College of Information Science
Computing Resources Working Group
DRAFT WORKING PACKET | October 19, 2026
Point people: Barney Maccabe | maccabe@arizona.edu; Greg Chism, Faculty Director of Instructional Computing | gchism@arizona.edu

College of Information Science: computing for research and instruction, including AI, data science, digital scholarship, games and extended reality, software, data and the people who support them.
Working resource and draft deliverables; not endorsed recommendations or a completed college assessment.

OBJECTIVES
Understand the current landscape
Identify needs and opportunities
Explore alternative approaches

DELIVERABLES

Resource inventory | Seeded draft; college entries and service-owner verification pending
Preliminary draft: End of Fall 2026 semester
inventory.html

Needs and gaps assessment | Assessment structure ready; faculty/student inputs not collected here
Preliminary draft: End of Fall 2026 semester
needs-assessment.html

Portfolio of approaches | Candidate approaches for comparison; no selection or commitment
Preliminary draft: End of Fall 2026 semester
approaches.html

Recommendations | Draft action framework; group review and priorities pending
Preliminary draft: End of Fall 2026 semester
recommendations.html

MILESTONES

October–November 2026 | Build the baseline
Confirm scope and resource owners; review campus routes; gather research, teaching and student perspectives.
Output: Versioned inventory, agreed input process and a list of unknowns.

November–end of Fall 2026 semester | Draft all four deliverables
Validate significant barriers; compare approaches; separate college actions from university dependencies.
Output: Preliminary inventory, needs assessment, portfolio and recommendations.

Early Spring 2027 | Refine and circulate within the college
Review drafts with faculty, students and resource owners; resolve corrections and agree priorities.
Output: Revised intra-college drafts with evidence, owners and unresolved questions.

As university discussions develop | Carry college priorities forward
Prepare the shared-service, policy, staffing and infrastructure questions that require university participation.
Output: College briefing for anticipated university-wide planning; timing not yet set.

USE AND REVIEW
The resource tool offers explicit submission of a reviewed public/synthetic brief and contact details to a private pilot queue for Barney and Greg. Optional Luna drafting is separate and does not persist briefs in the drafting service. The queue stores submissions and review notes until reviewers delete them; it is outside university Microsoft 365 and is not for sensitive data. Agree deliverable owner roles and the review process. No group endorsements, college-wide needs totals, staff availability or funding are assumed. The separate pilot retains its own zero-cash/four-hour constraints.

SEEDED RESOURCE INVENTORY

UITS Support | University | Available
Access: University faculty, staff and students can contact the UITS 24/7 Support Center by phone, chat or online ticket.
Cost: Basic diagnostics and fixes are available at no cost to campus community members. Repair services and specialist resources may have separate terms; confirm before use.
Contact: UITS 24/7 Support Center · 520-626-8324 · service.arizona.edu | https://it.arizona.edu/support/247-support-center
Support: Campus applications, accounts, connectivity, software installation and basic device troubleshooting; specialist needs are routed for confirmation.
Limits: General support does not guarantee RSE time, research workflow development, hardware capacity or an allocation. Repair and specialist service terms need confirmation.
Funding: University support service; specialist capacity and separate charges require confirmation.
Sources: https://it.arizona.edu/support/247-support-center
Review: 2026-10-20
Support channels and no-cost basic diagnostics verified on the UITS support page October 20, 2026. College-specific service ownership corrected at Greg Chism’s request.

College hardware, labs and loan equipment | College | Inventory pending
Access: Ask Barney Maccabe or Greg Chism to coordinate a roster of machines, locations, owners, access rules and any loan pool.
Cost: Unknown; inventory existing commitments and hours before proposing funding.
Contact: Barney Maccabe or Greg Chism — working-group point people | program.html
Support: Barney Maccabe or Greg Chism — working-group point people
Limits: No shared college CPU/GPU pool, equipment checkout entitlement or spare capacity is verified.
Funding: To document; no new funding, staff time or loan inventory assumed.
Sources: https://infosci.arizona.edu/people/barney-maccabe
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Inventory question, not a verified service entitlement. Routing contact designated by the user; profile confirms role/email.

College software, datasets and agreements | College | Inventory pending
Access: Ask the working group to identify license/data owners, storage, renewals and permitted research/classroom use.
Cost: Unknown; inventory existing commitments and hours before proposing funding.
Contact: Barney Maccabe or Greg Chism — working-group point people | program.html
Support: Barney Maccabe or Greg Chism — working-group point people
Limits: No college license roster, API allowance or training/distribution rights verified.
Funding: To document; no new funding, staff time or loan inventory assumed.
Sources: https://infosci.arizona.edu/people/barney-maccabe
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Inventory question, not a verified service entitlement. Routing contact designated by the user; profile confirms role/email.

College research labs and collaborators | College | Documented route
Access: Explore the college research-labs directory; approach the relevant lab lead for a research collaboration.
Cost: No general-use fee schedule or guaranteed shared access published.
Contact: College research-labs directory; Barney Maccabe or Greg Chism for working-group coordination | https://infosci.arizona.edu/research-faculty/research-labs
Support: College research-labs directory; Barney Maccabe or Greg Chism for working-group coordination
Limits: A lab listing establishes research capability, not open compute, staff availability or a classroom reservation.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://infosci.arizona.edu/research-faculty/research-labs
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

co/lab: Critical Archives & Curation Collaborative | College | Documented route
Access: Discuss digital curation, obsolete media/computers and digital-forensics collaborations with the co-directors.
Cost: Shared equipment access, project charges and supervision not published.
Contact: Co-directors Jamie A. Lee and Zack Lischer-Katz — lab page | https://infosci.arizona.edu/colab-critical-archives-curation-collaborative
Support: Co-directors Jamie A. Lee and Zack Lischer-Katz — lab page
Limits: Research collaboration and preservation capability; no public equipment checkout policy, GPU entitlement or staffed digitization service.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://infosci.arizona.edu/colab-critical-archives-curation-collaborative
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

