2013 Presentations (Communicative Events)
Comparing Approaches for the Sustainability of Scientific Data Repositories
Sustainable data systems are critical components of the cyberinfrastructure needed to provide long-term stewardship of scientific data, including Earth science data, throughout their entire life cycle. A variety of approaches may help ensure the sustainability of such systems, but these approaches must be able to survive the demands of competing priorities and decreasing budgets over long time periods. Analyzing and comparing various approaches can identify viable aspects of each approach and inform decisions for developing, managing, and supporting the cyberinfrastructure needed to facilitate discovery, access, and analysis of data by future communities of users. A typology of sustainability approaches is proposed, and example use cases are offered for assessing the approaches over time. These examples help illustrate the potential strengths and weaknesses of each approach under various conditions and with regard to different objectives, e.g., open vs. limited access. By applying the results of these analyses to their particular circumstances, systems stakeholders can assess their options for a sustainable systems approach, which may incorporate multiple sustainability options, along with other metrics to ensure the sustainability of the scientific data and information for which they are responsible. In addition, clarifying and comparing sustainability approaches should inform the design of new systems and the improvement of existing systems to meet the needs for long-term stewardship of scientific data, and support education and workforce development efforts needed to ensure that the appropriate scientific and technical skills are available to operate and further develop sustainable cyberinfrastructure.
- DownsChen2013ComparingApproachesSustainability.pdf application/pdf 272 KB Download File
More About This Work
- Academic Units
- Libraries and Information Services
- Published Here
- February 27, 2013
Presented on February 27, 2013 at Research Data Symposium, Columbia University, New York, NY.