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Docker Compose for Metadata Quality Assessment (MQA) on CKAN and European Data Portal catalogs

github.com/mjanez/ckan-docker

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Docker Metadata Quality Assessment (MQA) for CKAN/EDP catalogs

mqa2ckan version License: Unlicense

Overview • Quick start • Debug • Containers • DCAT-AP info

Requirements:

Overview

ckan-mqa offers a Docker Compose solution for performing Metadata Quality Assessment (MQA) on both CKAN endpoints and the European Data Portal catalogs. MQA is a crucial process to ensure the accuracy, completeness, and reliability of metadata, enhancing the overall data interoperability and accessibility.

This Docker Compose configuration enhances a Python MQA software 1 to integrates the powerful MQA toolset seamlessly with CKAN endpoints and European Data Portal catalogs, enabling users to perform in-depth assessments of metadata quality effortlessly. The setup provides an efficient way to run comprehensive quality checks on various metadata attributes, including data relevance, schema compliance, data format consistency, and adherence to standard vocabularies.

Tip

It can be tested with an open data portal of the CKAN type such as: mjanez/ckan-docker2

Metadata Quality Assessment Methodology

The MQA measures the quality of various indicators, each indicator is explained in the tables below. The results of the checks are stored as Data Quality Vocabulary (DQV) . DQV is a specification of the W3C that is used to describe the quality of a dataset.

Dimension Maximal points
Findability 100
Accessibility 100
Interoperability 110
Reusability 75
Contextuality 20
Sum 405

The dimensions are derived from the FAIR principles:

  • Findability The following table describes the metrics that help people and machines in finding datasets. A maximum of 100 points can be scored in this area.

  • Accessibility The following table describes which metrics are used to determine whether access to the data referenced by the distributions is guaranteed. A maximum of 100 points can be scored in this area.

  • Interoperability The following table describes the metrics used to determine whether a distribution is considered interoperable. According to the assumption 'identical content with several distributions', only the distribution with the highest number of points is used to calculate the points. A maximum of 110 points can be scored in this area

  • Reusability The following table describes which metrics are used to check the reusability of the data. A maximum of 75 points can be scored in this area.

  • Contextuality The following table show some light weight properties, that provide more context to the user. A maximum of 20 points can be scored in this area.

5 MQA_dimensions png

The final rating happens via four rating groups. The mapping of the points to the rating category is shown in the table below. The representation of the rating in the MQA is expressed exclusively via the rating categories. This enables providers to achieve the highest rating even with a slight deduction of points.

Rating Range of points
Excellent 351 - 405
Good 221 – 350
Sufficient 121 – 220
Bad 0 - 120

Example of ckan-mqa results summary

Dimension Indicator/property Count Population Percentage Points Weight
Findability dcat:keyword 46 46 1.0 30.0 30
Findability dcat:theme 46 46 1.0 30.0 30
Findability dct:spatial 42 46 0.91 18.26 20
Findability dct:temporal 0 46 0.0 0 20
Accessibility dcat:accessURL code=200 255 255 1.0 50.0 50
Accessibility dcat:downloadURL 0 255 0.0 0 20
Accessibility dcat:downloadURL code=200 0 255 0.0 0 30
Interoperability dct:format 255 255 1.0 20.0 20
Interoperability dcat:mediaType 255 255 1.0 10.0 10
Interoperability dct:format/dcat:mediaType from vocabulary 378 510 0.74 7.41 10
Interoperability dct:format non-proprietary 131 255 0.51 10.27 20
Interoperability dct:format machine-readable 252 255 0.99 19.76 20
Interoperability DCAT-AP compliance 0 46 0.0 0 30
Reusability dct:license 255 255 1.0 20.0 20
Reusability dct:license from vocabulary 245 255 0.96 9.61 10
Reusability dct:accessRights 46 46 1.0 10.0 10
Reusability dct:accessRights from vocabulary 0 46 0.0 0 5
Reusability dcat:contactPoint 46 46 1.0 20.0 20
Reusability dct:publisher 46 46 1.0 10.0 10
Contextuality dct:rights 255 255 1.0 5.0 5
Contextuality dcat:byteSize 0 255 0.0 0 5
Contextuality dct:issued 46 46 1.0 5.0 5
Contextuality dct:modified 46 46 1.0 5.0 5
Total points Rating: Good 0.69 280.31 405

Quick start

First copy the .env.example template as .env and configure by changing the CKAN_CATALOG_URL, as well as the DCAT-AP Profile version (DCATAP_FILES_VERSION), if needed.

cp .env.example .env

Custom ennvars:

  • CKAN_CATALOG_URL: URL of the CKAN catalog to be downloaded (i.e. http://localhost:5000/catalog.rdf?q=organization:test).
  • APP_DIR: Path to the application folder in Docker.
  • TZ: Timezone.
  • DCATAP_FILES_VERSION: DCAT-AP version (Avalaibles: 2.0.1, 2.1.0, 2.1.1).
  • UPDATE_VOCABS: Update vocabs from the EU Publications Office at start (True or False).
  • CKAN_METADATA_TYPE: CKAN Metadata elements type: ckan_uris for GeoDCAT-AP schema with all elements described by URIs (e.g. dct:format = http://publications.europa.eu/resource/authority/file-type/XML) or ckan if used a CKAN default schema with label metadata elements (e.g. dct:format = "XML").

