mjanez / ckan-mqa

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

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

Overview • Quick start • Debug • Containers

Requirements:

• Docker

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.

Note
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.

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

Note:
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.

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 ([email protected]), Javier Lacasta ([email protected]), Manuel Ureña ([email protected]), F. Javier Ariza ([email protected]), Héctor Ochoa Ortiz ([email protected]). Trafair Project 2020. ↩

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

ckan-mqa's Issues

Feature - Improve workflows (Test, lint & scan)

Improve Github Actions:workflows:

• Test PR images.
• Build docker & push after PR closed.
• Add lint to Dockerfiles.
• Add vulnerability scan.

New docker-pr.yml, docker-manual.yml and docker-push.yml.