{"id":"https://openalex.org/W7203607340","doi":"https://doi.org/10.3390/bdcc10080275","title":"Declarative Causal Inference and Counterfactual Reasoning via SQL-Dialect Operators","display_name":"Declarative Causal Inference and Counterfactual Reasoning via SQL-Dialect Operators","publication_year":2026,"publication_date":"2026-08-17","ids":{"openalex":"https://openalex.org/W7203607340","doi":"https://doi.org/10.3390/bdcc10080275"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc10080275","doi":"https://doi.org/10.3390/bdcc10080275","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10080275","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/bdcc10080275","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015925913","display_name":"Ronnit Peter","orcid":"https://orcid.org/0009-0004-4025-4985","observed_orcids":["https://orcid.org/0009-0004-4025-4985"]},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ronnit Peter","raw_affiliation_strings":["Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009118014","display_name":"Suprio Ray","orcid":"https://orcid.org/0000-0003-0681-9685","observed_orcids":["https://orcid.org/0000-0003-0681-9685"]},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Suprio Ray","raw_affiliation_strings":["Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039930829","display_name":"Moulay A. Akhloufi","orcid":"https://orcid.org/0000-0002-4378-2669","observed_orcids":["https://orcid.org/0000-0002-4378-2669"]},"institutions":[{"id":"https://openalex.org/I154799132","display_name":"Universit\u00e9 de Moncton","ror":"https://ror.org/029tnqt29","country_code":"CA","type":"education","lineage":["https://openalex.org/I154799132"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Moulay A. Akhloufi","raw_affiliation_strings":["Department of Computer Science, Universit\u00e9 de Moncton, Moncton, NB E1A 3E9, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4378-2669","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Universit\u00e9 de Moncton, Moncton, NB E1A 3E9, Canada","institution_ids":["https://openalex.org/I154799132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009118014"],"corresponding_institution_ids":["https://openalex.org/I106938459"],"apc_list":{"value":1800,"currency":"CHF","value_usd":2172},"apc_paid":{"value":1800,"currency":"CHF","value_usd":2172},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"8","first_page":"275","last_page":"275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.3815999925136566,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.3815999925136566,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.1542000025510788,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.1429000049829483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.7419999837875366},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"counterfactual reasoning","score":0.9919999837875366},{"id":"https://openalex.org/keywords/relational-algebra","display_name":"relational algebra","score":0.6610000133514404},{"id":"https://openalex.org/keywords/treatment-effect-estimation","display_name":"treatment effect estimation","score":0.9599999785423279},{"id":"https://openalex.org/keywords/conditional-treatment-effects","display_name":"conditional treatment effects","score":0.8159999847412109},{"id":"https://openalex.org/keywords/meta-learner","display_name":"meta-learner","score":0.9229999780654907},{"id":"https://openalex.org/keywords/k-d-tree","display_name":"k-d tree","score":0.6209999918937683},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"locality-sensitive hashing","score":0.9670000076293945},{"id":"https://openalex.org/keywords/covariate-imbalance","display_name":"covariate imbalance","score":0.546999990940094},{"id":"https://openalex.org/keywords/statistical-significance-testing","display_name":"statistical significance testing","score":0.4259999990463257},{"id":"https://openalex.org/keywords/relational-databases","display_name":"relational databases","score":0.4860000014305115}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8073999881744385},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.7188000082969666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61080002784729},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.5454000234603882},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.4991999864578247},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.397599995136261},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.37779998779296875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35910001397132874},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.34150001406669617},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3400000035762787},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C129916263","wikidata":"https://www.wikidata.org/wiki/Q1141183","display_name":"Backward chaining","level":4,"score":0.32820001244544983},{"id":"https://openalex.org/C156884757","wikidata":"https://www.wikidata.org/wiki/Q798554","display_name":"Backtracking","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.29499998688697815},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C24394798","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database