Xinformatics Class Spring 2010

Instructors: Professor Peter Fox, TA Mandeep Singh
Meeting times: Tuesday morning 9:00 am - 11:50 am. SAGE 3705;
Office Hours: Monday 3-4pm in Winslow 2120 or by appointment at JSC 1C22
phone: 276-4862
Class Listing: XINFORMATICS
* ITEC 4962/6961 53353/53354
* ERTH 4963/6963 53355/53356
* CSCI 4960/6960 53357/53358

Description

In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems. This course will introduce informatics, each of its components and ground the material that students will learn in discipline areas by coursework and project assignments.

Topics for Xinformatics/ Foundations:

* Introduction to informatics
* State-of-the-Art examples; bioinformatics
* Capturing the problem: Use case development and requirement analysis
* Information theory, models, tools
* Foundations; semiotics, library, cognitive and social science
* Information life-cycle
* Information architectures (Internet, Web, Grid, Cloud)
* Information Visualization,
* Information and Workflow Management
* Information Discovery, Information Integration

Xinformatics Applications:

* Geoinformatics
* Astroinformatics
* Cheminformatics
* Bioinformatics
* Helioinformatics
* Health informatics
* Ecoinformatics

Xinformatics Project options (examples):

* Information Management for collaborative web sites
* Information Modeling for Health Sciences: Patient Records
* Information Architecture Analysis Case Study: GEOSS
* Information Management for Disasters: Earthquakes
* Information Content, Content and Structure Analysis: Library Information Systems

Syllabus/ Calendar

Refer to Reading/ Assignment/ Reference list for each week (see below).

Week 1 (Jan. 26): Introduction to informatics slides
Week 2 (Feb. 2): State-of-the-Art examples; bioinformatics slides
Week 3 (Feb. 9): Capturing the problem: Use case development and requirement analysis slides
Feb. 16: no classes, Tuesdays follow Wednesday schedule
Feb 23: class cancelled.
Week 4 (Mar. 2): Information systems theory slides
Mar. 9: no classes - spring break
Week 5 (Mar. 16): Foundations; semiotics, library, cognitive and social science and class exercise - information modeling slides
Week 6 (Mar. 23): Information architectures theory and practice (Internet, Web, Grid, Cloud) and class exercise for project definitions slides
Week 7 (Mar. 30): Class presentations for assignment 3
Week 8 (Apr. 6): Class cancelled.
Week 9/10 (Apr. 13): Information life-cycle and visualization and project definition check-in/ discussion (critiquing a design and iterating) slides
Week 11 (Apr. 20): Information and Workflow Management slides
Week 12 (Apr. 27): Information Discovery, Information Integration slides
May. 4: no class, work on final project and presentations
Week 13 (May. 11): Final class and term presentations

Academic Integrity

Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own. Acts, which violate this trust, undermine the educational process. The Rensselaer Handbook of Student Rights and Responsibilities defines various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. Submission of any assignment that is in violation of this policy will result in a penalty. If found in violation of the academic dishonesty policy, students may be subject to two types of penalties. The instructor administers an academic (grade) penalty, and the student may also enter the Institute judicial process and be subject to such additional sanctions as: warning, probation, suspension, expulsion, and alternative actions as defined in the current Handbook of Student Rights and Responsibilities. If you have any question concerning this policy before submitting an assignment, please ask for clarification.

Objectives

* To instruct future information architects how to sustainably generate information models, designs and architectures
* To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers
* For both to know tools, and requirements to properly handle data and information
* Will learn and be evaluated on the underpinnings of informatics, including theoretical methods, technologies and best practices.

Course Learning Objectives

Through class lectures, practical sessions, written and oral presentation assignments and projects, students should:

* Understand and develop skill in Development and Management of multi-skilled teams in the application of Informatics
* Understand and know how to develop Conceptual and Information Models and Explain them to non-experts
* Knowledge and application of Informatics Standards
* Skill in Informatics Tool Use and Evaluation

Assessment Criteria

* Via written assignments with specific percentage of grade allocation provided with each assignment
* Via oral presentations with specific percentage of grade allocation provided
* Via group presentations
* Via participation in class (not to exceed 10% of total)
* Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day

Suggested Prerequisites

* Knowledge such as that gained in a Data Base class (e.g., CSCI-4380)
* Knowledge such as that gained in a Data Structures class (e.g., CSCI-1200)
* Knowledge such as that gained in a Data Science class (e.g. ITEC/CSCI/ERTH 6961-01)
* or permission of the instructor

Reading/ Assignment/ Reference List

Class 1 Reading Assignment: Xinformatics Applications - State of the Art

Clinical Informatics: [1]
Clinical Informatics, Medical Device Connectivity: [2]]
Urban Informatics: [3]
Geo Informatics: [4]
Astro Informatics: [5], [6]
Bio Informatics: [7]

Class 2: Reading Assignment: Use case development and requirement analysis

Required:

Optional:

Use case template

Partial use case example 1

Partial use case example 2

Class 3: Reading Assignment: Information theory, models, tools

no reading

Assignment 1

Class 4: Reading Assignment:

Information entropy

Information Is Not Entropy, Information Is Not Uncertainty!

More on entropy

Sequence logos

Awareness in Context-Aware Information Systems

Context

Compression and encoding: D.A. Huffman, "A Method for the Construction of Minimum-Redundancy Codes", Proceedings of the I.R.E., September 1952, pp 1098–1102