Data-centric AI advocates a paradigm shift towards better, and not just bigger, datasets. As data protection laws with extra-territorial reach proliferate worldwide, ensuring datasets are legal is an increasingly crucial yet overlooked component of "better". To help dataset builders become more willing and able to navigate this complex legal space, this paper reviews key legal obligations surrounding datasets, examines the practical impact of data laws on ML pipelines, and offers a framework for building legal datasets.