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As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier for the users to keep track of the analyses being performed and datasets being generated, and to enable the users to understand and analyze the work ows. In this paper, we describe our vision of a uni ed provenance and metadata management system to support lifecycle management of complexdoi:10.1145/3077257.3077267 dblp:conf/sigmod/MiaoCD17 fatcat:ofr25bj2trewri4ksbwtq3wxgu