<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">DATASET REQUEST</span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; font-style: italic; vertical-align: baseline;">What: Request for identification of a data set </span></div><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; font-style: italic; vertical-align: baseline;">Why: Offer of assistance with data set by a data curation student</span></div><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; font-style: italic; vertical-align: baseline;">Course: Foundations in Data Curation</span></div><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; font-style: italic; vertical-align: baseline;">When: January-May 2015</span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">We work with a Data Curation Specialization certification program team at the University of Illinois Urbana Champaign Graduate School of Library and Information Science (UIUC, GSLIS). Taught since 2007 as part of the MSLIS program, this one-semester Foundations of Data Curation (DC) course integrates as much exposure to data issues and direct experience with data as possible. </span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">In recent semesters we have found that hands-on experience with authentic data sets noticeably improves student class engagement and understanding of data curation. Students are able to work effectively upgrading, ingesting, and/or rescuing a dataset. For instance, students improve their skills by enriching documentation, structuring for ingestion, and reformatting to accessible formats.</span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">Students select a dataset at the start of the course and continue working on it in phases: 1) investigating & selecting a dataset; 2) developing a data management plan for improving the dataset; and 3) implementing the plan given available time and resources. Each dataset has an associated contact but communication with the dataset contact is restricted until the student has demonstrated to the instructors that they have mastered an understanding of the data and related available resources including papers or reports in the peer reviewed literature. </span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">There is an expectation that if a student substantially improves the metadata documentation or the state of the data that the repository would consider using the results of their work. For instance, the National Snow and Ice Data Center is currently in the process of publishing datasets worked on by students, datasets that would not otherwise be publically available. In addition to contributing to data availability, this approach represents an opportunity for a) students to provide a pointer to an example of data curation work on their vitae and b) repositories to enhance visibility of some data as well as to highlight their contributions to education and training of a much needed workforce in data curation. </span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">If you have data that require attention and are interested in having a data curation student work with your data sets as a class project, please contact us. We need to have your data sets in hand by January 20.</span></div><br><div style="line-height: 1; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">Ruth Duer, </span><a href="mailto:rduerr@nsidc.org" style="text-decoration:none;"><span style="font-size: 16px; font-family: Cambria; color: rgb(0, 0, 255); text-decoration: underline; vertical-align: baseline;">rduerr@nsidc.org</span></a><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">, National Snow and Ice Data Center</span></div><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">Karen Baker, </span><a href="mailto:ksbaker2@illinois.edu" style="text-decoration:none;"><span style="font-size: 16px; font-family: Cambria; color: rgb(0, 0, 255); text-decoration: underline; vertical-align: baseline;">ksbaker2@illinois.edu</span></a><span style="font-size: 16px; font-family: Cambria; vertical-align: baseline;">, UIUC Graduate Student in Data Curation</span></body></html>