DCAT Dataset in xml/rdf or ttl format Import Tool

A Python-based tool for importing DCAT datasets in xml/rdf or ttl format into the I14Y platform of the Swiss Federal Statistical Office (BFS).

Features

• Import DCAT datasets from xml/rdf or ttl files to I14Y API
• Supported properties for dcat.Dataset:

Property	Requirement level
dct:title	mandatory
dct:description	mandatory
dct:accessRight (chosen from: PUBLIC, NON_PUBLIC, CONFIDENTIAL, RESTRICTED)	mandatory
dct:publisher (stated in config.py)	mandatory
dct:identifier	mandatory
dct:issued	optional
dct:modified	optional
dcat:landingPage	optional
dcat:keyword	optional
dct:language	optional
dcat:contactPoint	optional
documentation (foaf:page)	optional
schema:image	optional
dct:temporalCoverage	optional
dcat:temporalResolution	optional
frequency (dct:accrualPeriodicity)	optional
dct:isReferencedBy	optional
dct:relation	optional
spatial/geographical coverage (dct:spatial)	optional
dct:conformsTo	optional
dcat:theme	optional
dcat:version	optional
adms:versionNotes	optional

prov.qualifiedAttribution and prov.qualifiedRelation are not supported automatically, you can add those informations manually on I14Y.

• Supported properties for dcat.Distribution:

Property	Requirement level
dct:title (if not stated, set automatically to 'Datenexport')	mandatory
dct:description (if not stated, set automatically to 'Export der Daten')	mandatory
dcat:accessURL	mandatory
dcat:downloadURL	optional
dct:license	optional
dct:issued	optional
dct:modified	optional
dct:rights	optional
dct:language	optional
schema:image	optional
dcat:spatialResolutionInMeters	optional
dcat:temporalResolution	optional
dct:conformsTo	optional
dcat:mediaType	optional
dct:format	optional
dct:packageFormat	optional
spdx:checksum	optional
dcat:byteSize	optional

Prerequisites

• Python 3.8+
• pip package manager

Installation

1. Clone this repository:

git clone [repository-url]
cd import_rdf_datasets

2. (Optional but recommended) Create and activate a virtual environment:

# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

3. Install dependencies:

pip install -r requirements.txt

4. Configure the application:
   • Edit src/config.py with your I14Y API token, organization ID and right file format ("xml" or "ttl")

Usage

Import Datasets

1. Log in on the interoperability platform. Copy the token clicking on the profile symbol. Fill in the token in the file config.py. Also provide the identifier of your organsation.
2. Place your RDF files in the data/ folder (.xml, .rdf or .ttl)
3. Run the import script:

python src/import_datasets.py

The script will process each row and display real-time progress and error messages in the terminal.

File Structure

import_rdf_datasets/
├── data/
│   └── datasets.xml
├── src/
│   ├── config.py
│   ├── dcat_properies_utils.py
│   ├── import_datasets.py
│   └── mappings.py
├── requirements.txt
└── README.md

Contributing

Please ensure any pull requests or contributions adhere to the following guidelines:

• Keep the code simple and well-documented
• Follow PEP 8 style guidelines
• Include appropriate error handling
• Test thoroughly before submitting