1. Management and Mining of Spatio-Temporal Data Rui Zhang http://www.csse.unimelb.edu.au/~rui The University of Melbourne

2. 2 Subject Information Topic: Management and Mining of Spatio-Temporal Data Form: summer intense subject Subject code and name: COMP90005 Advanced Studies in Computing 6B No LMS website. Subject homepage: http://ww2.cs.mu.oz.au/~rui/spatio-temporal.htm No textbook, all materials from subject homepage Time: three weeks

3. 3 Objective Introduction to spatio-temporal data management and mining Basics of databases, queries, indexes Spatial queries and indexes Spatio-temporal queries and indexes Location-based social networks Graphs, basics on graph mining algorithms Cloud computing and MapReduce Trajectory data management and mining, trajectory privacy Skills for understanding advanced research papers, writing top conference/journal papers, and paper reviewing in this area Outcome Knowledge and ideas about the above topics Ability to read (large) research code and modify the code for your own use Ability to understand key quality indicators of research papers and write reviews on such papers Who is subject for: PhD students Master-by-research students Master-by-course students who are interested in doing research to obtain basics to enter more advanced research in this exiting area.

4. 4 More Subject Information Feature First time offered, may or may not be offered again Guest lecture every other day – Academics from our department Interactive and exploratory learning – nature of research, sooooo don’t be upset if things are not perfect. Provisional schedule (see website); tolerance Enrolment / Withdraw Those who are not enrolled: we will not mark any assignments or report from you, so please do NOT submit them. Contact: 9 days: 3 hours lecture + 1 hour lab on most days Total 36 contact hours, but expect a workload of 120 hours. Because this is an intense subject, you might want to spend some after-hours Expectation Come to lectures and actively participate in class discussions Do all the assignments and reports by yourself Work hard in these three weeks

5. 5 Assessment Two lab assignments: 30 marks Assignment 1: Spatial queries Due Friday of 1 st week Assignment 2: MapReduce Due Friday of 2 nd week Challenge queries from both due together with Final Report Proposal of a data structure, 500 words: 10 marks Must submit a draft describing the idea: Due Thursday of 2 nd week and feedback will be provided to you Final proposal of data structure due as part of Final Report Presentation of reviewing one assigned paper: 15 marks Group of three students presenting the paper itself and your review on the paper, on Monday of 3 rd week. Paper review assignments: 45 marks Due as part of Final Report To pass the subject, you must get at least Lab assignments: 12 out of 30 Data structure proposal: 5 out of 10 Presentation: 7 out of 15 Overall: 50 out of 100 NOTE: all assignments and reports are individual work except for the presentation of reviewed paper.

6. 6 Academic Misconduct 25%50%75%100%0 Probability of NOT getting caught Workload Do it by yourself Try to plagiarize