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Presentation

We have spent the semester getting familiar with multiple topics in of databases. Some topics were practical (e.g., how to use a few non-relational databases) and some were algorithmic (e.g., probabilistic algos, B-trees) Now, it is your turn to lead the class and help everyone understand something that you are interested in.

Topic Selection

Before midnight Friday Oct 25, propose a database related topic that you would like to learn about and lecture on. I may reach out to discuss your topic further. I will use your topic suggestions to organize the lectures following the exam.

Description

For your topic, you and your partner (partner optional) will lead the lecture. You will have two steps:

  • By at least midnight, TWO days before your lecture, post on the discussion board links to resources and a description of what students should do prior to your lecture to be prepared. Sources may be materials that you put together, papers, video, software to install, problems to work through, message board postings, etc. Note that if you need to post content, for example a PDF, Box is a campus supported option for sharing. Students are expected to come prepared to class by working through the material you suggest. Note that you should target the student preparation at under an hour, it should NOT exceed two hours.

  • On the day of your presentation, arrive at least five min early for class to be ready to start on time. You may use between 30-45 min of the lecture period. We will use the last five min to fill out feed back forms. Feel free to get creative. Your lecture may be interactive, you can have people work on problems, write code, discuss in groups, or anything else that you think may help you to introduce the class to your topic.

  • By midnight at most TWO days after your lecture, a (approximately) two page written summary of your lecture (either Markdown or PDF) that will be posted on the course website

  • By midnight at most TWO days after your lecture, a (approximately) one paragraph to one page written reflection from the peer feedback and how you would incorporate that feedback next time you lecture. This will NOT be posted on the course website

    You will be graded on the following:

    As a lecturer:

    • Pre-lecture materials (10 points)
    • Demonstration of knowledge of the presented material (30 points)
    • Preparation of the lecture (20 points)
    • Effectiveness of the lecture (10 points)
    • Lecture summary (15 points)
    • Peer feedback reflection (05 points)

    As a learner:

    • Your participation (10 points)

Schedule

Date Topic Group
11/15 Realtime DBs Prashanta Saha and Saidur Rahman
11/18 DB Security David Kelly and Kemal Turksonmez
11/20 Rainbow Tables Andrew Johnson
11/22 Blockchain DBs Grant Nelson and Singleton
11/25 Multi-objective query planning Mark Harris and Peng Zou
12/02 Community Detection Britney Gibbs and Michael Hewitt
12/04 Streaming Clustering Parker Folkman and Caleb Whitman
12/06 CouchDB versioning & conflict resolution Jerad Hoy and Anna Watson

Deliverables

  • Before midnight Friday Oct 25: email me with the following information: group members (up to 2 per group), topic, potential conflicting dates of team members from 11/18 to the end of semester.

  • Midnight two days before you lecture, post resources on discussion board.

  • Lecture on assigned date.

  • Midnight two days after your lecture, email me summary document.

  • Midnight two days after your lecture, email me reflection writeup.
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