XRG: Extended Reality & Games Lab | College | Documented route
Access: Discuss XR, virtual/augmented reality and interaction research with the lab leads.
Cost: No general-use equipment rate or access entitlement published.
Contact: Lila Boz and Ren Boz — lab leads listed on XRG page | https://infosci.arizona.edu/xrg-lab
Support: Lila Boz and Ren Boz — lab leads listed on XRG page
Limits: Research lab, not a documented open GPU lab or college equipment-loan service; confirm scheduling and participation.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://infosci.arizona.edu/xrg-lab
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

College course technology requirements | College | Documented route
Access: Check the program-specific minimum hardware and operating-system requirements before designing an activity.
Cost: Student-owned device requirements; no provided machine or subsidy established.
Contact: Course lead or faculty adviser; college office for routing | mailto:infosci@arizona.edu
Support: Course lead or faculty adviser; college office for routing
Limits: Requirements vary by degree. Device specifications do not establish college-owned inventory or access to loan equipment.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://infosci.arizona.edu/technology-requirements
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Campus HPC: Puma CPU and GPU | University | Documented shared allocation
Access: Registered faculty PI groups receive 150,000 CPU core-hours per PI group each month, shared by research and class groups. CPU, GPU and high-memory jobs debit the same CPU-based pool; this is not 150,000 GPU-hours. Unused hours expire at month end.
Cost: Standard allocation and HPC consulting have no charge. High-priority access requires a separate buy-in; windfall jobs are lower-priority and preemptible.
Contact: HPC Consult — ServiceNow ticket | https://uarizona.service-now.com/sp?id=sc_cat_item&sys_id=12eaba153bf9ba5017be8a8a25e45a7d
Support: HPC Consult via ServiceNow; published hours 8 am-5 pm Monday-Friday, excluding university holidays.
Limits: Published standard concurrency ceiling: four GPUs and 3,290 CPUs per group, shared across users; this is a limit, not a reservation. Shared queues give no guaranteed start time or priority for assignment deadlines. Instructors provide student support; HPC Consult helps instructors on weekdays, not weekends or university holidays. Confirm remaining PI balance, resource limits and course fit; no class reservation is established. Lynx/H200 is explicitly not available yet. Published Puma MIG memory figures differ between the table and narrative; confirm the requested device.
Funding: University standard allocation; buy-in and special-project awards have separate conditions. Local support capacity is not implied.
Sources: https://hpcdocs.hpc.arizona.edu/resources/allocations/ | https://hpcdocs.hpc.arizona.edu/resources/compute_resources/ | https://hpcdocs.hpc.arizona.edu/policies/hpc_for_instruction/ | https://hpcdocs.hpc.arizona.edu/support_and_training/consulting_services/ | https://hpcdocs.hpc.arizona.edu/running_jobs/job_limits/
Review: 2026-10-20 — current public allocation, teaching, hardware and support documentation; no signed-in balance or workload test
Current published Puma allocation and classroom permission verified directly. This does not verify Greg’s remaining balance, a course reservation, allocation renewal or staffing. A Jeremy Frumkin (UITS) slide in supplied October 14–15 briefing notes adds hardware context, not a classroom allocation or reservation; the slide lists 40 GB A100 MIG slices on Puma.

Campus HPC: Puma classroom computing | University | Class groups permitted
Access: Faculty PIs may create class groups for instruction on Puma. 150,000 CPU core-hours per PI group each month, shared by research and class groups. CPU, GPU and high-memory jobs debit the same CPU-based pool; this is not 150,000 GPU-hours. Unused hours expire at month end.
Cost: No added class allocation or dedicated class storage. Standard allocation and consulting have no charge; research and teaching share the PI pool.
Contact: HPC Consult — instructor should open a ticket | https://uarizona.service-now.com/sp?id=sc_cat_item&sys_id=12eaba153bf9ba5017be8a8a25e45a7d
Support: HPC Consult helps instructors set up class groups and troubleshoot infrastructure. Students get course support from their instructor/team; no individual student consulting is promised.
Limits: Published standard concurrency ceiling: four GPUs and 3,290 CPUs per group, shared across users; this is a limit, not a reservation. Shared queues give no guaranteed start time or priority for assignment deadlines. Instructors provide student support; HPC Consult helps instructors on weekdays, not weekends or university holidays. Confirm remaining PI balance, resource limits and course fit; no class reservation is established.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://hpcdocs.hpc.arizona.edu/policies/hpc_for_instruction/ | https://hpcdocs.hpc.arizona.edu/resources/allocations/ | https://hpcdocs.hpc.arizona.edu/registration_and_access/group_management/ | https://hpcdocs.hpc.arizona.edu/support_and_training/consulting_services/ | https://hpcdocs.hpc.arizona.edu/resources/compute_resources/ | https://hpcdocs.hpc.arizona.edu/running_jobs/job_limits/
Review: 2026-10-20 — current public teaching and allocation policies; no signed-in balance, reservation or class-load test
The current teaching policy explicitly permits Puma class groups, superseding the earlier Ocelote-only uncertainty. Specific course capacity, remaining balance, supported data and readiness still need validation. A Jeremy Frumkin (UITS) slide in supplied October 14–15 briefing notes adds hardware context, not a classroom allocation or reservation; the slide lists 40 GB A100 MIG slices on Puma.

