Update README.md

README.md

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+````markdown
 ---
+language:
+- en
+
 license: cc-by-4.0
+
+pretty_name: InfoBay.AI Infographic Dataset Catalogue
+
+size_categories:
+- 100K<n<1M
+
+task_categories:
+- image-classification
+- image-generation
+- image-to-text
+- object-detection
+- visual-question-answering
+
+task_ids:
+- computer-vision
+- multimodal-learning
+
+tags:
+- infographic
+- charts
+- diagrams
+- data-visualization
+- documents
+- business
+- education
+- technology
+- science
+- computer-vision
+- multimodal
+- generative-ai
+- vision-language-models
+- ocr
+- enterprise-ai
+- knowledge-extraction
 ---
+
+# InfoBay.AI Infographic Dataset Catalogue
+
+## Overview
+
+The **InfoBay.AI Infographic Dataset Catalogue** is a professionally curated collection of **90,000 infographic images** designed for Artificial Intelligence, Computer Vision, Document Understanding, Visual Question Answering (VQA), Optical Character Recognition (OCR), and Multimodal Foundation Models.
+
+The collection includes high-quality infographic assets covering business intelligence, education, finance, healthcare, science, technology, analytics, and documentation. The dataset has been serialized into **Apache Parquet** for efficient storage, cloud-native distribution, and large-scale AI training while preserving the original filenames, directory hierarchy, and binary image data.
+
+The original image files can be reconstructed exactly from the provided Parquet files.
+
+---
+
+# Dataset Statistics
+
+| Property | Value |
+|----------|------:|
+| Dataset Name | InfoBay.AI Infographic Dataset Catalogue |
+| Asset Type | PNG / JPEG |
+| Total Images | 90,000 |
+| Storage Format | Apache Parquet |
+| License | CC BY 4.0 |
+
+---
+
+# Dataset Categories
+
+The collection covers a diverse range of infographic styles and industries, including:
+
+- Business & Finance
+- Education
+- Healthcare
+- Technology
+- Science
+- Data Analytics
+- Reports
+- Documentation
+- Charts
+- Graphs
+- Diagrams
+- Timelines
+- Process Flows
+- Presentations
+- Statistical Visualizations
+
+---
+
+# Primary AI Applications
+
+This dataset is suitable for training and evaluating models in:
+
+- Computer Vision
+- Document AI
+- OCR
+- Vision Language Models (VLMs)
+- Large Multimodal Models (LMMs)
+- Visual Question Answering (VQA)
+- Image Captioning
+- Image Retrieval
+- Knowledge Extraction
+- Automated Report Generation
+- Educational AI
+- Presentation AI
+- Search Indexing
+- Enterprise Search
+- Retrieval-Augmented Generation (RAG)
+
+---
+
+# Enterprise Applications
+
+- Business Intelligence
+- Educational Platforms
+- Analytics Dashboards
+- Document Automation
+- Knowledge Management
+- Search Engines
+- Digital Libraries
+- Enterprise AI Systems
+- Marketing & Presentation Automation
+- Visual Search Platforms
+
+---
+
+# Storage Format
+
+The dataset is distributed in **Apache Parquet** format.
+
+Each row represents one original infographic image.
+
+Typical schema:
+
+| Column | Description |
+|---------|-------------|
+| relative_path | Original file path |
+| filename | Original filename |
+| extension | File extension |
+| size | Original file size (bytes) |
+| content | Binary image data |
+
+The complete original directory structure can be restored programmatically from the Parquet dataset.
+
+---
+
+# Why Apache Parquet?
+
+Apache Parquet offers several advantages for large-scale AI datasets:
+
+- Efficient compression
+- Faster loading
+- Reduced storage requirements
+- Cloud-native architecture
+- Hugging Face compatibility
+- Streaming support
+- Distributed processing
+- Scalable data pipelines
+
+---
+
+# Loading the Dataset
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("YOUR_USERNAME/YOUR_DATASET_NAME")
+
+print(dataset)
+```
+
+---
+
+# Example
+
+```python
+sample = dataset["train"][0]
+
+print(sample["filename"])
+print(sample["extension"])
+print(sample["size"])
+print(sample["content"])
+```
+
+---
+
+# AI Research Use Cases
+
+Researchers can leverage this dataset for:
+
+- Infographic Classification
+- Document Understanding
+- Layout Analysis
+- OCR Benchmarking
+- Visual Retrieval
+- Multimodal Representation Learning
+- Chart Understanding
+- Knowledge Graph Construction
+- Information Extraction
+- Automated Educational Content Generation
+
+---
+
+# Citation
+
+If you use this dataset in research, publications, or commercial applications, please cite:
+
+```bibtex
+@dataset{infobay_infographic_dataset_2026,
+  title     = {InfoBay.AI Infographic Dataset Catalogue},
+  author    = {InfoBay.AI},
+  year      = {2026},
+  publisher = {InfoBay.AI},
+  license   = {CC BY 4.0}
+}
+```
+
+---
+
+# License
+
+This dataset is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license.
+
+You are free to:
+
+- Share — copy and redistribute the material in any medium or format.
+- Adapt — remix, transform, and build upon the material for any purpose, including commercial use.
+
+Under the following condition:
+
+- Attribution — Appropriate credit must be given to **InfoBay.AI**, a link to the license must be provided, and any modifications should be clearly indicated.
+
+For the complete license, visit:
+
+https://creativecommons.org/licenses/by/4.0/
+
+---
+
+# Disclaimer
+
+This dataset is provided for research, educational, and enterprise AI development purposes. Users are responsible for ensuring compliance with all applicable copyright laws, intellectual property rights, and licensing obligations when using or redistributing the dataset.
+
+---
+
+# Acknowledgements
+
+The **InfoBay.AI Infographic Dataset Catalogue** has been curated to advance research in Computer Vision, Document AI, Vision-Language Models, Multimodal Learning, Knowledge Extraction, and Generative AI. We hope this collection accelerates innovation in intelligent document understanding, educational technologies, and enterprise AI solutions.
+````