-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00546-3","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:17007d99f79642efab2e7518d410b417","is_oa":true,"landing_page_url":"https://doaj.org/article/17007d99f79642efab2e7518d410b417","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 8, Iss 1, Pp 1-26 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-021-00546-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00546-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00546-3","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200130791.pdf","grobid_xml":"https://content.openalex.org/works/W4200130791.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W58772654","https://openalex.org/W1721251433","https://openalex.org/W1964055730","https://openalex.org/W1977653087","https://openalex.org/W1981172110","https://openalex.org/W2011804442","https://openalex.org/W2025892407","https://openalex.org/W2065139696","https://openalex.org/W2098434088","https://openalex.org/W2115583184","https://openalex.org/W2131645490","https://openalex.org/W2149995688","https://openalex.org/W2159814293","https://openalex.org/W2163349370","https://openalex.org/W2343200401","https://openalex.org/W2426836148","https://openalex.org/W2527131581","https://openalex.org/W2904521286","https://openalex.org/W4250969944","https://openalex.org/W4376453519"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W4244478748","https://openalex.org/W4233347783","https://openalex.org/W2910064364","https://openalex.org/W4255224757"],"abstract_inverted_index":{"Abstract":[0],"Whole":[1],"Slide":[2],"Image":[3],"(WSI)":[4],"datasets":[5,11,30,45,113,179,191],"are":[6,192],"giga-pixel":[7],"resolution,":[8],"unstructured":[9],"histopathology":[10],"that":[12,89,110,228],"consist":[13],"of":[14,37,51,59,68,202,221,251,272],"extremely":[15],"big":[16],"files":[17],"(each":[18],"can":[19,231,254],"be":[20],"as":[21,23,269],"large":[22],"multiple":[24],"GBs":[25],"in":[26,33,152,248],"compressed":[27],"format).":[28],"These":[29],"have":[31],"utility":[32],"a":[34,199,203,213,237],"wide":[35],"range":[36],"diagnostic":[38],"and":[39,57,87,100,135,138,165,167,225,263],"investigative":[40],"pathology":[41],"applications.":[42,70],"However,":[43],"the":[44,52,66,85,94,115,119,146,153,160,177,185,229,252,270],"present":[46,107],"unique":[47],"challenges:":[48],"The":[49,149,173,188],"size":[50,133],"files,":[53],"propriety":[54],"data":[55,62,174,261],"formats,":[56],"lack":[58,84],"efficient":[60],"parallel":[61],"access":[63,175],"libraries":[64],"limit":[65],"scalability":[67],"these":[69,80,112],"Commercial":[71],"clouds":[72],"provide":[73],"dynamic,":[74],"cost-effective,":[75],"scalable":[76,101,126],"infrastructure":[77],"to":[78,145,176,184,226],"process":[79],"datasets,":[81,212,224],"however,":[82],"we":[83,106],"tools":[86,164],"algorithms":[88,109,129,230],"will":[90],"transfer/transform":[91],"them":[92,123],"onto":[93,114],"cloud":[95,116],"seamlessly,":[96],"providing":[97],"faster":[98],"speeds":[99],"formats.":[102,127],"In":[103],"this":[104],"study,":[105],"novel":[108],"transfer":[111,137,163],"while":[117],"at":[118],"same":[120],"time":[121],"transforming":[122],"into":[124,194],"symmetric":[125,190,260],"Our":[128],"use":[130],"intelligent":[131],"file":[132],"distribution,":[134],"pipelining":[136],"transformation":[139],"tasks":[140],"without":[141],"introducing":[142],"extra":[143],"overhead":[144],"underlying":[147],"system.":[148],"algorithms,":[150,166],"tested":[151],"Amazon":[154],"Web":[155],"Services":[156],"(AWS)":[157],"cloud,":[158],"outperform":[159,169],"widely":[161],"used":[162],"also":[168],"our":[170,258],"previous":[171],"work.":[172,187],"transformed":[178,189],"provides":[180],"better":[181],"performance":[182,264],"compared":[183],"related":[186],"fed":[193],"three":[195],"different":[196,247],"analytics":[197],"applications:":[198],"distributed":[200],"implementation":[201],"content-based":[204],"image":[205,244],"retrieval":[206],"(CBIR)":[207],"application":[208,218,241],"for":[209,219],"prostate":[210],"carcinoma":[211],"deep":[214],"convolutional":[215],"neural":[216],"network":[217],"classification":[220],"breast":[222],"cancer":[223],"show":[227,266],"work":[232,256],"with":[233,257],"any":[234],"spatial":[235],"dataset,":[236],"Canny":[238],"Edge":[239],"Detection":[240],"on":[242],"satellite":[243],"datasets.":[245],"Although":[246],"nature,":[249],"all":[250],"applications":[253],"easily":[255],"new":[259],"format":[262],"results":[265],"near-linear":[267],"speed-ups":[268],"number":[271],"processors":[273],"increases.":[274]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}