Management and Mining of Spatio-Temporal Data

Rui Zhanghttp://www.csse.unimelb.edu.au/~rui

The University of Melbourne

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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

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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.

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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

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Assessment Two lab assignments: 30 marks

Assignment 1: Spatial queries Due Friday of 1st week Assignment 2: MapReduce Due Friday of 2nd 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 2nd 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 3rd 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.

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Academic Misconduct

25% 50% 75% 100%0 Probability of NOT getting caught

Workload

Do it by yourself

Try to plagiarize