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LibPyFDP simplifies creating and managing DCAT metadata for Fair Data Points. Designed for data scientists and analysts, it eases searching, retrieving, and inserting dataset metadata into FDP. The library provides a Pythonic API for creating DCAT Catalogs, Datasets, DatasetSeries, and Distributions, enabling research data to be FAIR-compliant.

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LybPyFDP

A Python library for DCAT metadata management in Fair Data Points

GitHub branch check runs GitHub Actions Workflow Status Python Version from PEP 621 TOML GitHub License

The LibPyFDP library simplifies the process of creating, searching, and managing dataset metadata compliant with the DCAT (Data Catalog Vocabulary) standard for insertion into Fair Data Points. It is designed specifically for data scientists and data analysts who need to make their research data FAIR (Findable, Accessible, Interoperable, and Reusable).

Key Features

  • Easy DCAT creation: Programmatically create DCAT Catalogs, Datasets, Dataset Series, and Distributions
  • FDP integration: Seamless insertion of metadata into Fair Data Points
  • Search and retrieve: Query existing metadata from FDP instances
  • Pythonic API: Intuitive interface designed for data professionals

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License

This library is released under the Apache License 2.0. See LICENSE file for details.

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LibPyFDP simplifies creating and managing DCAT metadata for Fair Data Points. Designed for data scientists and analysts, it eases searching, retrieving, and inserting dataset metadata into FDP. The library provides a Pythonic API for creating DCAT Catalogs, Datasets, DatasetSeries, and Distributions, enabling research data to be FAIR-compliant.

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