Update README.md

README.md

@@ -30,4 +30,223 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc0-1.0
+language:
+- en
+size_categories:
+- 100K<n<1M
+tags:
+- ocr
+- handwriting-recognition
+- library-science
+- glam
+pretty_name: Boston Public Library Card Catalog
 ---
+
+# Boston Public Library Rare Books Card Catalog Dataset
+
+## Dataset Description
+
+This dataset contains approximately **410,000 digitized catalog cards** from the Boston Public Library's Rare Books Department card catalog. The cards represent the main entry catalog (author/title cross-referenced) covering printed materials from various historical periods.
+
+### Why This Dataset?
+
+Historical card catalogs are rich sources of:
+
+- **Bibliographic information** structured in semi-standardized formats
+- **Handwritten and typewritten text** from multiple time periods and catalogers
+- **Historical cataloging practices** including subject classification and cross-referencing
+- **Metadata about rare and historically significant materials**
+
+This dataset is valuable for training and evaluating AI models on:
+- OCR and handwriting recognition for historical documents
+- Information extraction from semi-structured text
+- Layout analysis of document formats
+- Vision-language model performance on library/archival materials
+
+### Dataset Summary
+
+- **Total Cards**: ~410,000 individual catalog cards
+- **Total Drawers**: 386 drawers organized alphabetically
+- **Image Format**: JPG (converted from JP2)
+- **OCR Coverage**: ~100% (Tesseract 5.x via Internet Archive)
+- **Source**: [Internet Archive - BPL Rare Books Catalog](https://archive.org/details/bplrbcatalog)
+- **Original Institution**: Boston Public Library Rare Books Department
+
+## Dataset Structure
+
+### Data Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `image` | Image | JPG image of the catalog card (~800-1000px width) |
+| `drawer_id` | string | Internet Archive item identifier (e.g., "248-pach-palmas") |
+| `card_number` | int | Card position within drawer (0-indexed) |
+| `filename` | string | Original filename of the card image |
+| `text` | string | OCR-extracted text from the card (Tesseract 5.x) |
+| `has_ocr` | bool | Whether OCR text is available for this card |
+| `source` | string | Attribution string |
+| `source_url` | string | Direct link to source drawer on Internet Archive |
+| `ia_collection` | string | Internet Archive collection identifier |
+
+### Data Splits
+
+This dataset contains a single `train` split with all catalog cards.
+
+### Example
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("davanstrien/bpl-card-catalog")
+
+# Access a sample
+sample = dataset['train'][0]
+print(f"Card #{sample['card_number']}")
+print(f"OCR Text:\n{sample['text']}")
+
+# Display the card image
+sample['image'].show()
+```
+
+### Typical Card Contents
+
+Catalog cards typically contain:
+- **Author names** (surname, forename)
+- **Book titles** and subtitles
+- **Publication information** (publisher, place, date)
+- **Physical description** (pages, illustrations, size)
+- **Call numbers** and shelfmarks
+- **Subject headings** and cross-references
+- **Notes** on condition, provenance, or special features
+
+## Dataset Creation
+
+### Source Data
+
+The cards were originally created by Boston Public Library catalogers over many decades, representing a historical record of the library's rare books collection. The physical cards were digitized by BPL and uploaded to the Internet Archive with OCR processing.
+
+### Collection Process
+
+1. **Digitization**: Boston Public Library photographed each drawer of cards
+2. **OCR Processing**: Internet Archive applied Tesseract OCR to create searchable text
+3. **Dataset Creation**: Images were extracted from JP2 archives, converted to JPG, and paired with OCR text
+
+### Data Processing
+
+- Original format: JP2 images in ZIP archives on Internet Archive
+- Converted to: JPG at 95% quality for ML compatibility
+- OCR format: HOCR (HTML with bounding boxes) → plain text extraction
+- Organization: Preserved original drawer organization and card order
+
+## Uses
+
+### Example Use Cases
+
+**OCR Model Evaluation**
+```python
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+
+processor = TrOCRProcessor.from_pretrained('microsoft/trocr-base-handwritten')
+model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-base-handwritten')
+
+# Evaluate on catalog cards with ground truth OCR
+for sample in dataset['train'].select(range(100)):
+    pixel_values = processor(sample['image'], return_tensors="pt").pixel_values
+    generated_ids = model.generate(pixel_values)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+    # Compare with ground truth
+    print(f"Ground truth: {sample['text'][:100]}")
+    print(f"Generated: {generated_text[:100]}")
+```
+
+**Information Extraction**
+```python
+# Extract structured bibliographic data
+import re
+
+def extract_author(text):
+    # Authors typically appear at start, often in "Surname, Forename" format
+    lines = text.split('\n')
+    if lines:
+        return lines[0].strip()
+    return None
+
+# Process cards to extract authors
+authors = [extract_author(card['text']) for card in dataset['train']]
+```
+
+**VLM Evaluation**
+```python
+from transformers import AutoProcessor, AutoModelForVision2Seq
+
+processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b")
+model = AutoModelForVision2Seq.from_pretrained("HuggingFaceM4/idefics2-8b")
+
+# Ask questions about catalog cards
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image"},
+            {"type": "text", "text": "What is the author and title of this book?"}
+        ]
+    }
+]
+
+for card in dataset['train'].select(range(10)):
+    text = processor.apply_chat_template(messages, add_generation_prompt=True)
+    inputs = processor(images=[card['image']], text=text, return_tensors="pt")
+    outputs = model.generate(**inputs, max_new_tokens=100)
+    print(processor.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Bias, Risks, and Limitations
+
+### Known Biases
+
+1. **Historical Language**: Cards use terminology that may be considered offensive by modern standards, reflecting historical cataloging practices and societal biases.
+
+2. **Western Canon Bias**: The collection reflects the collecting priorities and interests of a major American library, which historically focused on Western European and American materials.
+
+3. **Cataloger Variation**: Cataloging practices evolved over time; older cards may use different standards than newer ones.
+
+### OCR Limitations
+
+- **Handwriting Variation**: Some cards are handwritten with varying legibility
+- **Typewriter Quality**: Older typewritten cards may have faded or unclear text
+- **Special Characters**: Diacritical marks, mathematical symbols, or non-Latin scripts may be incorrectly recognized
+- **Layout Complexity**: Multi-column layouts, annotations, or crossed-out text may confuse OCR
+
+## Additional Information
+
+### Dataset Curators
+
+- **Digitization**: Boston Public Library Rare Books Department
+- **Hosting & OCR**: Internet Archive
+- **Dataset Creation**: Daniel van Strien ([@davanstrien](https://huggingface.co/davanstrien))
+
+### Licensing Information
+
+The catalog card images are in the **public domain** as works of the U.S. government or works whose copyright has expired. The dataset is released under **CC0 1.0 Universal (Public Domain Dedication)**.
+
+### Acknowledgments
+
+- **Boston Public Library** for digitizing this invaluable historical resource and making it publicly accessible
+- **Internet Archive** for hosting the collection and providing OCR processing
+- The **catalogers** who created these cards over many decades, preserving knowledge about rare books
+
+### Links
+
+- **Source Collection**: https://archive.org/details/bplrbcatalog
+- **BPL Guide**: https://guides.bpl.org/rarebooks/book-search
+- **Statement on Harmful Language**: https://guides.bpl.org/rarebooks/book-search#s-lg-box-27736072
+
+### Version History
+
+- **v1.0** (2025): Initial release with ~410,000 cards from 386 drawers
+
+### Contact
+
+For questions about this dataset, please open an issue in the dataset repository