Operations
AuraScore 81/100

Multi-Site Collaborative Grant Research Operations Activation Checklist

Validate operational readiness, regulatory IRB harmonization, and financial workflows across multi-institutional research consortiums.

Deploy this checklist prior to disbursing grant funds and activating decentralized research sites across university partner networks. It ensures harmonized compliance, automated reporting conduits, and clear operational risk ownership.

Template

Role: Senior Director of Sponsored Research Operations specializing in multi-institutional academic consortium governance and compliance lifecycle management.

Context

  • Lead Academic Institution: {{lead_institution}}
  • Sponsoring Agency: {{funding_agency}}
  • Participating Consortium Sites: {{consortium_partners}}
  • Data Governance Standard: {{data_governance_model}}
  • Ethics Oversight Model: {{irb_approval_scope}}
  • Total Grant Award Cap: {{milestone_budget_cap}}

Task

Construct an end-to-end operational activation and readiness checklist to govern site onboarding, ethics clearance harmonization, financial conduits, and data-sharing readiness across {{consortium_partners}} sponsored by {{funding_agency}}.

Method

  1. Establish legal readiness checks including fully executed Subaward Agreements, Memoranda of Understanding (MOUs), and intellectual property terms.
  2. Verify Institutional Review Board (IRB) or ethics reciprocity alignments under {{irb_approval_scope}} across all partner jurisdictions.
  3. Formulate financial disbursement milestones ensuring cost-share tracking and invoicing adhere to {{milestone_budget_cap}} and {{funding_agency}} rules.
  4. Design data ingestion, pseudonymisation, access control, and storage validation checkpoints aligned with {{data_governance_model}}.
  5. Standardize site personnel onboarding, verifying credentialing, Conflict of Interest (COI) declarations, and Good Clinical/Research Practice certifications.
  6. Detail protocol adherence monitoring and periodic audit schedule verification across all decentralized testing sites.
  7. Establish risk mitigation triggers for subcontract non-performance, budget burn anomalies, or ethics non-compliance.

Constraints

  • Checklist items MUST establish clear boundary criteria between the responsibilities of {{lead_institution}} and {{consortium_partners}}.
  • MUST NOT permit site activation or fund disbursement without verified ethics clearance under {{irb_approval_scope}}.
  • Invoicing and fiscal tracking checks must link directly to demonstrable deliverables.
  • All items must include concrete documentary proof requirements (e.g., signed sIRB Authorization Agreement, Data Transfer Agreement).

Output format

  • Domain 1: Legal, Subaward & Consortium Contracts (5 items)
  • Domain 2: Regulatory & Ethics (IRB/IACUC) Reciprocity (5 items)
  • Domain 3: Data Infrastructure & Governance Readiness (5 items)
  • Domain 4: Fiscal Management & Sub-Recipient Monitoring (5 items)
  • Domain 5: Site Go-Live Final Authorization Gate (4 items)
  • Format: [ ] [Gate #] Requirement | Responsible Entity | Mandatory Artifact | Approval Criteria | Risk Level

Self-review

  • Ensure the scope of {{irb_approval_scope}} covers every individual site listed in {{consortium_partners}}.
  • Confirm financial milestones do not exceed {{milestone_budget_cap}} limits and comply with {{funding_agency}} guidelines.
  • Check that data pipeline security controls satisfy {{data_governance_model}} across all site endpoints.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

business-strategy
business-operations
education-research
research-administration
grant-management
consortium-operations