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SPARQL Data Quality Monitoring Tool

This software provides tools to monitor the quality of data in OpenCitation Meta and OpenCitations Index by querying their SPARQL endpoints. It includes two monitoring classes: MetaMonitor and IndexMonitor, which are designed to run a series of tests on the triplestores and generate reports on data quality issues.

The reports are generated in JSON format, which is then converted to HTML for easier visualization.

Table of Contents

Overview

The tool uses SPARQL queries to check for potential issues in the data stored in the specified SPARQL endpoints:

  • MetaMonitor is used for the OpenCitations Meta endpoint.
  • IndexMonitor is used for the OpenCitations Index endpoint.

Each monitor runs a series of pre-configured tests defined in the related configuration file (in JSON format). The tests produce a report (JSON file) that details which issues are detected, including metadata such as runtime, whether the tests passed or failed, and any errors encountered during the process. The JSON report is then converted into HTML to be read more easily.

Two classes are responsible for interrogating the triplestores, the MetaMonitor class for OpenCitations Meta and the IndexMonitor class for OpenCitations Index, which can both be found inside the data_monitor module. They both require, upon instantiation, the path to the appropriate configuration file and the base path for the output files. In both the classes, the run_tests() method actually interrogates the endpoint specified in the related config file and produces the JSON output.

The JSON output can be converted into an HTML page by using the generate_html() method of the ReportVisualiser class, inside the html_vis module.

Installation

  1. Clone the repository:

    git clone https://github.com/opencitations/oc_monitor.git
    
  2. Install dependencies:

    The project's dependencies and virtual environment are managed with Poetry. If you're already using Poetry and have installed on your machine, you can use it to create a virtual enviroment by simply running:

    poetry install
    

    and then, to activate it:

    poetry shell
    

    If you're not using Poetry, you can install the required Python libraries by using pip and the requirements.txt file on your preferred environment:

    pip install -r requirements.txt
    
  3. Ensure proper configuration files:

    Make sure you have the necessary configuration files (e.g., meta_monitor_config.json and index_monitor_config.json) in the project folder. See the section on Configuration Files for details. The configuration files provided in this repository should work out of the box.

Usage

To run the process with the default configuration:

cd oc_monitor
python -m main

Configuration Files

The configuration files for both MetaMonitor and IndexMonitor are in JSON format and contain details about the endpoint to be queried and the tests to run. The endpoint field stores the URL of the endpoint to interrogate. The fields for each test include:

  • label: A short name for the tested issue.
  • description: A brief description of the issue.
  • query: The SPARQL query used to perform the check.
  • to_run: A boolean flag (true or false) indicating whether to run this specific test.

Example configuration (custom_meta_monitor_config.json):

{
    "endpoint": "https://k8s.opencitations.net/meta/sparql",
    "tests": [
        {
            "label": "duplicate_br",
            "to_run": true,
            "description": "A single value for a given external ID scheme (e.g. DOI value) is associated with more than one BR.",
            "query": "PREFIX datacite: <http://purl.org/spar/datacite/>\nPREFIX literal: <http://www.essepuntato.it/2010/06/literalreification/>\nPREFIX fabio: <http://purl.org/spar/fabio/>\n\nASK {\n    ?br1 datacite:hasIdentifier/literal:hasLiteralValue ?lit ;\n    a fabio:Expression .\n    ?br2 datacite:hasIdentifier/literal:hasLiteralValue ?lit ;\n    a fabio:Expression .\n    FILTER(?br1 != ?br2)\n}"
        }
    ]
}
        

Command-Line Arguments

The script allows users to further customise the default behaviour of the software via command-line arguments. Here are the available options:

Argument Description Default Value
--meta_config Filepath for the MetaMonitor configuration file. meta_monitor_config.json
--index_config Filepath for the IndexMonitor configuration file. index_monitor_config.json
--run Specify which monitor to run: meta, index, or both. both
--output_base_path Base folder for reports output. The folder structure follows monitor_results/<meta_reports|index_reports>/<YYYYMMDD>/. monitor_results

Examples

Run Both MetaMonitor and IndexMonitor (Default)

To run both monitors using default configurations and output paths:

cd oc_monitor
python -m main

This will generate reports in:

  • results/meta_reports/YYYYMMDD/
  • results/index_reports/YYYYMMDD/

Run Only MetaMonitor

To run only the MetaMonitor and specify a custom configuration file:

cd oc_monitor
python -m main --run meta --meta_config my_meta_config.json

Custom Output Path

To run both monitors but specify a custom output base path:

cd oc_monitor
python -m main --output_base_path /my/custom/path

The reports will be saved in:

  • /my/custom/path/meta_reports/YYYYMMDD/
  • /my/custom/path/index_reports/YYYYMMDD/

Run Only IndexMonitor with Custom Paths

To run only the IndexMonitor and specify both the configuration file and a custom output path:

cd oc_monitor
python -m main --run index --index_config custom_index_config.json --output_base_path custom_reports

The reports will be saved in custom_reports/index_reports/YYYYMMDD/.

Output Structure

The output reports are stored in a folder structure that follows this pattern:

monitor_results/
  ├── meta_reports/
      └── YYYYMMDD/
           ├── output_meta_monitor_YYYYMMDD.json
           └── meta_monitor_vis_YYYYMMDD.html
  └── index_reports/
       └── YYYYMMDD/
            ├── output_index_monitor_YYYYMMDD.json
            └── index_monitor_vis_YYYYMMDD.html

The JSON output file stores information about the tests results along with details on the execution process (associated configuration file, date and time of the execution, runtime, raised errors, etc.). Each test result in the output file is associated with the label and description of the issue and the SPARQL query that has been run for the test itself.

Example JSON output (output_meta_monitor_20241020.json):

{
    "endpoint": "https://k8s.opencitations.net/meta/sparql",
    "collection": "OpenCitations Meta",
    "datetime": "20/10/2024, 17:29:10",
    "running_time": 1.0028636455535889,
    "config_fp": "custom_meta_monitor_config.json",
    "monitoring_results": [
        {
            "label": "duplicate_br",
            "description": "A single value for a given external ID scheme (e.g. DOI value) is associated with more than one BR.",
            "query": "query": "PREFIX datacite: <http://purl.org/spar/datacite/>\nPREFIX literal: <http://www.essepuntato.it/2010/06/literalreification/>\nPREFIX fabio: <http://purl.org/spar/fabio/>\n\nASK {\n    ?br1 datacite:hasIdentifier/literal:hasLiteralValue ?lit ;\n    a fabio:Expression .\n    ?br2 datacite:hasIdentifier/literal:hasLiteralValue ?lit ;\n    a fabio:Expression .\n    FILTER(?br1 != ?br2)\n}"
            "run": {
                "got_result": true,
                "running_time": 1.0028636455535889,
                "error": null
            },
            "passed": false
        }
    ]
}

The above JSON report is then converted into an HTML document (although some information is left out, e.g. the SPARQL query for each test) and stored in the same directory:

alt text

Filename Details

  • JSON report: output_<monitor_type>_YYYYMMDD.json
  • HTML report: <monitor_type>_monitor_vis_YYYYMMDD.html

If the script is run multiple times on the same day, the filenames of the files created after the first one will be versioned (e.g., output_meta_monitor_YYYYMMDD_1.json, meta_monitor_vis_YYYYMMDD_1.html, etc.).

License

This project is licensed under the ISC License. See the LICENSE.md file for details.

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