BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260202T201809Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20251118T080000
DTEND;TZID=America/Chicago:20251118T170000
UID:submissions.supercomputing.org_SC25_sess537_int_post104@linklings.com
SUMMARY:AIDRIN: A Comprehensive Toolset for Automating Data Preparation fo
 r AI
DESCRIPTION:Kaveen Hiniduma (The Ohio State University), Jean Luca Bez (La
 wrence Berkeley National Laboratory (LBNL)), Ravi Madduri (Argonne Nationa
 l Laboratory (ANL)), and Suren Byna (The Ohio State University)\n\nHigh-qu
 ality, ethically-governed, and efficiently structured data is important fo
 r effective AI. However, organizations often lack a unified method to asse
 ss whether datasets are ready for AI modeling. AIDRIN (AI Data Readiness I
 nspector) provides a comprehensive, multi-pillar framework that quantifies
  AI data readiness across six dimensions: Quality, Impact on AI, Understan
 dability and Usability, Fairness and Bias, Structure and Organization, and
  Governance. The tool enables data teams to identify issues early, priorit
 ize remediation, and make informed modeling decisions. AIDRIN is accessibl
 e as a web application, a Python package on PyPI, and openly developed on 
 GitHub for community use and contribution, making it flexible for various 
 workflows. Its interactive visualizations and interpretable reports help b
 oth technical and non-technical users understand dataset strengths and wea
 knesses. We extend AIDRIN by adding a customizability module, allowing use
 rs to define their own metrics and remedies to evaluate and prepare data f
 or AI.\n\nTag: Research & ACM SRC Posters\n\nRecording: Not Livestreamed, 
 Not Recorded\n\nRegistration Category: Technical Program Reg Pass\n\nSessi
 on Chairs: Kento Sato (RIKEN Center for Computational Science (R-CCS)); Ch
 ris Schlipalius (Pawsey Supercomputing Research Centre; Commonwealth Scien
 tific and Industrial Research Organisation (CSIRO), Australia); and Anja G
 erbes (Georg-August-Universität Göttingen)\n\n
END:VEVENT
END:VCALENDAR