HPC active storage and transfers | University | Documented route
Access: HPC account: 50 GB home; PI group: 500 GB communal space. Temporary xdisk on request: 200 GB–20 TB, up to 300 days.
Cost: Standard spaces supplied with account/group; rental is a separate priced service.
Contact: HPC Consult — ServiceNow ticket | https://uarizona.service-now.com/sp?id=sc_cat_item&sys_id=12eaba153bf9ba5017be8a8a25e45a7d
Support: HPC Consult — ServiceNow ticket
Limits: HPC data are not backed up; xdisk is temporary and node /tmp is cleared after a job. Storage quotas do not provide preservation or regulated-data approval.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://hpcdocs.hpc.arizona.edu/storage_and_transfers/storage/hpc_storage/ | https://hpcdocs.hpc.arizona.edu/support_and_training/consulting_services/
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

HPC software, containers and shared model data | University | Documented route
Access: Use HPC modules, user environments and containers; shared datasets include Llama 2 and AlphaFold inputs.
Cost: Open-source tools may have no license charge; licensed products and model terms still apply. Compute uses the allocation.
Contact: HPC Consult — software/setup questions | https://uarizona.service-now.com/sp?id=sc_cat_item&sys_id=12eaba153bf9ba5017be8a8a25e45a7d
Support: HPC Consult — software/setup questions
Limits: Availability varies by module/version. Llama 2 has its own community license; model memory/storage requirements can be substantial. A software listing is not permission for every use.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://hpcdocs.hpc.arizona.edu/software/common_datasets/ | https://hpcdocs.hpc.arizona.edu/software/overview/ | https://hpcdocs.hpc.arizona.edu/software/popular_software/ollama/ | https://hpcdocs.hpc.arizona.edu/support_and_training/consulting_services/
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

HPC consulting and visualization support | University | Documented route
Access: Open a ServiceNow ticket for onboarding, queue issues, code optimization and resource advice; request visualization help through its team.
Cost: HPC consulting is published as free of cost.
Contact: HPC Consult ticket; visualization: vislab-consult@list.arizona.edu | https://uarizona.service-now.com/sp?id=sc_cat_item&sys_id=12eaba153bf9ba5017be8a8a25e45a7d
Support: HPC Consult ticket; visualization: vislab-consult@list.arizona.edu
Limits: HPC team support hours: weekdays 8 a.m.–5 p.m., excluding university holidays. Consultation is not an assigned engineer or individualized student homework support.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://hpcdocs.hpc.arizona.edu/support_and_training/consulting_services/ | https://hpcdocs.hpc.arizona.edu/policies/hpc_for_instruction/
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

AI Verde → Arizona AI Assistant: planned transition | University | ORAI transition update; timing to confirm
Access: Wolfgang Jentner at the Office of Responsible AI (ORAI), via Greg Chism, reports AI Verde will be sunset in favor of Arizona AI Assistant. Use the new portal to check sign-in, API access and enrollment; migration timing and eligibility need confirmation.
Cost: Planned $200/month of AWS Bedrock credit, reported by Wolfgang Jentner at ORAI and relayed by Greg Chism on October 19, 2026. Confirm who receives the allowance, renewal, covered usage and overage controls; not an unlimited compute or GPU-training allocation.
Contact: Wolfgang Jentner · Office of Responsible AI (ORAI) · wjentner@arizona.edu | mailto:wjentner@arizona.edu
Support: Wolfgang Jentner · Office of Responsible AI (ORAI) · wjentner@arizona.edu
Limits: Supplied ORAI pricing screenshot lists 12 hosted models and per-token prices. These campus gateway rates differ from direct-provider rates. Credit is not transferred to this site’s OpenAI API; API compatibility, data rules, class concurrency and migration/export still need confirmation.
Funding: Campus Bedrock credit reported by Wolfgang Jentner at ORAI, via Greg Chism; allocation level and renewal terms to confirm.
Sources: https://ai-assistant.responsibleai.arizona.edu/ | https://news.arizona.edu/employee-news/guide-ai-tools-u | https://cyverse.org/ai-verde | https://responsibleai.arizona.edu/about-orai/directory
Review: 2026-10-19 — ORAI transition/credit update and pricing screenshot from Wolfgang Jentner, relayed by Greg Chism; portal HTTP 200, no signed-in entitlement test
Public university news describes Arizona AI Assistant as a fall pilot and AI Verde separately. The transition and $200/month credit come from Wolfgang Jentner at ORAI, relayed by Greg Chism; individual entitlements have not been tested. Pricing screenshot received October 19; its capture/effective date is unconfirmed. Confirm live account rates. Primary contact corrected at Greg Chism’s request October 20. ORAI directory confirms the spelling Wolfgang Jentner and wjentner@arizona.edu; primary service responsibility is user-confirmed.

U of A GenAI | University | Documented route
Access: Active UArizona NetID; published FAQ describes limited early access. Check genai.arizona.edu for availability.
Cost: Published no-cost campus use.
Contact: Responsible AI tools page and campus 24/7 IT support: 520-626-8324 | https://responsibleai.arizona.edu/tools-support/u-gen-ai
Support: Responsible AI tools page and campus 24/7 IT support: 520-626-8324
Limits: Models/features may rotate; no guaranteed API, classroom concurrency or GPU-training allocation. Early-access conditions and data-specific exclusions apply; this differs from AI Verde.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://responsibleai.arizona.edu/tools-support/u-gen-ai | https://it.arizona.edu/student-resources | https://responsibleai.arizona.edu/ai-tools-guide
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Campus software licensing | University | Documented route
Access: Use the UITS software catalog and student/faculty service routes; check each product and affiliation.
Cost: Student page lists Microsoft 365, Google Apps and Adobe Creative Cloud without added software charge while enrolled; other products are free or discounted. Student services are supported by the IT & Library Fee.
Contact: UITS 24/7 support — 520-626-8324 | https://it.arizona.edu/student-resources
Support: UITS 24/7 support — 520-626-8324
Limits: Eligibility, device counts, renewal and commercial/research use vary. Listed MATLAB/Autodesk etc. do not imply every license or API credit is included.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://it.arizona.edu/student-resources | https://it.arizona.edu/node/616
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