With docker compose

To deploy the environment, docker compose will build the latest image (ghcr.io/mjanez/ckan-mqa:latest).

git clone https://github.com/mjanez/ckan-mqa
cd ckan-mqa

docker compose up --build

# Or detached mode
docker compose up -d --build

Note

Deploy the dev (local build) docker-compose.dev.yml with:

docker compose -f docker-compose.dev.yml up --build

If needed, to build a specific container simply run:

 docker build -t target_name xxxx/

Without Docker

Dependencies:

python3 -m pip install --user pipx
pipx install pdm
pdm install --no-self

Run:

pdm run python ckan2mqa/ckan2mqa.py

Debug

VSCode

  1. Build and run container.
  2. Attach Visual Studio Code to container
  3. Start debugging on ckan2mqa.py Python file (Debug the currently active Python file).

Containers

List of containers:

Base images

Repository Type Docker tag Size Notes
python 3.11 base image python/python:3.11-slim 45.57 MB -

Built images

Repository Type Docker tag Size Notes
mjanez/ckan-mqa custom image mjanez/ckan-mqa:v*.*.* 264 MB Tag version.
mjanez/ckan-mqa custom image mjanez/ckan-mqa:latest 264 MB Latest stable version.
mjanez/ckan-mqa custom image mjanez/ckan-mqa:main 264 MB Dev version.

References

DCAT-AP Validator Validation Cases

The different cases to validate in the DCAT-AP Validator are based on the level of completeness of the checks and the incorporation of background knowledge (vocabularies). Each case is designed for a specific data exchange scenario. The following describes each case and recommends which one you should use for a CKAN catalog:

Case 1: DCAT-AP Base Zero (no background knowledge)

Includes all constraints required for technical coherence, excluding range class membership constraints and controlled vocabulary usage.

SHACL Profiles:

Case 2: DCAT-AP Ranges Zero (no background knowledge)

Includes all range class membership constraints.

SHACL Profiles:

Case 3: DCAT-AP Base (with background knowledge)

Extends Case 1 with background knowledge, including all vocabularies used in DCAT-AP.

SHACL Profiles:

Case 4: DCAT-AP Ranges (with background knowledge)

Extends Case 2 with background knowledge, adding validation of range class membership and vocabulary standards compliance.

SHACL Profiles:

Case 5: DCAT-AP Recommendations (with background knowledge)

Includes all constraints related to recommended properties.

SHACL Profiles:

Case 6: DCAT-AP Controlled Vocabularies

Includes all constraints related to controlled vocabularies.

SHACL Profiles:

Case 7: DCAT-AP Full (with background knowledge)

The union of Cases 3, 4, 5, and 6.

SHACL Profiles:

Recommendation:

For most use cases, Case 3: DCAT-AP Base (with background knowledge) is recommended. It provides comprehensive validation of basic coherence and vocabulary standards compliance. If your CKAN catalog uses controlled vocabularies, consider using Case 6: DCAT-AP Controlled Vocabularies or Case 7: DCAT-AP Full (with background knowledge) for more exhaustive validation. Remember, the choice of the appropriate validation case depends on your specific needs and data exchange context.

Tip

DCAT-AP:

EU Vocabularies: https://op.europa.eu/en/web/eu-vocabularies/dcat-ap

Validator:

DCAT-AP Country profiles:

SHACLs: https://github.com/ISAITB/validator-resources-dcat-ap/blob/baca3adf63d31ee415fa5e769249053ae211414c/resources/config.properties

License

Copyright (c) the respective contributors. It is open and licensed under the GNU Affero General Public License (AGPL) v3.0 whose full text may be found at: http://www.fsf.org/licensing/licenses/agpl-3.0.html

Footnotes

  1. Program to test MQA evaluation: Javier Nogueras (jnog@unizar.es), Javier Lacasta (jlacasta@unizar.es), Manuel Ureña (maurena@ujaen.es), F. Javier Ariza (fjariza@ujaen.es), Héctor Ochoa Ortiz (719509@unizar.es). Trafair Project 2020. ↩

  2. A custom installation of Docker Compose with specific extensions for spatial data and GeoDCAT-AP/INSPIRE metadata profiles. ↩

About

Docker Compose for Metadata Quality Assessment (MQA) on CKAN and European Data Portal catalogs

github.com/mjanez/ckan-docker

Topics

metadata ckan edp dcat-ap geodcat-ap metadata-quality mqa

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