Page History

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Survey Results as of Sept 21, 2008:

Discussion about the first set of Survey results:

*Data Management Survey*

The data management survey was mailed to the DASIG EDUCAUSE constituent group email list. The survey asks respondents to self-rate in nine data management categories. To date, there have been 21 responses. Results are in a spreadsheet available on the wiki: https://spaces.at.internet2.edu/download/attachments/2972/data_management_responses.xls^{Image Added}

(AI) (Mike Fary) will send a reminder to the DASIG list seeking additional respondents. (AI) (Jim Phelps) will seek permission to send the survey link to the EDUCAUSE CIO list. Jim will also send the survey link to the ITANA email list.

The highest self-ranking are in the data management and data security management areas. The lowest marks are in the data architecture and data warehousing areas. The data governance area has evenly distributed results.

The last question, "which areas are most critical to you and your institution," probably could have been two separate questions; answers for the institutional perspective and the IT perspective may differ. Two areas received more than 50 percent of the votes: data security management, and data warehousing and business intelligence management.

The survey results will be discussed at both the DASIG and ITANA sessions at EDUCAUSE. These face-to-face meetings will provide an opportunity to probe deeper on the items on the survey and hear feedback about which data management topics seem most important right now.

There were other areas of interest:

The data governance responses are bimodal. What are the similarities among the group at 8 and the group at 4 and under?
Data warehousing received uniformly low rankings.
Two institutions self-rated at 10 on the data security issues. (AI) (Jim Phelps) will follow-up with those institutions to determine if they would do case studies in that area.
There may also be potential case studies for those institutions that self-rank highly in the governance area. (AI) (Mike Fary) will follow-up with those institutions.

One of the next steps, once the survey is completed, is to identify the high achievers and determine whether there are best practices to capture. (AI) As a way to identify those achievers, Mike Fary will graph the survey results by institution.

(AI) (Jim Phelps) will follow up with these high achievers, suggesting case studies, online presentations/webinars, and determining whether there are helpful URLs with information about the respondents' areas of achievement.

Example Use Cases

1. Online archives of University functions - Duke Chapel, recordings of events.
2. Multimedia archives of class support materials (not just lectures but also study materials, etc)
3. Images as class materials but also products of artist's work (Art history as well visual studies)
4. Research data - as it pertains to new NIH rules
5. Research data as institutional asset housed at the institution
6. Research data of Duke PIs at other institutions or on google docs or in the "computing cloud"
7. E-mails as electronic archives under e-discovery rules
8. Logs as electronic archives of access to systems and actions taken.

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