Future Aspirations in Graph Datasets

This chapter explores the future aspirations for datasets within graph theory, emphasizing the need for more accessible and detailed real-world data. It examines the complexities in graph learning, the challenges of current frameworks, and advocates for ongoing dataset curation to support innovation in research.