This document discusses challenges and opportunities in managing large volumes of scientific data from various sources like experiments, simulations, literature, and archives. It advocates making all scientific data available online to increase scientific information velocity and productivity. Key aspects of scientific data management discussed include data ingest, common schemas, organization, sharing, querying, modeling, documentation, curation and long-term preservation. The cloud is presented as a way to democratize access to scale and analytics for scientific data.