VCAT and Tech Zone software access | University | Documented route
Access: VCAT supplies virtual applications through a browser; Tech Zone labs provide installed software. Instructors can request a lab software installation.
Cost: Campus student-service route; fee-supported. Product-specific access and installation charges, if any, must be checked.
Contact: UITS 24/7 support — 520-626-8324 | https://it.arizona.edu/tech-zone-software
Support: UITS 24/7 support — 520-626-8324
Limits: App/version and lab availability vary; not a general-purpose GPU allocation, unrestricted server or always-on research host.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://it.arizona.edu/tech-zone-software | https://it.arizona.edu/news/finding-resources-faculty | https://it.arizona.edu/student-resources
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Libraries Data Cooperative: Python, R and ML support | University | Documented route
Access: Faculty, staff and students can consult library specialists on data science, visualization, programming and data management.
Cost: No project-specific fee or dedicated engineering allowance established by these pages.
Contact: Sarah Stueve — sarahstueve@arizona.edu (Python/ML); Jeff Oliver — jcoliver@arizona.edu (R/Git/visualization) | https://lib.arizona.edu/research/data
Support: Sarah Stueve — sarahstueve@arizona.edu (Python/ML); Jeff Oliver — jcoliver@arizona.edu (R/Git/visualization)
Limits: Consultation, instruction and referrals; no dedicated developer hours, turnaround or ongoing operations commitment.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/research/data | https://lib.arizona.edu/research/data/data-science
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Digital scholarship and text/data mining | University | Documented route
Access: Consult about corpora, text analysis, humanities data, metadata and digital editing; listed open tools include OpenRefine, Voyant, AntConc and CollectionBuilder.
Cost: Listed tools are free to use; sustained project implementation/support not priced here.
Contact: Heather Froehlich — froehlich@arizona.edu | mailto:froehlich@arizona.edu
Support: Heather Froehlich — froehlich@arizona.edu
Limits: Tool availability does not clear copyright, dataset licensing, hosting, compute or staff time.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/research/data/digital-scholarship | https://lib.arizona.edu/research/plan/tdm-llm
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Library datasets, databases and reuse rights | University | Documented route
Access: Use licensed resources under current UA affiliation and the specific agreement. Contact Collections before TDM or use with AI.
Cost: Institutional subscriptions cover authorized access; additional TDM/API rights or fees depend on the agreement.
Contact: Library Collections — LBRY-collectionmanagement@email.arizona.edu | mailto:LBRY-collectionmanagement@email.arizona.edu
Support: Library Collections — LBRY-collectionmanagement@email.arizona.edu
Limits: Reading access does not authorize bulk download, sharing, training or uploading to public AI tools. Each publisher agreement differs.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/research/plan/tdm-llm
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

GIS software, geospatial data and consultation | University | Documented route
Access: Use the Libraries GIS/data guides and repository; discuss ArcGIS, QGIS, R and spatial analysis with a specialist.
Cost: QGIS is open source; ArcGIS eligibility and project-specific data/service terms require checking. No universal paid-product entitlement inferred.
Contact: Garrett Smith — garrettsmith@arizona.edu | mailto:garrettsmith@arizona.edu
Support: Garrett Smith — garrettsmith@arizona.edu
Limits: Data licenses, service quotas and support capacity differ. A geospatial repository is not a general GPU or database-hosting award.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/research/data/geospatial | https://lib.arizona.edu/research/data
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

ReDATA: research data and code preservation | University | Documented route
Access: Active faculty/staff, enrolled students and certain DCCs with valid NetID/library privileges can submit eligible final research materials for curatorial review.
Cost: FAQ: no cost to individual UArizona researchers; quota increases depend on need and availability.
Contact: ReDATA team — data-management@arizona.edu | mailto:data-management@arizona.edu
Support: ReDATA team — data-management@arizona.edu
Limits: Non-sensitive research materials and rights required; curatorial review mandatory. Not an active database/backup service. Published notice reports intermittent traffic-related errors and automated download restrictions; not a breach.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/research/data/redata | https://lib.arizona.edu/research/data/redata/faqs | https://lib.arizona.edu/research/data/redata/deposit
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

Data Science Institute / CyVerse research software expertise | University | Contact reconfirmation needed
Access: Indexed official DSI pages describe project/proposal consultation and cross-college teams; their live hostnames did not resolve during this review. Reconfirm the current route before relying on it.
Cost: No blanket free engineering-hour entitlement or public project rate established; scope and funding must be agreed.
Contact: Published DSI contact — RII-datascienceinstitute@arizona.edu (current operation to reconfirm) | mailto:RII-datascienceinstitute@arizona.edu
Support: DSI — RII-datascienceinstitute@arizona.edu
Limits: Named engineering expertise is not an available appointment or staffed help desk for every course. Confirm capacity, deliverables, maintenance and funding.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://data7.arizona.edu/contact-us | https://datascience.arizona.edu/directory
Review: 2026-10-19 — indexed official text retrieved; direct live verification unsuccessful
Official-source search/fetch text supplied the contact and engineering roles, but direct checks of data7.arizona.edu and datascience.arizona.edu failed DNS resolution. This is an availability limitation, not evidence of service closure. No available staff hours verified.

