1. Gisella Stalloch Cliff Snellgrove

2. Understand how scientists manage their data Determine data management issues in specific scientific fields Determine best approach in developing a standard data management schema Current opinions on scientific data management

3. Science in an information-dominated age..."information-enabled science allows us to dare to observe and model the complex (DOE management)." NIH and new NSF requirements http://sciencemuseum.org.uk/WhoAmI/FindOutMore/You rgenes/Whatwasthehumangenomeproject/Whathappeneda fterthehumangneomeproject.aspx

4. Interviewing select faculty from STEM departments at Syracuse University Coding of interviews and content analysis Survey created from interview results Based off of interviews and survey, help OSP develop a guideline that would expedite data management proposal process

5. Faculty selected for interviews  Recommended by OSP Question design  Consulted with Dr. Qin, OSP, and previous questions by John D’Ignazio Consent and confidentiality  Institutional Review Board (IRB)  Sensitive data

6. 1. What Directorate and Program funds your research? 2. What kind of outputs emerge from your research? 3. How do you currently manage your data? 4. How much data do you produce? 5. What data management practices do you feel are holding back advences in your research field.

7. 6. Have you contributed data to disciplinary or community data repositories? Challenges? 7. Would an SU data repository benefit your research and data management practices? If yes, how so? 8. Do you see any challenges to depositing your data in an SU institutional repository?

8. Interviewees were anonymized and given “P” numbers e.g. P1, P2, etc. Answers were “coded” to group topics. ParticipantQ#PassageCode categoryCodeNotes P11a 5-year NSF career grant funding sourceNSF P12The lab produces peer-reviewed papers, books, articles, conference presentations, workshops, and reading groups. They will also produce an interactive web site. output typesPeer-reviewed papers, books, articles, conference presentations, workshops, and reading groups

9. Funding All interviewees at least partially funded by NSF Output All interviewees produced peer-reviewed material Only two interviewees considered data sets or coding as output

10. Data management plan  Only one interviewee had a DM plan- project specific  All interviewees were concerned more with data storage  Secure department servers  Encrypted jump drives  Websites and databases  Copies on multiple hard drives  Online storage (i.e. Mozy)  Computer storage

11. All interviewees were willing to use an SU repository Concerns/suggestions  Confidentiality and compliance/ control of access  Curation and active IT support  Flexible formatting- All were concerned with data loss with format changes  Multiple platforms and ease of use  SU must have a flexible open data policy

12.  Periodically survey faculty  Questions targeted to STEM faculty about managing data  Integrate the iSchool with the STEM researchers to curate their data  Facilitate compliance with NSF and SU data management policies  Provide structured hands-on experience for iSchool students  IT/iSchool could provide researchers with current information and support about new and emerging research technology