Course Description and Goals
This course introduces students to important and fundamental topics in data and search informatics. It is appropriate for the incoming CS or Informatics graduate student who has an interest in the area of data and search and wants to learn more. It is also appropriate for graduate students outside the School of Informatics who want a better understanding of the key concepts in the area. It is offered once a week in the evening, and does not require programming experience.

The course will be taught seminar style where discussion of the material is facilitated by a faculty who has expertise in the area. Common threads running through the course ensure the student has a unified understanding.

Since this may be the first seminar course a graduate student will take, the course will spend time on how to read and understand scholarly papers in the field. The course is open to all students of a graduate standing. A good comfort level with computing concepts is desired but not necessary.

Students will be asked to study assigned scholarly papers prior to the time they are discussed, and will be expected submit abstracts on each assigned paper. As the semester progresses, a student's analysis of a particular work or topic should reflect an understanding of the topics already covered. The course will culminate with each student's presentation of a written work they have done that explores one of the topic areas of data and search.

Please feel free to contact Professor Groth or Professor Plale with questions.

Agenda:

• Week 1 (Sep 8): course intro and data visualization (Groth and Plale)
• Week 2 (Sep 15): metadata foundations (Robertson)
• Weeks 3-4 (Sep 22,29): ethical, social, and legal dimensions of data (Shankar)
• Weeks 7-8 (Oct 6,13): queries/searches over large and complex data (Groth)
• Weeks 5-6 (Oct 20, 27): indexing techniques for data and XML representation and storage (Wu)
• Weeks 9-10 (Nov 3, 10): provenance of data: its capture and use (Plale)
• Weeks 11-12 (Nov 17,24): knowledge/artificial intelligence; use case applied to provenance (Leake)
• Weeks 13-14 (Dec 1,8): languages and expressiveness (Van Gucht)
• Week 15 (Dec 15): student presentations