Data handling and management are perennial challenges in science, and data cleaning is usually ranked as our most laborious and time-consuming piece of that. The work is typically difficult to document and replicate, especially when our goals are comprehensive: datasets that are accurate, machine-readable, human-readable, and computation-ready.
We track some tools and approaches in our latest blogpost - EarthCube CRESCYNT Toolbox: Data Cleaning. https://crescyntblog.wordpress.com/2017/09/30/crescynt-toolbox-data-cleaning/ Cheers, Ouida Ouida W. Meier, Ph.D. Data Manager, ‘Ike Wai ITS - Cyberinfrastructure & EarthCube CRESCYNT Coral Reef Science & Cyberinfrastructure Network University of Hawai‘i http://crescynt.org https://crescyntblog.wordpress.com
