Friday, January 24, 2014

Mar: Data Management (Library Juice Academy)

March 3-29, 2014      Credits: 1.5 CEUs
Price: $175

"Digital information lasts forever or five years, whichever comes first" - Jeff Rothenberg, RAND
Petabytes of scientific data are produced on a regular basis, but could be lost in as much time if they are not properly captured and curated for future use, nor marked up in a way that allows for discovery and reuse by researchers. What can we do to help? Librarians, archivists, and information professionals bring many necessary skills to the realm of scientific data. For instance, developing necessary metadata, standards, and systems of classification, or establishing an archival plan for data selection, migrating data forward, and creating finding aids that capture the placement of data in its milieu for the user, or finally developing appropriate databases and technologies to support data creation, preservation, discovery, and reuse to capture data earlier in the data lifecycle rather than asking for deposition after the publication is away. As institutions are largely being held responsible for the long-term preservation and hosting of scientific research data, data librarianship within the context of academic and special libraries is both viable and necessary for those who have an interest.
As a relatively new area, data management is a place where individuals can make a difference by bringing our expertise to this timely need. The purpose of this course is to explore the processes of data production and data management, and the role of LIS professionals and institutions in supporting data producers. The course will cover the following topics:
- The role and lifecycle of research data
- Data curation lifecycle
- Stakeholders and stakes
- The role of institutions and libraries
- Data curation and preservation strategies
- Tools for writing data management plans
- Repositories and registries
- Metadata standards
During the course students will be exposed to various policy reports and current research, and will result in the preparation of an NSF or NIH data management plan and an institutional data management plan.