Professor, Department of Management Information Systems
Academic Director, Executive Doctorate in Business Administration
Director of Research Projects and Reports, Institute for Business and Information Technology
Fox School of Business, Temple University
207G Speakman Hall (006-00)
1810 N. 13th Street, Philadelphia, PA 19122
Email: David.Schuff at temple.edu
The Benefits and Costs of Using Metadata to Improve Enterprise Document Search
People spend up to 20% of their time searching for documents they never find. While many argue that metadata can improve enterprise document search, in reality few organizations use metadata. This article describes the results of two experiments that evaluate the impact of metadata on enterprise document search effectiveness. The first study provides quantitative evidence of the increase in recall and precision from the use of metadata-enhanced searches. The second study demonstrates that simple metadata structures are nearly as effective as complex ones, implying that the cost of creating and maintaining metadata is likely much lower than one might expect.
[Reference: Schymik, G., Corral, K., Schuff, D., and St. Louis, R.D. “The Benefits and Costs of Using Metadata to Improve Enterprise Document Search,” Decision Sciences. 46(6) (December 2015). pp. 1049-1075.]
Data Science for All: A University-Wide Course in Data Literacy
Infusing data literacy into a curriculum is an unrealized opportunity for higher education to truly make an impact on the current generation as they prepare to move into the workforce. This paper describes the design and structure of a new, unique undergraduate elective course introduced into the curriculum of a large, public University in the Northeastern United States. The design of the course is designed to inspire an “evidence-based” mindset, encouraging students to identify and use data relevant to them in their field of study and the larger world around them. The paper includes the course goals mapped to specific learning objectives, examples of exercises and assignments, a reading list, and a course syllabus. Instructors and institutions interested in bringing data science concepts to a broad audience can use this course as a foundation to build their own curriculum in this area.
[Reference: Schuff, D. “Data Science for All: A University-Wide Course in Data Literacy.” in the Proceedings of the 2015 Business Analytics Congress, Fort Worth, Texas. December 13, 2015]