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feat: Include inference resources in metadata
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{ | ||
"$schema": "http://json-schema.org/draft/2020-12/schema", | ||
"$id": "https://github.com/ai4os/ai4-metadata/blob/master/src/ai4_metadata/schemata/ai4-apps-v2.0.0.json", | ||
"type": "object", | ||
"properties": { | ||
"metadata_version": { | ||
"description": "Version of the metadata schema.", | ||
"pattern": "^[0-9]{1,}.[0-9]{1,}.[0-9]{1,}$", | ||
"example": "2.0.0", | ||
"type": "string" | ||
}, | ||
"title": { | ||
"description": "Name of the Data Science application.", | ||
"type": "string", | ||
"user_friendly": "Title", | ||
"example": "Deep Learning Model for Metadata Classification" | ||
}, | ||
"summary": { | ||
"description": "Short text describing the value of the Data Science application.", | ||
"type": "string", | ||
"user_friendly": "Summary", | ||
"example": "This model classifies metadata using deep learning techniques." | ||
}, | ||
"description": { | ||
"description": "Elaborated description of the Data Science application.", | ||
"type": "string", | ||
"user_friendly": "Description", | ||
"example": "This model uses a deep learning architecture to classify metadata into different categories. The model is trained on a dataset of 10,000 metadata entries and achieves an accuracy of 90%." | ||
}, | ||
"doi" : { | ||
"description": "DOI of the Data Science application.", | ||
"type": "string", | ||
"format": "doi", | ||
"user_friendly": "Digital Object Identifier", | ||
"example": "10.5281/zenodo.1234567" | ||
}, | ||
"links": { | ||
"title": "links", | ||
"type": "object", | ||
"properties": { | ||
"documentation": { | ||
"description": "URL pointing to the relevant documentation.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Documentation URL", | ||
"example": "https://example.org/docs" | ||
}, | ||
"source_code": { | ||
"description": "URL pointing to the relevant source code.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Source Code URL", | ||
"example": "https://example.org/code" | ||
}, | ||
"docker_image": { | ||
"description": "URL pointing to the relevant Docker image.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Docker Image URL", | ||
"example": "https://example.org/docker" | ||
}, | ||
"zenodo_doi": { | ||
"description": "DOI of the Zenodo record.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Link to Zenodo DOI", | ||
"example": "https://doi.org/10.5281/zenodo.1234567" | ||
}, | ||
"dataset": { | ||
"description": "URL pointing to the relevant training dataset.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Traning Dataset URL", | ||
"example": "https://example.org/dataset" | ||
}, | ||
"weights": { | ||
"description": "URL of file containing weights from training", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Weights URL", | ||
"example": "https://example.org/weights" | ||
}, | ||
"citation": { | ||
"description": "URL pointing to the relevant citation. Please use a Citation File Format (CFF) if possible.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Citation URL", | ||
"example": "https://example.org/citation.cff" | ||
}, | ||
"base_model": { | ||
"description": "URL pointing to a base model if this model is a fine-tune, adaptation, etc. of another one.", | ||
"type": "string", | ||
"format": "uri", | ||
"user_friendly": "Base Model URL", | ||
"example": "https://example.org/base_model" | ||
} | ||
}, | ||
"required": [ | ||
"source_code" | ||
] | ||
}, | ||
"dates": { | ||
"title": "dates", | ||
"type": "object", | ||
"properties": { | ||
"created": { | ||
"description": "Creation date of the Data Science application.", | ||
"type": "string", | ||
"format": "date", | ||
"user_friendly": "Creation Date", | ||
"example": "2022-01-01" | ||
}, | ||
"updated": { | ||
"description": "Last update date of the Data Science application.", | ||
"type": "string", | ||
"format": "date", | ||
"user_friendly": "Last Update Date", | ||
"example": "2024-12-31" | ||
} | ||
}, | ||
"required": [ | ||
"created", | ||
"updated" | ||
] | ||
}, | ||
"libraries": { | ||
"description": "Libraries used in the Data Science application.", | ||
"type": "array", | ||
"uniqueItems": true, | ||
"items": { | ||
"type": "string", | ||
"enum": [ | ||
"TensorFlow", | ||
"PyTorch", | ||
"Keras", | ||
"Scikit-learn", | ||
"XGBoost", | ||
"LightGBM", | ||
"CatBoost", | ||
"Other" | ||
] | ||
}, | ||
"user_friendly": "Libraries used", | ||
"example": ["TensorFlow", "PyTorch"] | ||
}, | ||
"tasks": { | ||
"description": "Topic/s for the tasks that categorize the Data Science application.", | ||
"type": "array", | ||
"uniqueItems": true, | ||
"items": { | ||
"type": "string", | ||
"enum": [ | ||
"Computer Vision", | ||
"Natural Language Processing", | ||
"Time Series", | ||
"Recommender Systems", | ||
"Anomaly Detection", | ||
"Regression", | ||
"Classification", | ||
"Clustering", | ||
"Dimensionality Reduction", | ||
"Generative Models", | ||
"Graph Neural Networks", | ||
"Optimization", | ||
"Reinforcement Learning", | ||
"Transfer Learning", | ||
"Uncertainty Estimation", | ||
"Other" | ||
] | ||
}, | ||
"user_friendly": "Model Tasks", | ||
"example": ["Computer Vision", "Natural Language Processing"] | ||
}, | ||
"categories": { | ||
"description": "Platform categories for the tasks that categorize the Data Science application.", | ||
"type": "array", | ||
"uniqueItems": true, | ||
"items": { | ||
"type": "string", | ||
"enum": [ | ||
"AI4 pre trained", | ||
"AI4 trainable", | ||
"AI4 inference", | ||
"AI4 tools" | ||
] | ||
}, | ||
"user_friendly": "AI4 Platform Categories", | ||
"example": ["AI4 pre trained", "AI4 trainable"] | ||
}, | ||
"tags": { | ||
"description": "User provided tags to best describe the Data Science application.", | ||
"type": "array", | ||
"uniqueItems": true, | ||
"items": { | ||
"type": "string" | ||
}, | ||
"user_friendly": "Tags", | ||
"example": ["Deep Learning", "Metadata Classification"] | ||
}, | ||
"data-type": { | ||
"description": "Data type used in the Data Science application.", | ||
"type": "array", | ||
"uniqueItems": true, | ||
"items": { | ||
"type": "string", | ||
"enum": [ | ||
"Image", | ||
"Text", | ||
"Time Series", | ||
"Tabular", | ||
"Graph", | ||
"Audio", | ||
"Video", | ||
"Other" | ||
] | ||
}, | ||
"user_friendly": "Data Type", | ||
"example": ["Text"] | ||
} | ||
}, | ||
"required": [ | ||
"metadata_version", | ||
"title", | ||
"summary", | ||
"description", | ||
"links", | ||
"libraries", | ||
"tasks", | ||
"categories", | ||
"tags" | ||
], | ||
"not": { | ||
"anyOf": [ | ||
{ "required": ["tosca"] }, | ||
{ "required": ["sources"] }, | ||
{ "required": ["dataset_url"] }, | ||
{ "required": ["cite_url"] }, | ||
{ "required": ["date_creation"] }, | ||
{ "required": ["keywords"] }, | ||
{ "required": ["license"] } | ||
] | ||
} | ||
} |