LIS-S 301 Data Policy and Governance
- Prerequisites: None
- Delivery: Online
- Semesters offered: Fall, Spring, Summer (Check the schedule to confirm.)
This course surveys data and information ethics and policy, justifying data practices per ethical frameworks. Students examine data-policy concerns governing contextual data flows and the systems on which they rely. Students distinguish the results of data policies and the manner they are used to support particular values.
This course emphasizes the importance of understanding policy and governance concerns with regards to data creation, access, ownership, and use. Students will gain an understanding of crucial data policy and governance principles, as well as emergent issues. Students will consider data governance and policy from a social, political, ethical, and legal perspective. Students will explore how socio-technical systems and data flows impact data policy and governance practices. Additionally, students will explore data policy and governance from various perspectives and context.
Program Learning Outcomes Supported
Instructors map their courses to specific Data Science Program Learning Outcomes (PLOs). Mapped program goals drive the design of each course and what students can expect to generally learn.
- C1: Information Science - Demonstrate an understanding of the data lifecycle, including data curation, stewardship, and long-term preservation.
- C4: Information Science - Understand the characteristics of various data types generated and used by a variety of disciplines, subdisciplines, research communities, and government organizations.
- C6: Information Science - Analyze data policies to compare possible outcomes.
- D2: Data Ethics - Identify and understand the social, political, ethical, and legal aspects of data creation, access, ownership, service, and communication.
- E1: Other Topics - Design, conduct, and write up results of research.
- Summarize and communicate key concepts in data policy and governance.
- Identify and interpret the social, political, ethical, and legal aspects of data creation, access, and ownership.
- Describe and explain emerging data policy and governance issues by engaging in discussion.
- Interpret and analyze data policies by comparing and contrasting possible outcomes.
- Analyze socio-technical systems and data flows by describing potential informational opportunities and challenges.
- Analyze and evaluate policies in relation to specific data and information flows in various contexts.
Profiles of Learning for Undergraduate Success (PLUS) Alignment
Instructors align their courses with the Profiles of Learning for Undergraduate Success. The profiles provide students various opportunities to deepen disciplinary understanding, participate in engaged learning, and refine what it means to be a well-rounded, well-educated person prepared for lifelong learning and success.
- P2.1 Problem Solver – Think critically
- P2.3 Problem Solver – Analyzes, synthesizes, and evaluates
- P3.2 Innovator – Creates/designs
- P4.3 Community Contributor – Behaves ethically
- P4.4 Community Contributor – Anticipates consequences
Module 1: Introduction to Course
- Course Basics and Course Navigation
- Course Structure and Schedule
- Course Technology
- Course Textbook
- Writing Resources and Student Engagement Roster
- How to Create a Video
Module 2: The Role of Data Governance
- What is Data Governance?
- Why is Data Governance Important?
- Benefits of Data Governance
Module 3: Ensuring Data Governance
- Data Governance Structure
- Data Governance Components
Module 4: Metadata management and data governance
- Metadata, Types of metadata, metadata repositories
- Master data management
Module 5: Data quality
- Data quality standards
- Impact of data quality on organizational governance
Module 6: Semantic analytics and ontologies
- What is semantic analytics?
- What are ontologies?
- The role of semantic analytics and ontologies in data governance
- Medical services ontology
Module 7: Data privacy, security, and compliance
- Types of data privacy
- Primary considerations for data governance
- Regulatory considerations
Module 8: Adaptive data governance
- Adaptive leadership
- AT-Ease Model
Module 9: Health Information Exchange
- Health information exchange – history and implementation
Module 10: Case Studies
- State-level HEI governance
- Legal Issues with HIPAA
- Mobile Health
- Risk Assessment
Module 11: Banking data
- Banking data, history and regulations
- Information Governance Framework
Module 12: Health Data
- Data governance infrastructures
- Big data and healthcare
- Tensions between data sharing and data privacy
Module 13: Emerging data governance
Module 14: Open Science and Data Science
- Open Data
- Responsible data governance, accountable algorithms
Module 15: Mobile devices and cloud computing
- Technological impacts on data governance
- Regulations for mobile data
- Data governance taxonomy for the Cloud
Policies and Procedures
Please be aware of the following linked policies and procedures. Note that in individual courses instructors will have stipulations specific to their course.