Let’s Blend Our Data

During his keynote address at the 2014 Library Assessment Conference, David Kay enthusiastically asserted that libraries are data rich, but our ability to participate in university student or learning analytics initiatives remains “constrained by application silos.” Data blending (or weaving, using David’s terms) facilitates the integration of data from multiple sources, by combining two or more datasets that contain the same data elements, or joining two or more datasets by matching at least one data item.

For example, when a patron establishes an ILLIAD account with the OSU Libraries, he or she must identify a primary department, major or college from a pre-populated list provided by our library. This list, does not necessarily match the list departments, majors, or colleges maintained by various enterprise systems across the university.

If I want to create a profile of ILLIAD use by academic department or college and in relation to the number of undergraduate students who have declared a major within that department or collge, I first need to find a way to blend this data. The OSU Libraries lists Environment and Natural Resources under FAES (Agriculture, Food Science, Natural Resources, etc.) in its ILLIAD system for example, while the university uses the code ENR in its Master Schedule of Classes, and ENVNATR in its system which identifies the number of students who have declared a major.

To create a meaningful report which can be filtered by the librarian assigned to engage an academic discipline, I create a reference file with a column for each of the fields listed below. I then blend this data with information about the librarian who is assigned to engage the academic discipline, such as the library division, library department, or library sub-department.

Subject ENR
ILLIAD Department FAES(Agriculture,Food Science, Natural Resources, etc.)
Major (Academic Plan) ENVNATR
Major Name Environment and Natural Resources
Librarian Email librarian@osu.edu

Once this is done, I join the reference file to the aggregate data I have gathered from various university systems, and voila – subject librarians now can access an enhanced report which hopefully provides better, richer insights into the needs of their constituents.

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