Committee findings and recommendation
Date
2014-01-31
Authors
ISTeC Data Management Committee, author
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Abstract
Data management is a core competency in most research projects. As datasets grow in volume, velocity and variety, they can quickly become unwieldy. The CSU research community, like those at many other research institutions, is rapidly becoming overwhelmed with data management, diverting time and energy from research projects. A recent survey shows CSU's research community has challenges in storage availability, organization, preservation and collaboration. While there is no panacea for these challenges, much can be done to reduce or eliminate hurdles in the research function. Four initiatives can begin to ease these challenges at CSU: 1. Learn from one another through Affinity groups. Like assembling a puzzle, individuals may hold the key to certain pieces of the puzzle and, through the sharing of ideas and knowledge, puzzles may be partially or wholly assembled. 2. Spread knowledge broadly through easily accessible vignettes that focus on specific data management challenges faced by researchers. 3. Build an information technology infrastructure, including both storage and compute capacity, to facilitate research. 4. Merge the research process with data curation practices to make data management seamless for the CSU research community. Confronting this issue now is important, as some research is churning in the data management morass. Other research institutions are further along than CSU in addressing data management challenges. To remain a viable, competitive and thriving research institution, CSU needs to take action.
Description
ISTeC (Information Science and Technology Center) is a university-wide organization for promoting, facilitating, and enhancing CSU's research, education, and outreach activities pertaining to the design and innovative application of computer, communication, and information systems.
January 31, 2014.
January 31, 2014.
Rights Access
Subject
infrastructure
searchability
research data
scientific data
big data
affinity groups
education
findability