• Grow and nurture the open-source data/infra community—launch initiatives, collaborate with data-focused groups, and organize events or challenges. • Promote the Hugging Face Hub as the go-to platform for data storage, versioning, and collaboration—curate and showcase datasets, benchmarks, and tools like Xet. • Highlight use cases like efficient large dataset updates, Parquet editing, and deduplication to demonstrate the Hub’s value for data workflows. • Create demos, benchmarks, and tools (e.g., Colab notebooks) to illustrate best practices for data storage and versioning. • Experiment with Xet, Parquet, and other data formats to showcase their potential for ML and data engineering. • Produce high-quality tutorials, blog posts, and videos that make complex topics accessible. • Share insights on storage optimization, dataset versioning, and deduplication to empower developers. • Actively participate in online communities (Discord, GitHub, forums) to highlight contributions, answer questions, and foster collaboration. • Ensure datasets and tools released on the Hub are well-documented, with clear examples, benchmarks, and use cases.