CCT Data Science: consultation and research software | University | Documented route
Access: Drop-in/workshop routes and grant collaboration documented. The 80-hour Data Science Incubator is limited to ALVSCE faculty, staff and students.
Cost: Longer collaboration can use hired effort or a co-PI grant arrangement; Information Science eligibility for other services and rates must be confirmed.
Contact: CCT Data Science team — current contact/consultation routes | https://datascience.cct.arizona.edu/
Support: CCT Data Science team — current contact/consultation routes
Limits: The ALVSCE incubator is not an 80-hour entitlement for Information Science. Training/drop-in help differs from funded long-term engineering.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://datascience.cct.arizona.edu/
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

CATalyst Studios: XR, making and class partnerships | University | Documented route
Access: Use Main Library makerspace hours, reserve eligible spaces/VR equipment, or plan a class visit with the team.
Cost: Free workshops are advertised; material/equipment-specific charges and eligibility must be checked.
Contact: CATalyst Studios — contact and consultation booking | https://lib.arizona.edu/catalyst/contact
Support: CATalyst Studios — contact and consultation booking
Limits: Some machines require authorization classes. Reservations, supervision and supplies constrain access; no general-purpose compute/GPU reservation inferred.
Funding: Institutional or project service; dedicated college capacity/funding not established.
Sources: https://lib.arizona.edu/catalyst | https://lib.arizona.edu/catalyst/contact
Review: 2026-10-19 — public documentation; no signed-in entitlement or owner confirmation
Access route, published cost basis and contact checked in public sources. Unpublished quotas, staffing and college capacity remain unknown.

AI tools and data-use guidance | University | Documented route
Access: Review the current university decision table before selecting a tool.
Cost: Public guidance; project review effort must be scoped.
Contact: Responsible AI campus support and current training organizers | https://responsibleai.arizona.edu/
Support: University AI, privacy and relevant data owners.
Limits: Data categories and account types matter; do not infer authorization from a vendor privacy claim.
Funding: University guidance; not a compute or staff allocation.
Sources: https://responsibleai.arizona.edu/ai-tools-guide
Review: 2026-10-19
Published guidance/training route only; not a compute or staff allocation.

Campus AI learning and events | University | Documented route
Access: Follow the university AI resources page for training and event routes.
Cost: Check each offering; staff learning time is still required.
Contact: Responsible AI campus support and current training organizers | https://responsibleai.arizona.edu/
Support: University AI learning and event organizers.
Limits: A course/event is not staffed project support or a reserved technical service.
Funding: University initiative; event availability varies.
Sources: https://it.arizona.edu/news/new-u-ai-resources
Review: 2026-10-19
Published guidance/training route only; not a compute or staff allocation.

NSF ACCESS | National / external | Application / approval
Access: Match the project and teaching/research use to a resource and request.
Cost: Allocated resource access is conditional; operations/support remain separate.
Contact: ACCESS support and selected resource provider | https://access-ci.org/
Support: ACCESS support plus the selected resource provider.
Limits: No award, class reservation or provider benchmark established.
Funding: Federally supported allocation route.
Sources: https://access-ci.org/
Review: Earlier compute-ledger review; not newly rechecked
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

NAIRR Classroom | National / external | Application / approval
Access: Check the current instructor/course call and resource terms.
Cost: Conditional award/resource terms; not funding in hand.
Contact: NAIRR program / current Classroom call | https://nairrpilot.org/
Support: Program and resource-specific support.
Limits: An eligible AI pilot does not supply every course or its ongoing staff support.
Funding: Federal pilot opportunity.
Sources: https://nairrpilot.org/
Review: Earlier compute-ledger review; recheck call before use
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

OSPool / throughput computing | National / external | Documented route
Access: Assess independent, checkpointed research jobs and facilitated onboarding.
Cost: Opportunistic use subject to policy and available capacity.
Contact: OSPool facilitation / support | https://osg-htc.org/ospool/
Support: OSG/OSPool support route.
Limits: Interruptions and queue behavior differ from live classroom sessions.
Funding: Federally supported/shared infrastructure.
Sources: https://osg-htc.org/ospool/
Review: Earlier compute-ledger review; recheck before use
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

MESA / CyVerse collaboration | National / external | Project / service terms
Access: Explore public service and collaboration routes; confirm underlying access.
Cost: Service-specific; no free college compute entitlement inferred.
Contact: MESA project team / underlying service provider | https://idss-mesa.github.io/
Support: Project/platform maintainers; commitments to confirm.
Limits: Grant participation and advertised products do not establish approved class capacity.
Funding: IDSS/project and underlying service support differ.
Sources: https://idss-mesa.github.io/
Review: Earlier compute-ledger review; recheck before use
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

Free GPU and cloud-credit experiments | National / external | Bounded / conditional
Access: Compare Kaggle, free Colab and credit-based platforms in the existing directory.
Cost: Quotas, cards and paid conversion vary.
Contact: Provider-specific help routes in comparison | classroom-resources.html
Support: Provider/community support; no class support commitment.
Limits: Useful for bounded experiments; not a guaranteed full-term GPU reservation.
Funding: Provider-sponsored tiers or promotional credits.
Sources: classroom-resources.html
Review: Earlier compute-ledger review; recheck before use
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

Repositories, databases and preservation | National / external | Service-specific
Access: Match code, active databases, research deposits and archival needs separately.
Cost: Storage, activity and hosting limits vary.
Contact: Service-specific contacts in continuity plan | repository-plan.html
Support: Institutional librarians, data owners and hosting operators.
Limits: Compute allocations do not automatically provide durable databases or preservation.
Funding: Institutional and provider arrangements differ.
Sources: repository-plan.html
Review: Earlier compute-ledger review; recheck before use
Earlier source-ledger review; current resource-owner access, cost and contact not newly verified in this campus expansion.

