https://github.com/bact/stav
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/bact/stav
- Owner: bact
- License: apache-2.0
- Created: 2023-09-22T13:55:13.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-23T04:19:21.000Z (over 1 year ago)
- Last Synced: 2025-11-28T00:36:59.945Z (7 months ago)
- Language: Jupyter Notebook
- Size: 7.31 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# STAV: System Trustworthiness and Accountability Vocabulary
[](https://www.repostatus.org/#wip)
[](https://pypi.org/project/stav)
[](https://pypi.org/project/stav)
-----
`This work is still under development.`
**stav**:
- Norwegian: *to spell (words)*
- Swedish: *letter (alphabet)*
- Slovak: *state (condition)*
- Czech: *stance*
## STAV Taxonomy
Available at [https://w3id.org/stav](https://w3id.org/stav.)
## STAV Python module
STAV terms can also be accessible through a Python module called `stav`, available freely on the [Python Package Index](https://pypi.org/project/stav/).
STAV class names are accessible through constants in the `stav` module. These class names are in capital letters with underscores separating words, `LIKE_THIS`, as stated in [PEP 8](https://peps.python.org/pep-0008/#constants).
Values of these constants are simply a STAV class name, a string in `CamelCase`.
For example, `stav.INSTRUCTIONS_FOR_USE` is a string with value of "InstructionsForUse".
(In the future, it should be able to configure the casing to "instructions_of_use", etc.)
With this, it will make the standardization of documentation within an organization, or across organizations, easier and can facilitate the use of the terms in MLOps settings, where data scientists and data engineers can use STAV terms as keys in their model logging and registration.
[](https://youtu.be/nSQ3rsaqpaQ?si=hZlHBSMUDnkbguSA "Watch the presentation from the Open Source Summit North America 2024")
### Installation
```console
pip install stav
```
### Use with MLflow
```python
from mlflow import log_artifact, log_metric, log_param, set_tag
import stav
with mlflow.start_run():
mlflow.set_tag(stav.INFO_TRAINING, "Basic LR model for iris data")
mlflow.set_tag(stav.AI_PROVIDER, "Acme Corporation")
mlflow.set_tag(stav.AI_DEPLOYER, "Sirius Cybernetics")
mlflow.set_tag(stav.USE_SENSITIVE_PERSONAL_INFO, "No")
mlflow.log_metric(stav.METRICS_ACCURACY, accuracy)
```
## Sister projects
STA*V* (a *V*ocabulary) and STA*P* (an ODRL *P*rofile) are sisters for system trustworthiness and accountability.
- **STAV** provides a vocabulary (with focus on *informational items*) extracted from regulations and policy documents, mostly AI safety-related, like EU Artificial Intelligence Act draft. Its IRI is [https://w3id.org/stav](https://w3id.org/stav). Its code repository is at [https://github.com/bact/stav/](https://github.com/bact/stav/).
- **STAP** provides a set of core accountability relationships, based on [Open Digital Rights Language](https://www.w3.org/TR/odrl-model/). They are trying not to be AI-specific. Its IRI is [https://w3id.org/stap](https://w3id.org/stap). Its code repository is at [https://github.com/bact/stap/](https://github.com/bact/stap/).
## License
STAV: System Trustworthiness and Accountability Vocabulary by Arthit Suriyawongkul is licensed under CC BY 4.0
The `stav` Python module is distributed under the terms of the [Apache License 2.0](https://spdx.org/licenses/Apache-2.0.html).
This work has emanated from research conducted with the financial support of Taighde Éireann – Research Ireland under Grant number 18/CRT/6224
([Research Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real)](https://d-real.ie/))
and with the organizational support from members of these research groups:
- [Knowledge and Data Engineering Group](https://www.tcd.ie/scss/research/research-groups/kdeg/), [Trinity College Dublin](https://www.tcd.ie/scss/)
- [Transparent Digital Governance strand](https://www.adaptcentre.ie/case-studies/transparent-digital-governance/), [ADAPT Centre](https://www.adaptcentre.ie/)
## Related works
Members of [RegTech group at ADAPT Centre](https://regtech.adaptcentre.ie/) contribute to AI and data ontology projects below, and they are may be of your interest:
- [Trustworthy AI Requirements Ontology (TAIR)](https://tair.adaptcentre.ie/)
- [AI Risk Ontology (AIRO)](https://w3id.org/airo)
- [Vocabulary of AI Risks (VAIR)](https://w3id.org/vair)
- [Data Privacy Vocabulary (DPV)](https://w3id.org/dpv) - [AI Extenstion](https://github.com/w3c/dpv/issues/126) (under development)