An open dataset is data that anyone can access, download, and reuse, subject to the provider’s license. A license may permit broad reuse or restrict the dataset to academic and research purposes rather than commercial applications. section 2.2
Open datasets provide important raw material for large language models (LLMs). Repositories such as Hugging Face contain collections of online writing, while Common Crawl makes a massive web-page archive publicly available. Companies may combine these resources with purchased, scraped, or specially created data. section 2.2
Typical open datasets include:
- Millions of Reddit posts, sometimes filtered to retain only English-language material. section 2.2
- News articles and reviews from Amazon and Rotten Tomatoes. section 2.2
- Questions and answers from Stack Exchange and pages gathered by Common Crawl. section 2.2
Accessibility can widen participation in research and model development, but openness does not guarantee balanced representation. English web data is especially abundant, and datasets concentrated in the United States and Western Europe can make LLMs serve those languages and perspectives better than others. section 2.2 section 4.12
ImageNet and shared datasets
ImageNet illustrates how a large shared dataset can shape a field. Its millions of labeled images helped establish a standard for comparing computer-vision models and encouraged the wider sharing of benchmark datasets for training and testing. section 4.12
