CIRSS faculty and students will participate in the upcoming 9th International Digital Curation Conference (IDCC) to be held February 24-27 in San Francisco. This year's theme, "Commodity, catalyst or change-agent? Data-driven transformations in research, education, business & society," will focus on how data-driven tools and services allow us to explore, manage, use, and benefit from the world around us.
Preparing the workforce for digital curation: The iSchools perspective
Organized by Carole L. Palmer
This panel will discuss the work of the study committee on Future Career Opportunities and Educational Requirements for Digital Curation in relation to educational programs in iSchools and expected workforce trends.
Scientific research group data management practices and local data repositories
Baker, K. S.
Research groups in the earth and environmental sciences are beginning to address new expectations for data management and data sharing aimed at providing data access. Further, a variety of sizes and configurations of data repositories have emerged in the last decades. Preparing data for release to a digital repository requires development of new data management practices particularly when scientific inquiry involves the heterogeneity of data associated with fieldwork in the natural sciences (Borgman, 2012; Parsons et al., 2011). This study focuses on repositories associated with project-oriented communities of data generators typically tied to a geographically specific site. What are the characteristics of research-oriented data repositories? What is their impact on scientific research groups (SRGs)? What decisions do scientists make about their data and data practices? Existing SRGs that have close ties with a local data repository provide an opportunity to investigate an array of data and repository arrangements.
Exploring description for research data in soil science journal publications
Curating data collections in the classroom: lessons learned
Duerr, R. & Chao, T.
Data curation issues in transitioning a field science
collection of long-term research data and artefacts from a local
repository to an institutional repository
Kaplan, N. E., Draper, D. C., Paschal, D. B., Moore, J. C., Baker, K. S., & Swauger, S.
A long-term place-based research effort in ecology, such as the Shortgrass Steppe Long-Term Ecological Research (SGS-LTER) project, produces a plethora of research data, articles, and other artefacts. These materials represent an extensive knowledge base created by a collaborative community over time. After thirty years of continuous interdisciplinary support for research (Lauenroth and Burke, 2008) and data management (Stafford et al., 2002) for the shortgrass steppe of eastern Colorado, the SGS-LTER site is being decommissioned and will no longer be funded as an LTER site after 2014. Currently, one focus of SGS-LTER information management is to complete submission of all datasets in the SGS data repository to the LTER Network Information System (NIS, Baker et al. 2000, Michener et al., 2010) prior to the end of funding. A second high priority activity is partnering with the Colorado State University Institutional Repository (CSU IR) to ensure that collections of artefacts, digital data and other objects remain open and available to local researchers who will continue their research on the shortgrass steppe by other means and may seek to append, revise and use their data. The SGS-LTER presents an example of a project with a rich legacy of data and information, in a variety of forms and file types, which if preserved in a local repository will continue to support local research efforts as well as contribute to advancing our understanding of ecology through data use.
Data Curation Education in Research Centers: Formative evaluation results from 2012-2013 cohorts
Palmer, C. L., Thompson, C. A., Mayernik, M. S., Williams, V., & Allard, S.
A citation analysis of “Data Publications” in Earth systems science
Weber, N. & Mayernik, M. (2014, February). 9th International Digital Curation Conference, San Francisco, CA
Automating the classification of author contribution statements
Weber, N. & Thomer, A.