INF 385T - Special Topics in Information Science: Metadata Generation and Interfaces for Massive Datasets
Graduate standing. Additional prerequisites may vary with the topic.
Study of the properties and behavior of information. Technology for information processing and management.
Three lecture hours a week for one semester.
May be repeated for credit when the topics vary.
Metadata Generation and Interfaces for Massive Datasets
Large-scale digitization projects as well as increasing quantities of born-digital materials have put enormous collections of documents and data within our reach. The use of programmatic techniques is necessary for managing such massive collections and improving their utility for specific purposes. The ability to blend understanding of digital collections, computational techniques (such as machine learning, data mining, image, audio, or video processing, data analysis), user experience design that you gain from this course will enable you to.craft small projects that demonstrate the viability of your proposed solutions to your supervisors, whether in academic institutions, not for profit organizations, start ups, or large corporations.
Using a hands-on, project-based learning approach in a studio setting, this course will enable you to synthesize competencies from several other courses taught in the iSchool for enhancing collections using techniques such as metadata extraction, generation, and the design of targeted user interfaces in order to enable novel mechanisms for accessing digital collections. Early in the semester, we will define team projects and the criteria for evaluating the outcomes of our efforts during the semester. Each week, we will review the progress made by teams, use the class session to develop targeted skills, and to set objectives for the following week.
During the Fall 2015 semester, we will develop projects in the cultural heritage domain with an emphasis on developing transferable competencies such as user interface design, database design, and programming.
There is no textbook for this course. All readings and reference
materials will be available online.
* assess the quantitative and qualitative aspects of large
* generate or retrieve metadata from documents and Web-based
* design storage structures (such as database schemas or XML
documents) for extracted metadata
* craft user interface widgets and features for supporting users
in accessing the data to address the target problem
* develop scripts that interface with third-party RESTful or
* evalute the developed scripts, techniques, and algorithms
Graduate standing and knowledge of a programming language
(examples: PHP, Python, Java, C++)
Familiarity with at least one of the following with a willingness
to self-learn the other quickly
Using an external API ( examples: MySQL or file APIs in PHP,
Data modeling (examples: Entity-relationship diagrams, databases,
Please contact me if you have doubts or concerns about satisfying
these criteria. I am more than happy to discuss your individual
case and suggest an appropriate course of action to maximize your
10% - Project proposal (due in late Sept.)
10% - User interface prototype and system architecture (due Oct.
10% - Evaluation plan (due in early Oct.)
10% - Evaluation report (due in early Dec.)
30% - Project implementation
10% - Adherence to programming style guides
10% - class participation (individual)
10% - peer evaluation (individual)