Breakthrough Seminar in Data Sciences
Syllabus
Note: The Breakthrough Seminar is a new Special Topics MLIS offering that permits self-selected
students in the Masters Program to study the work of leaders in Data Science,
and meet the researchers themselves.
This unusual course format requires that participants read papers prior
to the meeting with each visitor. Speakers will visit approximately every other
week. The Breakthrough Seminar carries 1.5 credits per semester, and a student
may take two such seminars as part of the course credit for either degree.
Instructors: Paul Kantor
Office: 310 SC&I
Class website: sakai.rutgers.edu
Telephone: 732 932 7500 x8216
email: paul.kantor@rutgers.edu
homepage: scils.rutgers.edu/~kantor
Office hours: Thursday
4:30-5:30 Friday 2:30-3:30
17:610:589:01 SPECIAL TOPICS VIII Sub title: Data Sciences Seminar Credits: 1.5 Instructor: Kantor, P. Stop point: 10 By Arrangement
Catalog Description
Data Sciences are
the new and fundamental sciences that drive the fast-moving disciplines of
Information Science. The Seminar will examine an overview of some of the key
issues in those sciences, including social and collaborative information
behaviors, information behaviors, and associated socio-political issues in the
development of global systems to serve individual needs.
Instructional
Objectives
This course will help you to explore:
· How data systems are organized and built;
· The complexities that result from scale and scope;
· How computers can process the language that we naturally create and understand;
· How concepts and their names drift, merge and split with the passage of time;
· How experts and the general public can collaborate to improve access to all kinds of knowledge; and,
· How you yourself might contribute new ideas and technologies to the field of data sciences.
Learning Objectives
If this course accomplishes its learning goals
· You will be able to discuss the key challenges of the data sciences
· You will be able to analyze and compare different approaches to the information sciences
· You will be able to understand, present and lead a discussion on one or more of the specific research papers selected over the course of the semester.
· You will be able to ask appropriate questions of researchers in the data sciences.
Course Schedule
Please see the separate Schedule in the course home page. The course will meet once a week, at 4:00 on Wednesdays.
Course Structure
Generally, after an initial organizational meeting, even-numbered weeks (2,4,…) will be devoted to discussion of two papers by the upcoming speaker. The following week the seminar will be presented by the invited outsider speaker. This course is collocated with the Yahoo! Data Sciences Seminar, which is supporting the expenses of the speaker series.
Assignments and
Assessment
Critical reviews of
readings
Each week, we will assign one or two readings relevant to that week’s topic. You are required to submit, no later than midnight of the Monday following the assignment of readings, a summary discussion of the readings. This review should summarize the main points of each reading, and articulate your understanding of how they relate to each other, and to other issues that matter to you, if any. Please use an .rtf or .doc format, 12 point Times New Roman with 1” margins all around, and not more than three pages, including references. Submit papers via your Sakai DropBox. I will try to read all of the papers, and will comment, using track changes (that’s why I would prefer that you not use .pdf) , on the most important points.
Threaded Discussion
Each week, there will be a Threaded Discussion of the readings, and of the topic in general. We expect you to submit one modestly original contribution to the discussion, and to comment courteously on one or more of the other students’ contributions. Your contributions will be assessed according to their substance. This is where you can raise questions about the readings or the topic in general, and also where you can critically comment on the readings, or on the topic in general. We would like to complete the threaded discussion before the seminar where we discuss the paper, as your comments will help the person who is presenting the paper to us.
THE FINE PRINT
Assessment
Your final grade will be based on these three different activities. The Critical Reviews and the Threaded Discussion components will each contribute 30% to your final grade, and the Presentation of a Selected Paper will contribute 40%. You are expected to attend each session.
Late Submission
If you find that you are unable to complete one of the assignments on time, please tell us in advance and explain why. Late submission will reduce the grade by the smallest available step on the Rutgers letter scale (e.g. A -> B+). Students are expected to attend all classes; if you expect to miss one or two classes, please use the University absence reporting website - https://sims.rutgers.edu/ssra/ - to indicate the date and reason for your absence. An email will automatically be sent to me from this system. Note that if you must miss classes for longer than one week, you should contact a dean of students to help verify your circumstances.
Readings
The readings for the course will be listed in the course Bibliography, in the course home page. Many of these readings will be made available to you in Resources section.
Academic Integrity
The consequences of scholastic dishonesty are very serious. Rutgers’ academic
integrity policy is at http://ctaar.rutgers.edu/integrity/policy.html.
An overview of this policy may be found at http://cat.rutgers.edu/integrity/student.html.
Multimedia presentations about academic integrity may be found at http://academicintegrity.rutgers.edu/multimedia.shtml
and http://www.scc.rutgers.edu/douglass/sal/plagiarism/intro.html
For sad examples of the consequences of failures of academic integrity, consider these two real-world cases L:
http://www.guardian.co.uk/world/2011/mar/01/german-defence-minister-resigns-plagiarism