Wikidata Constraints Violation Checker

The Wikidata Constraints Violations Checker allows you to analyze the number of constraints violations on a list of Wikidata Items. This is useful to better understand which Items need improvements the most and to better understand the data quality of a specific area of Wikidata.

Installation

This script requires at least Python 3.6. In your terminal, run:

git clone https://github.com/wmde/wikidata-constraints-violation-checker.git
cd wikidata-constraints-violation-checker
pip3 install -r requirements.txt

Usage

# To run the script with an input file
python3 checkDataQuality.py -i <inputfile>

# To run the script using randomly generated Item IDs
python3 checkDataQuality.py -r <number of items>

# You can also specify an output filename
python3 checkDataQuality.py -i <inputfile> -o <outputfile>

# Or a batch size
python3 checkDataQuality.py -r <number of items> -b <batch-size>

Arg	Name	Description
-i	Input file	The path to the file containing the input data
-r	Randomly generate Items	The number of Items to randomly generate
-o	Output file	The path to the file for output
-b	Batch Size	The list of Items are broken down into batches for processing. Default value is 10

Input Data

The script can read CSV files or generate random Item IDs.

CSV File

Example input file, the first column will be used to query for constrains violations:

Q60,New York
Q64,Berlin
Q70,Bern
Q84,London
Q90,Paris

Output Data

The following fields are provided in the output data for Items that are succesfully checked.

Field	Description
QID	The unique Item identifier
statements	Total amount of statements on the Item
violations_mandatory_level	# of violations at a mandatory level
violations_normal_level	# of violations at a normal level
violations_suggestion_level	# of violations at a suggestion level
violated_statements	# of statements with violations
total_sitelinks	# of sitelinks on the Item
wikipedia_sitelinks	# of sitelinks to Wikipedia
ores_score	ORES Item quality score From 1 to 5 (lowest to highest)

Note

Please be aware that some large Items are skipped during the analysis because the constraint check API times out for them.

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