Metadata Quality Evaluation Tool

A visualization-based tool for evaluating and comparing multiple dimensions of metadata quality in semantic data, with a focus on Digital Cultural Heritage collections. The tool supports query-based selection of collections, quality dimensions, and visualizes results to enable analysis and comparison within and across collections.

Architecture

The application is divided into two independent services:

1. Dash Frontend
2. FastAPI Backend

Frontend

Implemented using:

• Dash
• Plotly
• Dash Bootstrap Components

Responsibilities:

• Dataset configuration
• Metric selection
• Ontology scope filtering
• Interactive visualization
• Analysis and comparison views

Backend

Implemented using:

• FastAPI
• RDFLib
• pySHACL

Responsibilities:

• Datasorce processing through
  • RDF parsing
  • SPARQL querying
• Metric execution
• Ontology extraction
• Result aggregation

Requirements

• Python 3.11+ recommended
• pip
• virtualenv

Installation

1. Clone the repository
2. Setup Backend and Frontend
   1. Open the backend/ and frontend/ folders
   2. For each of them create a virtual environment
   3. For each of them install dependencies Windows

cd backend python -m venv venv venv\Scripts\activate

Linux / macOS

cd backend python -m venv venv source venv/bin/activate

pip install -r requirements.txt

3. Start the Backend Open the terminal inside backend/ and run

uvicorn main:app --reload	

The API will be available at: http://127.0.0.1:8000

4. Start the Frontend Open a second terminal inside frontend/ and activate the frontend virtual environment. Run:

python app.py

The Dash frontend will be available at: http://127.0.0.1:8050

Testing the backend separately

The backend can be tested separately from the Frontend http://127.0.0.1:8000/docs exposes all available requests.

An example request body for evaluate

{
  "datasets": [
    {
      "dataset_id": "local_file_test",
      "label": "Local Turtle Test",
      "source_config": {
        "type": "rdf_file",
        "file_path": "tests/resources/valid.ttl",
        "format": "turtle"
      }
    },
    {
      "dataset_id": "dbpedia_artworks",
      "label": "DBpedia Artworks",
      "source_config": {
        "type": "sparql_endpoint",
        "endpoint_url": "https://dbpedia.org/sparql",
        "query": "CONSTRUCT { ?s ?p ?o } WHERE { { SELECT DISTINCT ?s WHERE { ?s a <http://dbpedia.org/ontology/Artwork> . } LIMIT 10 } ?s ?p ?o . }"
      }
    }
  ],
  "metrics": [
    {
      "metric_id": "structural_completeness"
    },
    {
      "metric_id": "property_completeness"
    }
  ]
}