ICS 624 Advance Data Management (Spring 2015 CRN 89405)

General Information

Class Meets: Mon and Wed 10:30 - 11:45 am Room Holmes 247
Final Exam : None.
Instructor : Lipyeow Lim
Office Hours : Time Mon Wed 1:30-2:30PM POST 303 E or by appointment 808-956-3495
No Textbooks are required for this course. Readings will be drawn from a range of papers published in top data management conferences. Students without any background in data management should consider reading (parts of) the following two references:
- Architecture of a Database System
- Introduction to Information Retrieval
Student Learning Outcomes: At the end of this class, the successful student would
- have gained a broad understanding of the research issues in a range of data management topics including Big Data, Data warehousing, Parallel databases, Map-reduce Query optimization, IR and Web Search, Streaming systems, XML Data, Graph Data and ontologies, Data Integration, Data Mining, Energy Efficiency.
- have gained the skill of reading and critiquing research papers
- have gained the skill of performing basic research in a course project
Late policy: work submitted past due date and time will receive zero credits.
All students are expected to conduct themselves above and beyond the standards set forth in the University of Hawaii Systemwide Student Conduct Code.
Any student who feels s/he may need an accommodation based on the impact of a disability is invited to contact the instructor privately. The instructor would be happy to work with you, and the KOKUA Program (Office for Students with Disabilities) to ensure reasonable accommodations in the course. KOKUA can be reached at (808) 956-7511 or (808) 956-7612 (voice/text) in room 013 of the Queen Lili'uokalani Center for Student Services.

Topics

Big Data, Parallel databases and Map-reduce
Data warehousing, data mining and data analytics
Mobile Data Management and Energy Efficiency
Query optimization
IR and Web Search
Streaming systems
Graph Data and ontologies
Data Integration

This is a seminar-format course and readings will be drawn from recent articles published in the following conferences/journal: SIGMOD, VLDB, ICDE, EDBT, CIKM, WWW, SIGIR, Mobisys, MDM.

Grading (Tentative)

20 % Class Participation (Discussion Leader duties)
20 % Homework (Paper Reviews)
60 % Research Project

Class Schedule (tentative)

Paper reviews are due in Laulima->Discussions BEFORE the class which discusses the paper. Each student is expected to lead discussions at least three times during the semester.

Week	Date	Topic	Readings	Remarks

Readings and links

Reading List
Architecture of a Database System
Introduction to Information Retrieval
Google Map Reduce: Lecture 1 | Lecture 2
Distributed FS, GFS, HadoopFS: Map Reduce Lecture 3 | HadoopFS
NoSQL vs SQL

Useful Links

Info on LaTeX. Windows users should install MikTex. Linux users should install latex (usually tetex) using their respective software package managers. Mac users should use MacTex.
If you need to typeset algorithms in LaTeX, please use one of the algorithms latex package (see wikibook) to typeset pseudocode (algorithmic.sty is recommended).
If you need to draw diagrams for inclusion in your homework, use a diagramming software and export to eps or pdf format and include it in your latex source using the includegraphics command. Dia is a good open-source diagramming tool that runs on most platform. If you are using X windows in cygwin or unix or mac, xfig is also a very good diagramming tool.
Online Latex Authoring tool
Screencast-o-matic Free Screencast software for creating recorded presentations.
UHM Spring 2013 Academic Calender