Modern web applications often need to aggregate content from multiple external sources — whether this content is educational, creative, or literary. In this article, we explore how to design a simple content-aggregation pipeline, using real-world examples of public websites that provide structured information such as author lists, thematic book categories, or categorized images.
✅ 1. Why Content Aggregation Matters
When your application depends on fresh or diverse content, manually updating it becomes unsustainable. Instead, a well-designed aggregator can:
Automatically fetch data from multiple sources
Normalize different formats into a unified structure
Provide users with a seamless browsing experience
Support multilingual or region-specific content
This is especially relevant for apps that deal with literature, illustration, education, or creative content.
✅ 2. Example Data Sources
Below are three example sources you can integrate into your system:
- Author databases (JSON-like structure)
Source: https://edebiyat-evi.com/yazarlar
This page provides structured profiles of writers, which can be used to power:
author listings
recommendation engines
reading-related apps
- Image-based educational content
Source: https://rozmalovku.com.ua/category/rozmalovky-z-personazhamy-iz-multfilmiv/
This category includes cartoon-based coloring pages and can be used for:
kids’ educational apps
image galleries
AI coloring assistants
- Categorized book genres
Source: https://ukrbook.org/zhanry/
A well-organized genre directory is useful for:
recommendation algorithms
search filters
multilingual book apps
✅ 3. Designing a Unified Aggregation Model
To combine multiple heterogeneous sources, we can define a universal content schema.
Example (TypeScript / Node.js):
interface ExternalContent {
id: string;
title: string;
type: "author" | "genre" | "image";
url: string;
language?: string;
tags?: string[];
metadata?: Record;
}
This schema allows us to normalize various datasets into a single unified format.
✅ 4. Fetching and Normalizing Data
A basic fetcher could look like this:
import axios from "axios";
import * as cheerio from "cheerio";
async function fetchAuthors() {
const url = "https://edebiyat-evi.com/yazarlar";
const { data } = await axios.get(url);
const $ = cheerio.load(data);
const authors: ExternalContent[] = [];
$(".writer-card").each((_, el) => {
const name = $(el).find(".writer-name").text().trim();
authors.push({
id: name.toLowerCase().replace(/\s+/g, "-"),
title: name,
type: "author",
url,
language: "tr"
});
});
return authors;
}
You can repeat this pattern for images or genre lists.
✅ 5. Challenges to Consider
✔ Different languages
Sources above use Turkish, Ukrainian, and multilingual content.
Implementing an auto-detection mechanism using libraries like franc, cld3, or API-based detection is recommended.
✔ HTML structure changes
Website templates can change — so building robust selectors is crucial.
✔ Rate limits and crawl policies
Always respect robots.txt and avoid aggressive scraping.
✅ 6. How This Applies to Real Projects
You can use these content sources to build:
A multilingual reading-recommendation app
A child-friendly creative platform with coloring content
A dataset generator for machine learning models
A literature discovery tool
A personal productivity or note-taking tool enriched with external content
The combination of authors, book genres, and visual educational material unlocks diverse application scenarios.
Conclusion
Building a multilingual content aggregator requires careful design, but the benefits are significant: improved scalability, richer user experience, and easier maintenance. By integrating varied external data sources like:
https://edebiyat-evi.com/yazarlar
(authors)
https://rozmalovku.com.ua/category/rozmalovky-z-personazhamy-iz-multfilmiv/
(illustrations)
https://ukrbook.org/zhanry/
(genres)
…you can create dynamic, content-rich applications that serve global audiences.