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:20260202T201229Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20251118T080000
DTEND;TZID=America/Chicago:20251118T170000
UID:submissions.supercomputing.org_SC25_sess537_drs106@linklings.com
SUMMARY:Cyberinfrastructure-Driven Spatial Decision-Making Support: Addres
 sing Participatory Collaboration and Spatiotemporal Heterogeneity
DESCRIPTION:Zhenlei Song (Texas A&M University)\n\nSpatial decision suppor
 t systems (SDSS) are pivotal in resolving complex geospatial challenges bu
 t face critical limitations in harmonizing conflicting objectives, capturi
 ng behavioral heterogeneity, and enabling efficient large-scale data proce
 ssing. Besides, a central challenge is that current Geospatial cyberinfras
 tructure (GeoCI) is inefficient in supporting real-time data access. Addit
 ionally, CI struggles to deliver scalable computations needed for addressi
 ng complex, multidimensional problems. This research addressed these limit
 ations by presenting a unified GeoCI framework powered by geospatial artif
 icial intelligence (GeoAI). Our framework provides a dual-capability platf
 orm, enabling both participatory, stakeholder-driven planning for scenario
 s like offshore wind siting, and high-fidelity, agent-based simulations fo
 r dynamic phenomena such as epidemic transmission. These sophisticated app
 lications are underpinned by an intelligent service tier where a machine l
 earning model reduces data retrieval times by over 80%, making the entire 
 system more scalable and responsive. This study provides a validated templ
 ate for building next-generation spatial data sharing systems (SDSS) that 
 can balance the needs of all stakeholders, simulate complex real-world dyn
 amics, and process massive geospatial datasets in real time, thereby achie
 ving the goals of greater efficiency, inclusiveness, and adaptability to t
 he complexities of the real world.\n\nTag: Research & ACM SRC Posters\n\nR
 ecording: Not Livestreamed, Not Recorded\n\nRegistration Category: Technic
 al Program Reg Pass\n\nSession Chairs: Kento Sato (RIKEN Center for Comput
 ational Science (R-CCS)); Chris Schlipalius (Pawsey Supercomputing Researc
 h Centre; Commonwealth Scientific and Industrial Research Organisation (CS
 IRO), Australia); and Anja Gerbes (Georg-August-Universität Göttingen)\n\n
END:VEVENT
END:VCALENDAR