management system","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2540000081062317}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/bdcc10080275","doi":"https://doi.org/10.3390/bdcc10080275","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10080275","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6d80deb1720c438aa7bf0144bfda8bcb","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/6d80deb1720c438aa7bf0144bfda8bcb","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 10, Iss 8, p 275 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc10080275","doi":"https://doi.org/10.3390/bdcc10080275","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10080275","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G994121499","display_name":null,"funder_award_id":"AIP_2023_002","funder_id":"https://openalex.org/F4320319980","funder_display_name":"New Brunswick Innovation Foundation"}],"funders":[{"id":"https://openalex.org/F4320319980","display_name":"New Brunswick Innovation Foundation","ror":"https://ror.org/02rbgnh75"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1978108654","https://openalex.org/W1980056392","https://openalex.org/W2024834471","https://openalex.org/W2044849727","https://openalex.org/W2078658856","https://openalex.org/W2087796842","https://openalex.org/W2090850279","https://openalex.org/W2116943185","https://openalex.org/W2125671345","https://openalex.org/W2132917208","https://openalex.org/W2138290169","https://openalex.org/W2143891888","https://openalex.org/W2147717514","https://openalex.org/W2150291618","https://openalex.org/W2155163959","https://openalex.org/W2165558283","https://openalex.org/W2263423262","https://openalex.org/W2282821441","https://openalex.org/W2295598076","https://openalex.org/W2439568532","https://openalex.org/W2577227262","https://openalex.org/W2624816748","https://openalex.org/W2735301415","https://openalex.org/W2752836989","https://openalex.org/W2785011159","https://openalex.org/W2804233742","https://openalex.org/W2891340972","https://openalex.org/W2898694742","https://openalex.org/W2915762765","https://openalex.org/W2945295328","https://openalex.org/W2949054050","https://openalex.org/W2951936974","https://openalex.org/W2981869278","https://openalex.org/W3005086430","https://openalex.org/W3031898476","https://openalex.org/W3035965352","https://openalex.org/W3041564249","https://openalex.org/W3089065092","https://openalex.org/W3123436326","https://openalex.org/W3210216704","https://openalex.org/W4242484299","https://openalex.org/W4388656403"],"related_works":["https://openalex.org/W2520739254","https://openalex.org/W7124153410","https://openalex.org/W3182564431","https://openalex.org/W3086773382","https://openalex.org/W2752836989","https://openalex.org/W7063949193","https://openalex.org/W2963065643","https://openalex.org/W7160178997","https://openalex.org/W143679398","https://openalex.org/W7138856330"],"abstract_inverted_index":{"Relational":[0],"databases":[1],"power":[2],"high-stakes":[3],"decisions":[4],"in":[5,38,106],"lending,":[6],"healthcare,":[7],"and":[8,17,62,68,90,99,109,144],"justice,":[9],"yet":[10],"SQL":[11,42,51,85],"lacks":[12],"native":[13],"constructs":[14],"for":[15,59,71],"causal":[16,22],"counterfactual":[18,36],"reasoning.":[19],"Prior":[20],"SQL-based":[21],"systems":[23],"address":[24],"parts":[25],"of":[26],"this":[27],"gap":[28],"but":[29],"do":[30],"not":[31],"unify":[32],"treatment-effect":[33],"estimation":[34],"with":[35,53,94,133],"generation":[37],"a":[39,46,77,122,128,148,154,159],"single,":[40],"composable":[41],"surface.":[43],"We":[44,102],"present":[45],"system":[47,113],"that":[48],"extends":[49],"the":[50,104],"dialect":[52],"two":[54],"declarative":[55],"operators:":[56],"EXPLAIN_CAUSALLY_WHY":[57],"(\u03c8)":[58],"estimating":[60],"average":[61],"conditional":[63],"treatment":[64,125],"effects":[65],"via":[66,76,140],"meta-learners,":[67],"EXPLAIN_COUNTERFACTUAL":[69],"(\u03c6)":[70],"generating":[72],"diverse,":[73],"constraint-respecting":[74,146],"alternatives":[75],"hybrid":[78],"KD-tree/LSH":[79],"pipeline.":[80],"Both":[81],"operators":[82,105],"consume":[83],"standard":[84],"relations":[86],"(joins,":[87],"filters,":[88],"projections)":[89],"return":[91],"table-valued":[92],"results":[93],"optional":[95],"diagnostics,":[96,135],"confidence":[97],"intervals,":[98],"feasibility":[100],"metrics.":[101],"formalize":[103],"relational":[107],"algebra,":[108],"describe":[110],"our":[111],"prototype":[112],"called":[114],"PsiQL.":[115],"On":[116],"four":[117],"evaluation":[118],"datasets,":[119],"PsiQL":[120],"recovers":[121],"protective":[123],"TWINS":[124],"effect,":[126],"returns":[127],"non-significant":[129],"COMPAS":[130],"point":[131],"ATE":[132],"imbalance":[134,139],"flags":[136],"HMDA":[137],"covariate":[138],"built-in":[141],"SMD":[142],"checks,":[143],"generates":[145],"counterfactuals;":[147],"synthetic":[149],"Census":[150],"run":[151],"serves":[152],"as":[153],"balanced":[155],"pipeline":[156],"proof-of-concept":[157],"alongside":[158],"real":[160],"ACS":[161],"diagnostic":[162],"under":[163],"severe":[164],"imbalance.":[165]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-18T00:00:00"}
