Quality control list for digital books

Collective work of the Normes & standards working group of the SNE digital commission.

The quality control lists for digital books aim to :

• ensure access to digital books for as many readers as possible, without discrimination as to age, skills, physical or mental abilities, culture, equipment or access methods;
• to build a common quality standard for digital books
• make it easier for professionals to take ownership and give meaning to the actions undertaken;

This work is based on the Opquast Checklist - web quality assurance, 240 rules to improve your sites and take better account of your users - Version 4 - 2020-2025

## Licence The rules are published under a Creative Commons BY-SA licence. You may use them freely, provided you maintain authorship of the content, via a link to :

• https://www.opquast.com. Opquast is a French registered trademark.
• https://github.com/edrlab/qualebook
• https://creativecommons.org/licenses/by-sa/4.0/

Rules are available as JSON and CSV Data sets

JSON and CSV outputs are used to export rule data in structured formats that can be consumed by other systems or used for data analysis.

CSV Export

Structure

The CSV export contains all quality rules with 16 columns (semicolon-separated):

Column	Description	Type
title	Rule title	String
abstract	Brief description of the rule	String
categories	Rule categories (semicolon-delimited list)	Array
agrege	Aggregation identifier	String
description	Detailed rule description	String
actif	Active status (1 = active, 0 = inactive)	Boolean
tags	Labels/tags (semicolon-delimited list, e.g., "Legality", "Accessibility")	Array
objectif	Objectives/goals (semicolon-delimited list)	Array
Meo	Best Implementation Practice guidance (semicolon-delimited list)	Array
Controle	Validation/control criteria (semicolon-delimited list)	Array
Source	Reference sources (semicolon-delimited list)	Array
Referentiel	Standards and specifications (semicolon-delimited list, e.g., EPUB, WCAG)	Array
epubcheck	EPUB validation status	Boolean
ace	Accessibility checker status	Boolean
humancheck	Human review status	Boolean
steps	Process steps (semicolon-delimited list)	Array

URLs

• French: https://edrlab.github.io/qualebook/fr/rules/index.csv
• English: https://edrlab.github.io/qualebook/en/rules/index.csv

How to Use

1. Download the CSV file: Access the URL above for your desired language.

2. Import into spreadsheet software: Open in Excel, Google Sheets, or LibreOffice Calc using semicolon as the delimiter.

3. Parse array fields: Fields marked as "Array" contain multiple values separated by semicolons. Split by ; when processing programmatically.

4. Use cases:

   • Rule filtering by category, tags, or status
   • Compliance reporting
   • Integration with QA systems
   • Data analysis and reporting

JSON Export

Structure

The JSON export follows the JSON Feed v1.1 standard and contains all 16 rule fields per item:

Root object fields:

• version: JSON Feed version
• title: Feed title
• description: Feed description
• home_page_url: Homepage URL
• feed_url: JSON feed URL
• items: Array of rule objects

Each rule item contains:

• title, abstract, description, agrege: Text fields
• categories, tags, steps, objectif, Meo, Controle, Source, Referentiel: Array fields
• actif, epubcheck, ace, humancheck: Boolean fields
• date_published, date_modified: ISO 8601 timestamps
• id, url: Unique identifier and link to rule

URLs

• French: https://edrlab.github.io/qualebook/fr/rules/index.json
• English: https://edrlab.github.io/qualebook/en/rules/index.json

Sample Output

{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "Qualebook Rules Database",
  "description": "Quality checklist for digital books - Rule database",
  "home_page_url": "https://edrlab.github.io/qualebook",
  "feed_url": "https://edrlab.github.io/qualebook/en/rules/index.json",
  "items": [
    {
      "title": "Copyright and reuse information is available",
      "date_published": "2024-01-15T10:30:00Z",
      "date_modified": "2025-03-10T14:20:00Z",
      "id": "https://edrlab.github.io/qualebook/en/rules/001/",
      "url": "https://edrlab.github.io/qualebook/en/rules/001/",
      "abstract": "Users must be informed of the rights governing the reuse of content",
      "categories": ["rights management"],
      "agrege": "O4094-E010",
      "description": "Rule #01",
      "actif": 1,
      "tags": ["Legality", "Discoverability"],
      "objectif": ["Inform users about conditions of content publication"],
      "Meo": ["Add metadata to mark copyright information"],
      "Controle": ["Verify presence of copyright notice"],
      "Source": ["Opquast"],
      "Referentiel": ["EPUB 3", "Dublin Core"],
      "epubcheck": false,
      "ace": false,
      "humancheck": true,
      "steps": ["Editorial planning", "Digital production"]
    }
  ]
}

How to Use

1. Fetch the JSON: Download or stream the JSON feed URL.

2. Parse programmatically: Use a JSON parser to access rule data.

3. JavaScript example (fetch and filter by tag):

   fetch('https://edrlab.github.io/qualebook/en/rules/index.json')
     .then(response => response.json())
     .then(data => {
       const a11yRules = data.items.filter(rule => 
         rule.tags.includes('Accessibility')
       );
       console.log(`Found ${a11yRules.length} accessibility rules`);
       a11yRules.forEach(rule => {
         console.log(`${rule.title}: ${rule.abstract}`);
       });
     });

4. Python example (search and analyze):

   import requests
   
   response = requests.get('https://edrlab.github.io/qualebook/en/rules/index.json')
   data = response.json()
   
   # Find all active rules with humancheck status
   reviewed_rules = [
       rule for rule in data['items']
       if rule['actif'] == 1 and rule['humancheck']
   ]
   
   # Group by category
   by_category = {}
   for rule in reviewed_rules:
       for cat in rule['categories']:
           if cat not in by_category:
               by_category[cat] = []
           by_category[cat].append(rule['title'])
   
   for category, rules in by_category.items():
       print(f"{category}: {len(rules)} rules")

5. Use cases:

   • Build custom rule viewers/dashboards
   • Integrate rules into publishing workflows
   • Create rule recommendation systems
   • Perform automated compliance checks
   • Feed data into other applications

Deepwiki

This repo documentation is available as deepwiki

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