This document discusses data curation, which involves maintaining and preserving digital research data throughout its lifecycle. It defines scientific data as factual material necessary to validate research findings, including observational, experimental, simulation, and derived data. The data lifecycle is described using the DataONE model. Key points covered include funder requirements for data management plans from NSF and NIH, benefits of data curation such as transparency and allowing others to analyze and build upon the data, best practices for file naming, types and storage, use of metadata, and resources for data sharing and curation.