Hofelich Mohr, AliciaJohnston, Lisa RLindsay, Thomas A2016-06-212016-06-212016978-0-8389-8799-5https://hdl.handle.net/11299/181127This chapter appears as Chapter 4 in the 2016 book "Databrarianship: The Academic Data Librarian in Theory and Practice" edited by Lynda Kellam and Kristi Thompson and published by the ACRL. ISBN-13: 978-0-8389-8799-5Data management encompasses the practices and people that acquire, control, protect, deliver and enhance the value of data throughout the research lifecycle. Done well, data management requires that these practices and people be connected throughout the entire research lifecycle. However, much of this work takes place in researchers’ own offices or labs or with the help of specialized support offices on campus, who only directly interact with researchers at single points in their projects. In academic libraries, a data management specialist may only interact with researchers at the beginning and end of a project, assisting with the creation of a data management plan (DMP) and preservation of the data when the research is completed. This poses a challenge when trying to help researchers integrate best practices into their workflows throughout the planning, collection, and analysis stages. Most libraries are focused on providing broad, public access to the content under their stewardship, and given this mission, libraries alone may not be able to offer all of the data services that our researchers need (for example, dark archives for sensitive or private data). Therefore, given the diverse nature of research data and the distributed support researchers may seek throughout their project, universities need a well-connected, distributed way to support data management; it is a service that “takes a village.”endatacurationresearch lifecycleBook chapter