# Needs and gaps assessment

**Draft framework — no college-wide findings established.** The resource inventory and historical provider changes identify questions to examine; they do not establish the size or distribution of college needs.

[Prepare and optionally submit a need](needs.html) · [Download blank needs register](computing-needs-register.csv)

## Questions to investigate

| Area | What we need to learn | Useful evidence |
| --- | --- | --- |
| Compute and cloud | Which activities need local devices, interactive sessions, batch jobs, GPUs or hosted models? | Small measured workloads, access delays and required concurrency |
| Software and models | Which licenses, APIs, environments and accessible interfaces are required? | Current agreements, use cases, compatibility and renewal terms |
| Data | Which datasets, rights, metadata, storage and preservation services are missing? | Data inventories, permissions, stewardship and export/restore needs |
| RSEs and support | Which skills and support windows are required, and what capacity is actually available? | Task estimates, existing commitments and service-owner confirmation |
| Research and instruction | How do research schedules, class deadlines and student access differ? | Course/project scenarios and faculty/student perspectives |
| Collaboration | What can be shared or improved before adding infrastructure? | Underused resources, compatible workflows and willing partners |

## Assess a reported gap

Distinguish **not available**, **not accessible**, **not known about**, **not supported**, **not suitable** and **not affordable**. They require different responses.

For each need, capture who is affected, the activity being blocked, current workaround, timing and evidence. Compare it with a verified resource route. A technical shortage should be distinguished from permissions, onboarding, skills or support barriers.

## Summarize responsibly

Report which parts of the college and which roles contributed, the number of usable inputs and important missing perspectives. Keep measured demand, self-reported needs, estimates and unanswered questions separate. Do not scale a few examples into college-wide GPU, spending or staffing totals.

## Ready for a preliminary draft when…

The group has a versioned needs register, a documented account of participation, significant gaps linked to evidence, and a clear list of remaining unknowns. Refine these with faculty, students and resource owners early in Spring 2027.

## Review submitted briefs

Barney Maccabe and Greg Chism can use the [private pilot queue](https://infosci-compute-drafter.vercel.app/review/) to review explicitly submitted public/synthetic briefs, add a status and notes, and export or delete requests. Contact addresses are self-reported. Submission does not imply approval, capacity or an allocation; internal and restricted information needs an agreed university channel.


# Primers for the working group

Six starting points for discussing computing resources across the **College of Information Science**. Use the questions to identify evidence and a useful next step.

## 1. Start with the activity

An interactive class, a batch research job, a hosted model and a public website need different services. A GPU is one component; memory, software, storage, accounts and support can be the actual constraint.

**Discuss:** What must people be able to do, when, and with how many simultaneous users?

[Develop a brief](needs.html) · [Optional technical estimate](compute-estimator.html)

## 2. Separate availability from dependable access

A free account or published machine specification does not reserve capacity or authorize classroom use. Research tolerates some queues; a scheduled class may not. Puma now permits class groups, but teaching and research share the PI allocation. Jobs may queue without deadline priority, and instructors support students.

**Discuss:** Who is eligible, what is guaranteed, and what happens when access fails?

[Resource inventory](inventory.html) · [Classroom checks](readiness.html)

## 3. Count the people and recurring work

Allocations and credits do not automatically supply research software engineers (RSEs), onboarding, accessible interfaces, course support or a backup operator. Estimate tasks and hours before proposing a staffing or funding model.

**Discuss:** Who maintains the service, supports users and handles renewals and recovery?

[Candidate approaches](approaches.html) · [Pilot hours and grant dependencies](budget.html)

## 4. Treat data, software and preservation separately

Code repositories, licensed datasets, active storage, databases and preservation repositories have different purposes. Check rights, permitted data, exports and restore. A working copy is not an independent backup or a scholarly archive.

**Discuss:** What may be stored or shared, who owns it, and how will it outlast the account?

[Repositories, hosting and data](repository-plan.html) · [Campus data and software services](inventory.html)

## 5. Compare routes by the whole commitment

Use existing campus services, shared infrastructure, efficient workflows and national allocations where they fit. Free tiers and promotional credits can support bounded experiments; an operating service also needs ownership, support and continuity.

**Discuss:** What small, reversible test would distinguish the promising options?

[Federal platforms](federal-compute.html) · [Cloud credits and limits](serverless-compute.html) · [Classroom 50](classroom50.html)

## 6. Keep the evidence proportional

A self-reported need, an estimate, a benchmark and an owner-confirmed commitment are different evidence. A few examples cannot establish college-wide demand, savings or available staffing.

**Discuss:** Whose perspective is missing, what is measured, and which claims still need confirmation?

[Needs assessment framework](needs-assessment.html) · [Report and limitations](report.html#evidence-and-limitations)

## A useful output from a discussion

Record **the activity → the barrier → a route to investigate → a person who can confirm it → the next useful test**. Keep unknowns visible. The [working materials](supplemental.html#working-group-materials) provide the registers and review framework.


