{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T05:10:49Z","timestamp":1778130649676,"version":"3.51.4"},"reference-count":41,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,17]]},"DOI":"10.1109\/saner-c67878.2026.00024","type":"proceedings-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T19:39:18Z","timestamp":1778096358000},"page":"141-148","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Data Quality Disparity and Implications for Fair Machine Learning"],"prefix":"10.1109","author":[{"given":"Mohit","family":"Sharma","sequence":"first","affiliation":[{"name":"IIT Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pratik","family":"Mishra","sequence":"additional","affiliation":[{"name":"IBM Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandeep","family":"Hans","sequence":"additional","affiliation":[{"name":"IBM Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abhijnan","family":"Chakraborty","sequence":"additional","affiliation":[{"name":"IIT Kharagpur"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijay","family":"Arya","sequence":"additional","affiliation":[{"name":"IBM Research"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.32388\/OUXT01","volume-title":"Fantastic biases (what are they) and where to find them","author":"Barriere","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/sci6010003"},{"key":"ref3","volume-title":"Indibias: A benchmark dataset to measure social biases in language models for indian context","author":"Sahoo","year":"2024"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052660"},{"key":"ref5","volume-title":"Few-shot fairness: Unveiling llm\u2019s potential for fairness-aware classification","author":"Chhikara","year":"2024"},{"key":"ref6","volume-title":"AI Fairness 360: An extensible toolkit for detecting, understanding, and mitigating unwanted algorithmic bias","author":"Bellamy","year":"2019"},{"key":"ref7","volume-title":"Data quality assessment: Challenges and opportunities","author":"Mohammed","year":"2024"},{"key":"ref8","volume-title":"dbt core","year":"2025"},{"key":"ref9","volume-title":"Soda core","year":"2025"},{"key":"ref10","volume-title":"Rein: A comprehensive benchmark framework for data cleaning methods in ml pipelines","author":"Abdelaal","year":"2023"},{"key":"ref11","volume-title":"Adult income dataset","author":"Becker","year":"2019"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.463"},{"key":"ref13","volume-title":"IQA-PyTorch: Pytorch toolbox for image quality assessment","author":"Chen","year":"2022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1310\/sci2402-110"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1891\/1541-6577.27.4.276"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i9.21189"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0463-8"},{"key":"ref18","volume-title":"Missing fairness: The discriminatory effect of missing values in datasets on fairness in machine learning","author":"Fricke","year":"2020"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1287\/lytx.2014.01.05"},{"key":"ref20","article-title":"Assessing fairness in the presence of missing data","volume-title":"Proc. NeurIPS","author":"Zhang"},{"key":"ref21","doi-asserted-by":"crossref","DOI":"10.1145\/3630106.3658977","volume-title":"The impact of differential feature under-reporting on algorithmic fairness","author":"Akpinar","year":"2024"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3616865"},{"key":"ref23","article-title":"Why is my classifier discriminatory?","volume-title":"Proc. NeurIPS","volume":"31","author":"Chen"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1201\/9781003278290-37"},{"key":"ref25","volume-title":"Compas dataset","author":"Larson","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgph.0003555"},{"key":"ref27","volume-title":"Quantifying disparities in intimate partner violence: a machine learning method to correct for underreporting","author":"Shanmugam","year":"2023"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3375627.3375862"},{"key":"ref29","volume-title":"Still more shades of null: An evaluation suite for responsible missing value imputation","author":"Khan","year":"2025"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2402267121"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-030718-104938"},{"key":"ref32","article-title":"Hellinger distance","author":"Nikulin","year":"2001","journal-title":"Encyclopedia of Mathematics"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/18.61115"},{"key":"ref34","volume-title":"Breaking the global north stereotype: A global south-centric benchmark dataset for auditing and mitigating biases in facial recognition systems","author":"Jaiswal","year":"2024"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2019.102654"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00159"},{"key":"ref37","article-title":"Heart Disease","author":"Janosi","year":"1989","journal-title":"UCI Machine Learning Repository"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25353"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2831899"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3378466"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00447"}],"event":{"name":"2026 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)","location":"Limassol, Cyprus","start":{"date-parts":[[2026,3,17]]},"end":{"date-parts":[[2026,3,20]]}},"container-title":["2026 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11500139\/11499992\/11500251.pdf?arnumber=11500251","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:18:07Z","timestamp":1778127487000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11500251\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,17]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/saner-c67878.2026.00024","relation":{},"subject":[],"published":{"date-parts":[[2026,3,17]]}}}