After writing my post on the data curation lifecycle a while back, I have been slowly accumulating a bank of academic libraries who offer data management guides. Because data management is now a facet of librarianship that has come to the forefront of our profession, I felt that it was appropriate to explore a number of these university libraries to understand what types of information these guides provide to patrons. For this post, I’ve taken the time to include a brief list of what I believe to be good examples of data management guides with the hope that it will help librarians prepare their own data management guides within their institution. I’ve also included some other resources on this topic that have been helpful to me when learning more about this area.
If any readers know of other useful resources in this area, please send them along to me as this is in no way meant to be a comprehensive list. I think this is an exciting area for librarians (especially medical ones like me), and the libraries below have already done an excellent job in establishing their role within the discipline.
Data Management Resources
The University of Minnesota has an excellent resource guide on data management in that it provides examples of requirements that need to be fulfilled when working with grants such as the NSF; it includes a step-by-step approach to developing a plan; provides examples of existing data management plans to view; and gives reasons as to why data management is important. Minnesota’s library is very active in the data management realm and offer workshops that you can watch online here.
Not surprisingly, MIT offers an impressive resource guide for data management. Included in the guide is everything from a data planning checklist to a page on how to share data in various repositories. What I appreciate about the data sharing component of this guide is that MIT is encouraging it’s researchers to venture into a new area of scholarly publishing. This recommendation is a great approach for attracting university researchers to MIT’s DSpace repository, and other open data sharing repositories.
Like the other data management guides in this list, California’s Digital Library (CDL) provides a nice clean and straightforward approach to teaching their users about data management. I particularly liked their citing data page because it provided easy to follow steps and gave a lot of different examples. What sets CDL apart from the others is that they have the DMPToolkit which is an unbelievable resource that allows for a researcher to create ready-to-use data management plans for specific funding agencies; meet requirements for data management plans; get step-by-step instructions and guidance for data management plan; and learn about resources and services available at your institution to fulfill the data management requirements of their grants.
University of Washington (UW) provides a traditional libguide on the subject of data management. What I like about this particular resource is that they provide very clear instructions on the importance of organization and structure, and take the researchers through the process step by step. Like MIT, UW has a page on the importance of data sharing and provides links to a variety of file sharing and storing services.
Purdue has been a major player in the adoption of data management roles for librarians through the creation of their excellent Data Curation Profiles Toolkit, which provides a guide for librarians to interview researchers about their data and help build a data management plan. The Data Management Hub at Purdue is a stellar example of a library implementing data management practices as they offer everything from examples of Data Management Plans to a Data Plan Self Assessment Tool that you can download in pdf format.
Other Useful Tools
This document contains the 118 headings and questions that make up the DCC’s Checklist for a Data Management Plan
This document provides some simple guidelines for effective data management, which, if put into practice, will benefit the original data owner as well as enhance prospects for the long-term preservation and re-use of the data by other researchers.
This document provides answers to some of the questions the ARL is asking about the most relevant areas for library involvement in e-science projects. It also provides examples of library involvement in the data arena.
While MANTRA is a course designed for PhD students and others who are planning a research project using digital data, it is an excellent introduction to librarians who do not have the experience of working with data management. There are videos of researchers within the course, and mini-exams after each unit to help test your knowledge. I highly recommend it.