# Portfolio of approaches

**Candidates for investigation, not selected investments.** Combine approaches when useful; compare their support and recurring obligations as carefully as their technical benefits.

| Approach | Opportunity | First useful test | Main dependency |
| --- | --- | --- | --- |
| Improve use of campus resources | Reduce duplicate purchases and onboarding friction | Map one research and one teaching workflow to documented campus routes | Eligibility, headroom, support and class-use terms |
| Shared RSE and technical support | Pool scarce expertise and reusable environments | Estimate a few tasks and trial a bounded support window | Named staff, existing commitments and funding; no new appointment assumed |
| Shared data and software stewardship | Reuse datasets, metadata and environments safely | Review a dataset/license and test a portable workflow | Rights, permissions, accessibility and renewal ownership |
| Allocation-backed compute service | Support larger CPU/GPU work without relying only on free tiers | Benchmark components and validate a target route | An award, operations capacity and provider terms; ACCESS pilot remains conditional |
| Efficient models and workflows | Lower unnecessary compute and improve reproducibility | Compare a smaller model, retrieval approach or checkpointed job against a quality baseline | Task-specific evaluation; savings must be measured |
| Partnerships and shared infrastructure | Connect compatible college, campus and external efforts | Define a small joint use case with an interested partner | Agreed responsibilities, access and sustainable support |
| Reusable teaching and evaluation tools | Avoid rebuilding assignment environments and grading workflows | Test exports and a synthetic class before adoption | Maintainer continuity, account terms and separate compute quotas |

## Planned ORAI proposal

Greg will draft a bounded [AI Innovation Pilot](https://responsibleai.arizona.edu/tools-support/ai-innovation-pilots) next, showcasing ORAI tools alongside his infrastructure components in an **AI-native classroom**. A separate proposal will be drafted next. His capacity is **four hours/week total**. The program offers a potential eight-week proof-of-concept route after assessment; acceptance, RSE assignments and infrastructure must be confirmed. Ongoing maintenance and classroom operations need their own plan.

## Use one comparison standard

For each candidate, document instructional/research benefit, users served, accessibility, data suitability, required effort, recurring costs, funding status, ownership and a reversible test. Do not rank options using invented cost savings or unmeasured capacity.

[Draft recommendations](recommendations.html) · [Resource inventory](inventory.html) · [Supporting compute pilot](pilot-plan.html)

## Drafting support

The [resource tool](needs.html) prepares a local brief and sourced request template. Optional Luna drafting needs explicit consent for public/synthetic material. [Technical assessment, limits and model trials](drafting-notes.html) are supplementary.


# Resource-request drafting notes

Supporting assessment of the request tool. Start with the [resource tool](needs.html) for use, or the [report](report.html) for the main findings.

## Help prepare resource requests

The [needs tool](needs.html) offers a source-backed local template and an optional **GPT-6 Luna** rewrite after explicit consent for public/synthetic information. Luna uses a server-side credential and a shared allowance: 20 attempts/day, 200/month, five/network/day, up to 1,000 output tokens each. Attempts reserve $0.005 of the application allowance before calling the model, limiting this service to $1/month in reservations at current verified rates. This is separate from account-wide billing and hosting. Failed or timed-out calls are not retried automatically.

For a manual campus route, use [Arizona AI Assistant](https://ai-assistant.responsibleai.arizona.edu/). Wolfgang Jentner at ORAI reports an AI Verde transition and $200/month of Bedrock credit, relayed by Greg Chism; [review the credit boundaries and supplied model rates](campus-ai.html). [U of A GenAI](https://responsibleai.arizona.edu/tools-support/u-gen-ai) remains another documented route. Campus API integration and credit use have not been tested here.

### Browser-model assessment

Browser inference works without API keys or per-request inference fees. We tested two quantized SmolLM2 models on synthetic examples in Chromium on this machine. The 135M model invented student-record details; a 360M model produced short drafts in about 9–13 seconds, but an integrated example added an unsupported participant condition and weakened unknown-hours language. Its initial model/runtime download was about 390 MB. These examples are a small feasibility check, not a general ranking of browser models.

The integrated 360M worker generated with networking blocked after loading. That establishes local execution for that test; it does not establish reliable drafting. Browser inference remains disabled on the public site. The local template, optional hosted Luna draft and manual campus prompt are separate routes. The [SmolLM2 model card](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct) also advises checking generated content. Preserve original quantities, source facts and unknowns in every draft.

### GPT-6 Luna drafting test

On October 19, 2026, **GPT-6 Luna** completed three synthetic requests—data science instruction, MLIS data work and research software support—in **5.6–6.0 seconds each**. Review against supplied briefs and dated inventory facts found that all three preserved unknown costs, staffing, permissions and capacity. Drafts were 135–163 words and kept questions for resource owners separate.

**Assessment: useful first drafts with human review.** This was three examples with facts supplied, not a reliability guarantee or a matched comparison with browser models. Total usage was 4,157 input and 1,032 output tokens; estimated token charges were **about $0.001**, including reported cache writes, using [published standard rates](https://developers.openai.com/api/docs/models/gpt-6-luna). This is an estimate, not a verified invoice. That initial test established no institutional approval or college operating budget. The subsequent optional integration has its own usage limits and deployment checks.

## Optional submission and review

The resource tool now has a separate, explicit submission step. Public/synthetic briefs and contact details can be stored in a private pilot queue for Barney and Greg, using the existing hosting. Luna drafting never submits automatically and contact details are not sent to the model. Reviewers use a shared passphrase, update status and notes, export requests, and delete entries when no longer needed. This is not NetID, a sensitive-data intake or an allocation application.


# Arizona AI Assistant transition

**AI Verde → [Arizona AI Assistant](https://ai-assistant.responsibleai.arizona.edu/).** **Wolfgang Jentner at the Office of Responsible AI (ORAI)** is the source of this planned transition and **$200/month of AWS Bedrock credit**, relayed by Greg Chism. Transition date, who receives the credit, eligibility, renewal and overage controls need confirmation. This is an October 19, 2026 working-group update, not a verified entitlement for every faculty member or student.

Public [university news](https://news.arizona.edu/employee-news/guide-ai-tools-u) describes Arizona AI Assistant as a fall pilot and AI Verde separately. The new portal returned HTTP 200; we have not tested a signed-in account or campus API. Contact **[Wolfgang Jentner at ORAI](mailto:wjentner@arizona.edu)** for AI Verde, Arizona AI Assistant and Bedrock for current enrollment, migration and credit terms.

