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Merge pull request #51 from TranslatorSRI/karafecho-patch-4
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Update README.md
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jdr0887 authored Aug 29, 2024
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This folder is intended to suppport manually-defined, SMuRF- and SME-evaluated inferred CQS workflows, with each workflow structured as a valid TRAPI query and serving as a CQS template.

The CQS was conceptualized by the Translator Clinical Data Committee, but initial development and implementation were conducted under the Standards and Reference Implementation (SRI) component of Translator. The CQS provides a simple mechanism through which KP teams or any committee, working group, or external team can apply their expertise /resources to specify how their data are to be used for inference. Thus, the CQS enables a ”conservative ingest” paradigm, where KP teams directly ingest knowledge sources and perhaps compute on them, but rely on the CQS service to generate desired inferences based on this more foundational knowledge. The CQS templates are used by the CQS to create "treats" predictions.
The CQS was conceptualized by the Translator Clinical Data Committee, but initial development and implementation were conducted under the Standards and Reference Implementation (SRI) component of Translator. The CQS provides a simple mechanism through which KP teams or any committee, working group, or external team can apply their expertise /resources to specify how their data are to be used for inference. Thus, the CQS enables a ”conservative ingest” paradigm, where KP teams directly ingest knowledge sources and perhaps compute on them, but rely on the CQS service to generate desired inferences based on this more foundational knowledge. For instance, the CQS templates are used by the CQS to generate "treats" predictions based on a set of rules developed by the contributing KPs who expose the primary knowledge source (e.g., Clinical Trials provider exposes one-hop in_clinical_trials_for edges and directs the CQS to generate a predicted "treats" edge when a clinical trial meets certain criteria such as in phase 3 or 4).

**The process to contribute a new CQS template is as follows:**

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4. Test the CQS template by direct query of the Workflow Runner.
5. Create a branch in the CQS repo.
- Create a new template folder within CQS/templates. Following the nomenclature specified below.
- Within that folder, add a thoroughly descriptive README with a POC and select CURIES to be used for development and testing. The CURIES should be associated with test assets that the POC has contributed to the test assets repo, using [this G-sheet](https://docs.google.com/spreadsheets/d/1wAQaFEtFqAvp2fbTZIe-2ObF9zUU_cmXILfU8SzUWe0/edit?usp=drive_link).
- Within that folder, add a thoroughly descriptive README with a POC and select CURIES to be used for development and testing. The CURIES should be associated with test assets that the POC has contributed to the test assets repo: https://github.com/NCATSTranslator/Tests.
- Add a new CQS template structured as a valid TRAPI.
- Create a PR.
5. The new CQS template will then be deployed to DEV, thus entering the Translator pipeline.
6. After the CQS is deployed to CI, it will be picked up by the Information Radiator for automated testing. The POC for a given CQS template is responsible for monitoring the testing results.
6. After the CQS is deployed to CI, it will be picked up by the Information Radiator for automated testing. **The POC for a given CQS template is responsible for monitoring the testing results.**

*See https://github.com/NCATSTranslator/OperationsAndWorkflows/tree/main/schema for valid TRAPI operations and workflows.*

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### Overall Structure

Path A serves as a CQS template and is structured as a valid TRAPI query, with workflow parameters and an _allowlist_ parameter.
mvp1-template1-clinical-kps (formerly known as Path A) serves as a CQS template and is structured as a valid TRAPI query, with workflow parameters and an _allowlist_ parameter.

Note that Path A targets the clinical KPs, using the following predicates plus an _allowlist_ parameter:
Path A targets the clinical KPs, using the following predicates plus an _allowlist_ parameter. Note that the associated_with predicate and the correlated_with predicate are _not_ specific to the Clinical KPs, so the presence of those edges alone cannot be used to validate that the Clinical KPs have returned edges to a given query. Rather, one should search for infores identifiers.

associated_with

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