ScholarVault
Define the decision before designing the tool
A university may be deciding whether to fund attendance, permit a submission, recommend an opportunity or record an academic output. Those decisions need overlapping evidence but have different owners. A shared form should state which decision it supports.
Start with a small pilot in one department. Ask participants to bring an actual research question and a candidate event. Use the exercise to find missing evidence and unclear handoffs. Do not begin with a claim that every faculty member will save a fixed number of hours.
Countries represented in ScholarVault’s search audience include India, the United States, Oman, Kenya, Malaysia and South Africa, with further interest from the UK, Philippines, Indonesia and Canada. This informs the reading series; it does not establish university partnerships or product adoption.
Use a common evidence core and local rules
Keep a common core: event identity, official edition URL, dates, contribution type, publication claim, supporting source and check date. Add local fields for the institution’s own approvals and appraisal requirements. Do not apply one country’s promotion scoring system to another.
UKRI’s publication guidance illustrates that funder requirements can include open access, acknowledgement and research-data practice. These requirements apply in the relevant funding context, not automatically to every international researcher. [1]
A university team in any country should therefore record its own policy source and ask the appropriate office to resolve questions. The core evidence record supports that discussion; it does not replace institutional expertise.
Give uncertainty a visible place
Use three evidence states: confirmed, unresolved and not applicable. Keep the reason beside the state. “No official deadline found” is more actionable than a red score with no explanation. “Earlier edition proceedings found” should not become “current edition publication guaranteed”.
Assign the next action to a person: the student checks the edition, the supervisor reviews fit, the library helps evaluate a publication claim and the research office handles the institution’s approval process. Adapt these roles to your actual organisation.
The point is accountability for the next step, not a universal bureaucracy. A short consultation may be enough for a straightforward case; a confidential or disputed claim may need a specialist review.
Measure the pilot honestly
Track how many records have an official source, how many questions remain unresolved and how long a decision takes. Define each metric before the pilot. Compare the same process over time rather than quoting catalogue size as evidence of protection.
Report sample size and coverage. A collection dominated by one directory cannot establish the prevalence of harmful events on the whole web. A six-link shortlist cannot prove that a field has only six worthwhile conferences. The case study in this series explains that distinction with a real local snapshot.
If AI is part of discovery, retain its suggested sources and check them separately. UNESCO advocates human-centred validation of generative AI in education and research. [2]
Where a platform can support the process
ScholarVault’s documented workflows connect discovery, SCVS evidence review, research records, submission tracking and portfolio preparation. A university pilot could examine whether those connections make the evidence and next action easier to find. [3]
A configured PBAS draft can support Indian faculty preparation, while other institutions use their own appraisal rules. Automated assessment is separate from human verification and does not establish adoption, accreditation or partnership. Agree evaluation criteria before making organisational claims. [4]
Your next step: select a small group of volunteers and one real decision process. Review the evidence sheet with your library and research office, then test whether another person can reconstruct the decision from the saved record.
Sources & reading notes
Sources reviewed for this draft on 9 October 2026. Institutional examples illustrate a source trail; they do not imply a ScholarVault partnership or endorsement. Workflow recommendations are ScholarVault’s editorial interpretation.
- UKRI — publishing research findings
- UNESCO — guidance for generative AI in education and research
- ScholarVault — public learning center
- ScholarVault — SCVS methodology and assessment limits
Have a correction or a newer institutional source? Send it to the editorial team.