The UCI Machine Learning Repository has been a tremendous resource for empirical and methodological research in machine learning for decades. Yet with the growing number of machine learning (ML) research papers, algorithms and datasets, it is becoming increasingly difficult to track the latest performance numbers for a particular dataset, identify suitable datasets for a given task, or replicate the results of an algorithm run on a particular dataset. To address this issue, CML Professors Sameer Singh and Padhraic Smyth along with Philip Papadopoulos, Director of UCI’s Research Cyberinfrastructure Center (RCIC), have planned a “next-generation” upgrade. The trio was recently awarded $1.8 million for their NSF grant, “Machine Learning Democratization via a Linked, Annotated Repository of Datasets.”