## Models and prices in the supplied screenshot

USD per **one million tokens**. These are campus gateway prices in the ORAI screenshot from Wolfgang Jentner, relayed by Greg Chism, not direct OpenAI prices or measured bills. Check current account rates before use.

| Model ID | Input | Output |
| --- | ---: | ---: |
| `gpt-5.6-luna` | $0.22 | $1.32 |
| `gpt-5.6-sol` | $4.40 | $22.00 |
| `gpt-6.1-sol` | $2.20 | $11.00 |
| `claude-haiku-4-5-20251001` | $1.10 | $5.50 |
| `claude-opus-5` | $5.50 | $27.50 |
| `claude-opus-5-5` | $4.40 | $22.00 |
| `claude-sonnet-5` | $2.20 | $11.00 |
| `gpt-5.6-terra` | $2.20 | $13.20 |
| `gpt-6-luna` | $0.11 | $0.55 |
| `claude-haiku-5-5` | $0.11 | $0.55 |
| `claude-sonnet-5-5` | $2.20 | $11.00 |
| `google.gemma-4-31b` | $0.14 | $0.40 |

[View supplied pricing screenshot](guide-assets/campus-ai-pricing-2026-10-19.png) · Received October 19, 2026; capture and effective dates are unconfirmed.

For example, at the listed campus Luna rate, **10,000 input + 1,000 output tokens = $0.00165** before any other charges. This is illustrative arithmetic, not an observed bill or promised credit balance. Credit provides model inference, not a reserved GPU, training cluster or guaranteed class concurrency.

## Before relying on the replacement

- Confirm migration timing, existing team/workspace exports, API compatibility and the correct API base URL.
- Confirm whether $200/month is per person, team or another allocation; determine reset, expiry and overage behavior.
- Review allowed data, retention, model availability and throughput under campus terms.
- Test one public/synthetic workflow and a classroom rehearsal before required use.

The [resource request tool](needs.html) currently uses the separate direct OpenAI Luna pilot. Its $1 monthly application allowance does not draw from campus Bedrock credit. Campus integration needs a campus-issued credential and confirmed API terms.

[Resource inventory](inventory.html) · [Drafting assessment](approaches.html)

Primary contact confirmed by Greg Chism on October 20, 2026; spelling and email verified in the [university directory](https://responsibleai.arizona.edu/about-orai/directory).


# Recommendations for review

**Draft action framework — priorities and endorsement pending.** The working group should refine these using the inventory and faculty/student needs, rather than assume a single platform solves the problem.

## Actions the college can pursue

1. **Maintain a concise resource inventory.** Identify an owner role for each entry and a review process. Publish access routes and limitations that resource owners confirm.
2. **Document needs across research and instruction.** Use consistent briefs and an agreed university channel; include faculty, students, RSEs and technical staff. Summarize participation and unknowns.
3. **Improve discoverability and reuse.** Test clear onboarding, reusable environments, shared documentation and relevant training before expanding infrastructure.
4. **Scope bounded pilots.** Match a small activity to a confirmed route and support window. Measure benefit, access, effort and recovery before making it required.

## Opportunities for university participation

| Shared question | College contribution | What needs university participation |
| --- | --- | --- |
| Campus compute and hosted AI access | Concrete research/classroom scenarios and measured demand | Capacity, course access, account structure and service commitments |
| Software, APIs and data agreements | Priority tools, datasets, rights and renewal needs | Institutional agreements, permitted use and sustainable funding |
| RSE and technical support models | Skill/task estimates and existing college commitments | Shared staffing, escalation, training and long-term operations |
| Data governance and shared infrastructure | Workflow, preservation and collaboration requirements | Appropriate review, interoperability and institutional services |

## Before prioritizing an action

Attach the problem and evidence, users served, owner role, dependencies, effort, funding status, success measure and a review date. Explicitly distinguish an application, exploratory partnership or proposed role from a confirmed commitment.

The existing pilot’s **$0 cash and Greg’s 10 total hours/week** apply to that pilot. They are not a measured college budget or staffing ceiling. Do not assume funding or available staff for these broader recommendations.

[Recommendation template](computing-recommendations-template.csv) · [Needs assessment](needs-assessment.html) · [Milestones](timeline.html)


# Run a working session

Use a short, repeatable review. This is a suggested meeting format, not a scheduled event or an assigned set of roles.

## Before the session

Choose a deliverable and review its current draft. Bring a public or appropriately shareable resource correction or needs brief. Use the group’s agreed university channel for internal material; the resource tool’s separate submission step accepts only reviewed public/synthetic briefs into the private pilot queue.

## Suggested 45-minute agenda

| Minutes | Activity | Record |
| --- | --- | --- |
| 0–5 | Confirm the decision or question | Scope and intended outcome |
| 5–15 | Review resources and access | Verified facts, owners and unknowns |
| 15–25 | Discuss needs and barriers | Research/teaching differences and missing perspectives |
| 25–35 | Compare promising approaches | Evidence, prerequisites and a useful small test |
| 35–45 | Agree next steps | Action, owner role, dependencies and review point |

## After the session

Update the draft’s date and status. Separate a decision from an open question or suggested action. Record who needs to confirm access, costs, support or permissions; do not list an unconfirmed resource as ready.

## Questions for the group to settle first

- Who maintains each deliverable and confirms factual corrections?
- Which approved university channel will receive needs briefs and internal notes?
- How will faculty, students and technical staff contribute, and how will missing perspectives be recorded?
- Who will review the preliminary drafts before early Spring 2027 circulation?

[Four deliverables](deliverables.html) · [Working packet](computing-working-group-packet.txt)