Complete AI Training

AI app for science and research · no coding needed

Scientific terminology change tracker

Trace vocabulary changes to project-specific data definitions.

Made for: Research consortia maintaining shared vocabularies

What Scientific terminology change tracker looks like
Open the demo For members · a working demo with sample data

What it does for you

The problem

Terminology changes break comparability across studies.

What it gives you

Research terminology migration brief

What you give it

Approved ontology releasesproject data dictionaries

How it works, step by step

  1. Compare vocabulary versions
  2. Flag retired terms
  3. Link affected variables
  4. Draft mapping questions
  5. Record researcher decisions
  6. Export change notes

What you see on screen

  • Term watchlist
  • Version comparison
  • Mapping review

Build it yourself with your AI system

Build this app yourself, no coding needed

Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.

Sign in to see how to build it yourself

Build a quick version to try, or get the full app pack for Scientific terminology change tracker with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.

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4 Have it built for you days to a few weeks

Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Scientific terminology change tracker with you.

Have Nexibeo build it

What's in the app pack

Included in the Complete AI Training membership.

  • The building instructions your AI follows, step by step
  • The questions your AI will ask you about your business before it starts
  • A clickable demo you can open in your browser, to see how it should work
  • A detailed blueprint of the screens, the information it keeps and the checks it runs

Become a member to get the app packAlready a member? Sign in

The files, for the technically curious
  • START-HERE.mdHow to build it with your own AI (read first)3 KB
  • README.mdOverview and links1 KB
  • questions.mdQuestions to answer before you build2 KB
  • prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
  • prompt-vps.mdThe same build on your own server (Docker)25 KB
  • spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
  • demo/index.htmlThe working demo on sample data196 KB

Questions

Do I need to know how to code?

No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.

What does it cost?

The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.

How long does it take?

The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.

Can I change it to fit my business?

Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.

More detailsHow the AI works, safeguards and what to build first

For research consortia maintaining shared vocabularies, turn approved ontology releases and project data dictionaries into research terminology migration brief. Address this specific problem: terminology changes break comparability across studies. The aim: trace vocabulary changes to project-specific data definitions. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.

The buyer creates a project, supplies approved ontology releases and project data dictionaries, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final research terminology migration brief before use. Retain source links and a version history for the next cycle.

How the AI works

Suggest semantic mappings with explicit uncertainty. Keep model suggestions separate from verified facts. Link factual outputs to authorized input evidence and show missing information explicitly. Use deterministic checks for counts, dates, identifiers and arithmetic where applicable. A designated reviewer validates consequential outputs and signs off the delivered result.

Safeguards

Preserve original data, methods, citations and research limitations. Use researcher review and document every substantive transformation. Approved source releases; no automatic historical data rewriting. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.

What to build first

Costed pilot: Approved source releases; no automatic historical data rewriting. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: compare vocabulary versions; flag retired terms. Support the third task through an assisted review queue: link affected variables. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of research terminology migration brief. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.

What it can connect to

Authorized datasets, papers, protocols, code and research records. Permitted feeds, published document sources, email digests and internal briefing channels. Verify collection rights and source reliability before selling coverage commitments. Begin with uploads and exports of approved ontology releases and project data dictionaries. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.

The screens in detail

Use a watchlist with source health and last-checked dates, a chronological change feed, and a reviewable briefing editor. Display original evidence beside each alert. Let users mute irrelevant topics and record whether a change led to action. Open with term watchlist; move into version comparison for the detailed task; finish in mapping review for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.