LIS-S 305 Data Curation and Management
3 credits
- Prerequisite(s): None
- Delivery: Online
- Semesters offered: Spring (Check the schedule to confirm.)
Description
This course introduces concepts of data curation and management with applications. This course understands data curation as an active and ongoing management of data through its lifecycle, and adding values to the data in a way to be useful to scholarship, science, education, and any other relevant stakeholders (e.g., business, industry). Students explore the characteristics of data and data-curation lifecycle activities, such as the design of data through content-creator management; metadata creation; entry into a database system or a repository; access policies and implementation; and data reuse.
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.
- A1. Data Literacy - Distinguish between data, information, and knowledge.
- A2. Data Literacy - Recognize that data can have value and play a key role in society by providing opportunities to expand knowledge, to innovate, and to influence.
- A4. Data Literacy - Assess values with respect to the use of data technologies.
- C1. Information Science - Demonstrate an understanding of the data lifecycle, including data curation, stewardship, and long-term preservation.
- C2. Information Science - Apply the principles of consistency and uniformity to recognize the need for authorized terms for describing various types of data.
- C3. Information Science - Understand the principles of data organization including file name conventions, version control, and data documentation.
- C4. Information Science - Understand the characteristics of various data types generated and used by a variety of disciplines, subdisciplines, research communities, and government organizations.
- C5: Information Science - Understand critical issues associated with the storage, backup, and security of data.
- D1: Data Ethics - Understand the relation between data, ethics, and society.
- 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.
Learning Outcomes
- Recognize the urgency of and need for long-term data curation in public and private venues.
- Understand the characteristics of various data types generated and used by a variety of disciplines, sub-disciplines, research communities, and government organizations.
- Understand both theoretical and practical issues in data curation from a range of perspectives.
- Describe data curation concepts, terms, tools, and technologies.
- Identify the activities associated with each stage of the data curation lifecycle and their social, legal, ethical, and policy implications.
- Understand roles and responsibilities for data curators.
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.
- P1.4 Communicators – Conveys ideas effectively
- P2.1 Problem Solver – Think critically
- P2.2 Problem Solver - Collaborates
- P2.3 Problem Solver – Analyzes, synthesizes, and evaluates
- P3.1 Innovator – Investigates
Course Overview
Module 1: Introduction to the Course Module
- Course Basics
Module 2: Introduction to Data Curation
- What are data? What is data curation? Activities and incentives for data curation
Module 3: Data Curation History
- eScience, cyberscholarship, core skills for research data work, new skills for digital curation
Module 4: The Data Lifecycle & Conceptual Models
- The Digital Curation Centre (DCC) and the DCC Lifecycle Model,
- Consultative Committee for Space Data Systems (CCSDS) and the Open Archival Information System (OAIS) Model:
Module 5: Data Conceptualization, Designing, and Creation
- Defining data, digital objects, and databases
- Designing data, creating or receiving data
Module 6: Metadata
- Metadata definition and types, metadata in relation to the curation process, preservation metadata, metadata standards
Module 7: Ingesting and Storing Data
- Actions and processes for ingesting data
- Information packages
- Activities and considerations for storing data
Module 8: Data Preservation Methods
- Preservation aims and actions
- Comparison of different preservation methods
Module 9: Data Archives and Repositories
- Data storage principles and practices
- Various repository systems
- Cloud services
Module 10: Additional Curation Considerations
- The role of trust in data curation, appraisal and selection, technical tools for data curations, and open data and data sharing
Module 11: Ethical and Legal Considerations
- Copyright, intellectual property, and privacy
- Data science ethics
Module 12: Small Data Curation
- Big science and small science
- Small data curation infrastructures
Module 13: Big Data Curation
- Characteristics of big data and small data
- Models, tools, and techniques for big data curation
Module 14: Data Curation in Practice
- Real-world examples of how data curation is applied in various contexts
Module 15: Review and Prep for Final Exam
- Course wrap-up and final exam guidance
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.