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Research software planning needs to accommodate discovery while making the delivery commitment understandable. Start with the actual award and institutional requirements, then define what the software must enable and what evidence will demonstrate it. Keep scientific uncertainty visible alongside the engineering work needed for a usable result.
Read the actual obligations before defining delivery
Ask the responsible project and institutional owners to identify the requirements that apply to the award. Record relevant outputs, dates, review arrangements and any constraints affecting software or data. Do not assume that a rule from another programme applies to this project.
Translate the software-related commitments into concrete acceptance evidence. Specify the intended users, supported tasks and environment. Keep questions about procurement, permitted expenditure or publication with the authorised reviewers rather than resolving them through assumptions in a technical estimate.
Separate research questions from engineering commitments
Identify what the research is intended to discover and which software capabilities can be specified now. Record dependencies between the two. If a scientific result changes the implementation direction, the plan should show the decision point rather than hiding the uncertainty inside a fixed feature list.
Give investigations a question, an output and a reviewer. Define what would justify continuing, changing direction or stopping that part of the work. Keep the engineering baseline updated as evidence emerges so the team has one current account of the agreed scope.
Make reproducibility part of the deliverable
Record the code, dependencies, configuration and permitted inputs needed to reproduce representative behaviour. Include manual preparation and interpretation steps. Ask someone beyond the original author to follow the instructions in a documented environment.
Have the scientific owner define expected results and appropriate comparison methods. Keep engineering checks separate from scientific validation. A repeatable build and a successful test run provide useful evidence, but they do not establish every research claim or future use.
Reserve time for meaningful review
Plan reviews around working increments and the people needed to assess them. Include representative users and research specialists where their judgement is necessary. Agree how feedback changes scope and who resolves competing requests.
Record the environment and limits of each demonstration. Keep unresolved issues visible with owners and next actions. Allow time to correct findings before the final handover rather than treating the last presentation as the first opportunity to assess whether the software is usable.
Plan what happens after the funded phase
Identify who will control repositories, environments and operational accounts when the project phase ends. Decide whether the software will continue as a supported service, remain a reproducible research asset or be retired. Each outcome requires a different level of documentation and operating responsibility.
Review dependencies on named researchers or temporary infrastructure. Arrange knowledge transfer and record how authorised users obtain access. Have the responsible owners confirm permissions for any intended reuse or publication rather than assuming that technical availability settles those questions.
Close with evidence and explicit limitations
Prepare a delivery record linking outputs to acceptance evidence, known limitations and support arrangements. Distinguish completed work from future ideas and unresolved research. Keep the record aligned with the actual released version and the agreed review scope.
Exercise the handover with the people who will use or maintain the result. Resolve missing instructions while the delivery team is available. A useful conclusion leaves the next owner able to understand what was delivered, how to reproduce it and which questions remain open.
A grant-project handover with three possible endings
A fictional funded project produces a research analysis tool. Start from its actual award and institutional obligations, then choose the intended end state: a reproducible research asset, a supported service or a retired experiment. Do not assume the same documentation, infrastructure or staffing is appropriate for all three, and do not borrow obligations from another funding programme.
For a reproducible asset, hand over versions, permitted fixtures, environment instructions, expected behaviour and scientific limitations. For a supported service, add operating accounts, access, incident ownership, maintenance funding and tested recovery. For retirement, agree what is retained, how authorised researchers obtain it and how active service use ends. Confirm retention and access decisions with the responsible institution.
Rehearse before the funded team disperses: a successor recreates the environment, runs an agreed example and explains its limitations. Record missing steps and an owner for correction. UKRI’s open-research guidance supports reproducibility and recognises ethical, legal and commercial constraints; it does not prescribe the software handover for every grant. Link the actual award outputs to acceptance evidence and distinguish future product ideas from delivered commitments.
How this relates to Veda Software’s work
Encounter demonstrates a managed workflow around specialist information. It is adjacent handover context, not a grant-funded delivery, funder acceptance or research-policy compliance claim.