# How to create a profile A profile is a directory of static files conforming to [the RP Format](/researcher-profiles/rp-sdk/profile-format.md). The spec defines the format, not how to produce it. Any process that emits a conforming directory works, whether you write the files by hand, generate them with a script, or bootstrap them with an LLM. :::note[Prerequisites] - Familiarity with JSON - See [the tutorial](/researcher-profiles/rp-sdk/tutorial.md) for a full walkthrough ::: ## What a profile directory looks like At minimum, a profile is a directory containing two files: ``` jane-doe/ ├── profile.jsonld └── sources/papers.jsonld ``` `profile.jsonld` is the record and the manifest; `sources/papers.jsonld` is the works list, and it may be an empty `Collection` for a researcher with no publications. `profile.jsonld` lists it in `hasPart` with role `works`. A directory with those two files, where `profile.jsonld` carries `conformsTo`, is a conforming `lite` profile. Everything else is optional and additive: ``` jane-doe/ ├── profile.jsonld ├── personality/ │ ├── expertise.md │ └── SOUL.md └── sources/ ├── papers.jsonld └── summaries/ └── .summary.md ``` `personality/` and `sources/` enable deeper features (persona methods, search, citation-backed answers) but are not required to have a valid profile. See [the tutorial](/researcher-profiles/rp-sdk/tutorial.md) for a full walkthrough of building one of these directories by hand, file by file. ## The required fields `profile.jsonld` has three top-level keys with no default. Omit any one and the document fails to load (see [the profile document spec](/researcher-profiles/rp-spec/index.md#31-the-profilejsonld-document)): | Key | What it is | |---|---| | `name` | The researcher's display name | | `rid` | A canonical ORCID, or a `local:` id if they have none | | `provenance` | Who asserted this profile and on what basis (no default) | Five more keys are required on the wire. Every conforming published document carries them, but the reference implementation fills them in when absent, so you can omit them while authoring by hand: | Key | What it is | Default when absent | |---|---|---| | `@context` | Exact string: `https://profiles.databio.org/context/v1.jsonld` | filled in with this value | | `@id` | The subject IRI: `https://orcid.org/` for an ORCID `rid`, else the profile's `url`, else `#me` | filled in from `url` or `#me` | | `@type` | `"Person"` | filled in | | `conformsTo` | Equals the `@context` IRI and acts as the format gate. A present but wrong value fails to load. | filled in with the current format IRI | | `level` | `"lite"`, `"full"`, or `"deep"` | filled in as `"full"` | A minimal valid `profile.jsonld`: ```json { "@context": "https://profiles.databio.org/context/v1.jsonld", "@id": "https://orcid.org/0000-0002-1825-0097", "@type": "Person", "conformsTo": "https://profiles.databio.org/context/v1.jsonld", "name": "Jane Doe", "rid": "0000-0002-1825-0097", "provenance": "third_party", "level": "lite", "hasPart": [ { "@type": "Collection", "name": "Works", "role": "works", "contentUrl": "sources/papers.jsonld", "encodingFormat": "application/ld+json" } ] } ``` Everything else (personality documents, summaries, career history, collaborators) is optional. A `lite` profile with this document and the works list it names is conforming; it cannot run persona methods or feed a full-corpus search until it has more. `rp manifest --write` fills in `hasPart` from the files on disk, so you do not have to type it. ## Ways to create a profile - By hand: follow [the tutorial](/researcher-profiles/rp-sdk/tutorial.md) step by step. It builds a small profile from scratch and explains each file. - By script: any code that writes valid JSON (and, optionally, Markdown) into the directory works. There is no required tool; validate the output against the schema (see below). - By LLM: paste the prompt below into ChatGPT, Claude, or any other model to generate a starter `profile.jsonld`. - By pipeline: a profile directory can also be produced by an automated build tool. The format does not care which tool produced it; only the resulting directory is specified. The SDK defines and validates the format; it does not ship a build pipeline. See [Creation is out of scope](/researcher-profiles/rp-sdk/profile-format.md#creation-is-out-of-scope). ## Generate a starter profile with an LLM Paste a prompt like this into any chat model, filling in the researcher's name and ORCID: ```text Generate a profile.jsonld file for the researcher-profiles format (https://profiles.databio.org/context/v1.jsonld). The researcher is , ORCID <0000-0000-0000-0000>. Return a single JSON object with these required keys: - "@context": "https://profiles.databio.org/context/v1.jsonld" - "@id": "https://orcid.org/" - "@type": "Person" - "conformsTo": "https://profiles.databio.org/context/v1.jsonld" - "name": their full name - "rid": their ORCID (no URL, just the identifier) - "provenance": "third_party" - "level": "lite" Also fill in whatever of the following you can determine from public information: "affiliation", "field", "subfields" (array), "summary" (one paragraph), "expertise" (array of short topic labels). Output only the JSON object, no commentary. ``` Example output: ```json { "@context": "https://profiles.databio.org/context/v1.jsonld", "@id": "https://orcid.org/0000-0002-1825-0097", "@type": "Person", "conformsTo": "https://profiles.databio.org/context/v1.jsonld", "name": "Jane Doe", "rid": "0000-0002-1825-0097", "provenance": "third_party", "level": "lite", "affiliation": "Example University", "field": "Computational Biology", "subfields": ["epigenomics", "chromatin"], "summary": "Jane Doe develops methods for region-set analysis.", "expertise": ["region-set-analysis", "reproducible-workflows"] } ``` Save this as `/profile.jsonld`. LLM-generated metadata should be reviewed for accuracy before you treat it as authoritative: the model may guess at affiliation, field, or summary details it has not verified. ## Validate the result Run the conformance check. It validates every artifact against its schema and checks the cross-file invariants (manifest drift, summary ids that match a paper, and so on): ```bash rp validate jane-doe ``` The same check from Python returns a `ProfileValidationReport`: ```python from researcher_profiles import ResearcherProfile report = ResearcherProfile.from_files("jane-doe").validate() print(report.ok) ``` Loading with `from_files` alone is not a conformance check: it reads each file lazily and only parses the ones you touch. See [How to validate a profile](/researcher-profiles/rp-sdk/how-to/validate-a-profile.md) for schema validation without installing the package, and for the deeper quality-audit checks.