--- dataset_info: - config_name: cartoons features: - name: filepath dtype: string - name: pub_date dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: decimal128(21, 20) - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: prediction_section_iiif_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string splits: - name: train num_bytes: 238959228 num_examples: 206054 download_size: 71381230 dataset_size: 238959228 - config_name: comics features: - name: filepath dtype: string - name: pub_date dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: decimal128(23, 22) - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: prediction_section_iiif_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string splits: - name: train num_bytes: 887230943 num_examples: 526319 download_size: 352764547 dataset_size: 887230943 - config_name: default features: - name: pub_date dtype: string - name: prediction_section_iiif_url dtype: string - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string - name: filepath dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: float64 splits: - name: train num_bytes: 4315793816 num_examples: 3274561 download_size: 1404652833 dataset_size: 4315793816 - config_name: illustrations features: - name: filepath dtype: string - name: pub_date dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: decimal128(22, 21) - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: prediction_section_iiif_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string splits: - name: train num_bytes: 942457956 num_examples: 798475 download_size: 258125239 dataset_size: 942457956 - config_name: maps features: - name: filepath dtype: string - name: pub_date dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: decimal128(22, 21) - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: prediction_section_iiif_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string splits: - name: train num_bytes: 382556331 num_examples: 200188 download_size: 150128611 dataset_size: 382556331 - config_name: photos features: - name: filepath dtype: string - name: pub_date dtype: string - name: page_seq_num dtype: int32 - name: edition_seq_num dtype: int64 - name: batch dtype: string - name: lccn dtype: string - name: box sequence: decimal128(22, 21) - name: score dtype: float64 - name: ocr sequence: string - name: place_of_publication dtype: string - name: geographic_coverage sequence: string - name: name dtype: string - name: publisher dtype: string - name: url dtype: string - name: page_url dtype: string - name: prediction_section_iiif_url dtype: string - name: iiif_full_url dtype: string - name: predicted_type dtype: string splits: - name: train num_bytes: 1971669677 num_examples: 1543525 download_size: 596762379 dataset_size: 1971669677 configs: - config_name: cartoons data_files: - split: train path: cartoons/train-* - config_name: comics data_files: - split: train path: comics/train-* - config_name: default data_files: - split: train path: data/train-* - config_name: illustrations data_files: - split: train path: illustrations/train-* - config_name: maps data_files: - split: train path: maps/train-* - config_name: photos data_files: - split: train path: photos/train-* task_categories: - image-classification - object-detection - image-feature-extraction tags: - glam - lam - newspapers - history pretty_name: Newspaper Navigator license: cc0-1.0 language: - en size_categories: - 1M ⚠️ **Note:** Please use IIIF image APIs responsibly and in accordance with the current [Library of Congress Terms of Use](https://www.loc.gov/legal/). You should still consider the number of requests you make, cache client-side, etc. ### Source - Original dataset: https://news-navigator.labs.loc.gov/ - Paper: Visual Content Extraction from Historical Newspapers - Code: https://github.com/LibraryOfCongress/newspaper-navigator ### Conversion Notes This version of the dataset was prepared using nnanno. The conversion process reformats JSON metadata into structured Parquet files for easier querying and integration with modern ML pipelines. ### Ethical Considerations Working with historical newspaper content requires careful consideration of several ethical dimensions: #### Historical Context and Bias Historical newspapers reflect the biases and prejudices of their time periods Content may include offensive, racist, or discriminatory language and imagery Researchers should contextualize findings within the historical social and political climate #### Responsible Use Guidelines - Avoid decontextualizing historical content in ways that could perpetuate stereotypes - Consider adding appropriate content warnings when sharing potentially offensive historical material - Acknowledge the partial and biased nature of newspaper coverage from different eras #### Technical Limitations and Representation Bias - OCR quality varies significantly across the dataset, potentially creating selection bias in text-based analyses - The machine learning models used to identify visual elements may have their own biases in classification accuracy - Certain communities and perspectives are underrepresented in historical newspaper archives #### API Usage Ethics - The IIIF image API should be used responsibly to avoid overwhelming the Library of Congress servers - Implement caching and throttling in applications that make frequent requests ### Citation ```bibtex @article{visualcontent2020, title={Visual Content Extraction from Historical Newspapers}, author={Benjamin Charles Germain Lee et al.}, journal={arXiv preprint arXiv:2005.01583}, year={2020} } ``` #### Acknowledgments This work draws on the remarkable digitization and metadata efforts of the Library of Congress’s Chronicling America and the innovative Newspaper Navigator project. ### Dataset Contact This conversion of the dataset is created and maintained by [@davanstrien](https://huggingface.co/davanstrien/).