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Information Management is an interdisciplinary field concerned with managing, storing, processing, and disseminating information. The key emphasis of Information Management is connecting people with data using technology. Therefore, understanding the human side of information seeking and use is also critical. This track includes such courses as Human Information Behavior, which prepares students to understand how users interact with information, and System Evaluation and Analysis, which allows students to assess and evaluate the performance of information systems in alignment with users’ goals. 

The track is divided into Human-Computer Interaction/User Experience; Data Science; and Information Science. 

Human-Computer Interaction (HCI) and User Experience (UX) shape how users find, understand, and interact with information across websites, digital libraries, databases, mobile applications, enterprise systems, social platforms, and emerging digital environments. Students develop practical skills in organizing content, designing navigation and labeling systems, creating metadata schemas, building database structures, and evaluating usability. Through applied projects, they learn how to translate user needs and organizational goals into functional, scalable information systems. Students gain experience in user research, workflow analysis, wireframing, site mapping, controlled vocabularies, and information governance. The emphasis is placed on balancing user needs, organizational objectives, accessibility, scalability, and long-term sustainability.

The Data Science track prepares graduate students to develop advanced analytical, technical, and critical thinking skills needed to extract meaningful insights from complex and large-scale data. In today’s data-driven environment—across the research, government, nonprofit, cultural heritage, and industry sectors—the ability to manage, analyze, and interpret data is essential for informed decision-making and strategic planning. Data Science courses build competencies in data mining, text analytics, big data processing, statistical modeling, coding (e.g., Python or R), and data visualization.

Information Scientists should have a good understanding of the latest and historical technology trends and utilize technology for appropriate contexts and goals. Graduates of the Information Science track are prepared for such careers as an information architect, UX designer, content strategist, taxonomy specialist, metadata analyst, digital product manager, information systems consultant, data librarian, data curator, data analyst, data engineer, research data specialist, data journalist, and research data manager.

 

Courses for Information Sciences

Required Courses (4 courses: 12 credits)

  • LSC 551: Organization of Information
  • LSC 553: Information Organizations and Communities
  • LSC 555: Information Systems in Libraries and Information Centers
  • LSC 557: The Information Professions in Society

Recommended Electives (Overall IM)

  • 563: Data Visualization
  • 565: Data on the Web
  • 612: Foundations of Digital Libraries
  • 635: Human information Behavior
  • 654: Database Management
  • 656: AI for Information Professionals
  • 675: Research Methods in Library and Information Science
  • 676: Information Ethics and Policy
  • 753: Programming for Web Application 
  • 756: Systems Analysis and Evaluation

Recommended Electives for Specific Areas

HCI/UX

  • 525: User Interface Design and Evaluation
  • 650: Information Architecture and Web Design
  • 615: Metadata

 

Data Science

  • 527: Introduction to Data Science
  • A graduate course on computing from Computer Science (e.g., CSC584 Introduction to Machine Learning; CSC641 Data Mining)

 Information Management Coursework Plan (CWP)

 

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 Updated: July 2026