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- Structure of the University
- Departments, Divisions, Groups
- Different organizations within the campus might have conflicting views of this data
- For example, a research group that reports to one unit but is funded by another.
- Names and network IDs from an LDAP directory
- Personnel records from Human Resources
- Must be filtered to remove sensitive data.
- Grants information from the Office of Sponsored Funds
- Because of data challenges, this data is only harvested a few times each year.
- List of classes from the Registrar's Office
- Publications from a faculty reporting system
- This also provides many challenges.
- For example, two co-authors may provide slightly different names for the same journal article, or for the journal itself.
- If the data comes from a well-curated source (e.g. PubMed), the challenges of data cleaning are greatly reduced, but the challenges of disambiguation are increased.
- In the on-campus faculty reporting system, it is common practice to use an ID that definitively associates the data with the faculty member.
- When reading from a public source, are these the same auithors authors or different authors?
- James L. Fox
- J. L. Fox
- J. Leroy Fox
- James L. Foxx
- This also provides many challenges.
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