LIS-S 583 Data Curation and Management
3 credits
- Prerequisite(s): LIS-S 500, LIS-S 507; one of any S503, S584, or S634
- Delivery: Online
- Semesters offered: Fall (Check the schedule to confirm.)
Description
This course introduces the active curation and management of data throughout its lifecycle to enhance its value for scholarship, science, education, industry, and other stakeholders. Students explore data activities, such as access policies and implementation, data reuse, data design through content-creator management, data entry into databases or repositories, and metadata creation.
Program Learning Goals Supported
Instructors map their courses to specific LIS Program Goals. Mapped program goals drive the design of each course and what students can expect to generally learn.
- Curate Collections for Designated Communities
Learning Outcomes
Instructors develop learning outcomes for their courses. Students can expect to be able to achieve the learning outcomes for a given course after successfully completing the course.
- Assess the need for long-term data curation in public and private venues, its benefits, and limitations.
- Conceptualize data curation activities and terms.
- Analyze the characteristics of various data types generated and used by a variety of disciplines, subdisciplines, research communities, and government organizations.
- Apply theoretical understanding to practical issues in data curation.
- Analyze the activities associated with each stage of the data curation lifecycle and their social, legal, ethical, and policy implications.
- Evaluate existing data curation tools and technologies to create a solution to different curation issues in the real-world context by applying data curation concepts, terms, and theories.
- Analyze critical issues associated with the storage, backup, and security of data to create a solution.
- Analyze new roles and responsibilities for data curators in many sectors.
- Create a data preservation and management plan.
Course Overview
Instruction is in Canvas. Lessons are organized into Modules whose length may vary.
Module 1: Overview of data, data practice, and data curation
- Introduction to the course
- What are data? Research data?
- What is data curation?
- Why do we care? Who should care?
Module 2: Data and its impact on our society
- Role of data
- Data lifecycle; research data lifecycle
- Impact on our society
Module 3: Open data, data sharing and reuse
- Why data sharing and reuse?
- Obstacles of sharing and reuse
- Sharing policies
- Role of curation in sharing and reuse
Module 4: Type, formats, and stages of data
- Different data types and formats
- Disciplinary data
- Curation action associated with stages of data
Module 5: Small data, big data, and curation approach
- Data curation lifecycle
- Difference between big and small data
- Curation approaches for big and small data
Module 6: Data management plan (DMP) and policy
- What is DMP?
- Federal policy
- DMP requirements used to characterize and plan
Module 7: Data organization and documentation
- Data documentation
- Contextual information to make data meaningful
- Metadata
- Challenges
Module 8: Data provenance
- Concept of provenance
Module 9: Fall Break
Module 10: Data storage, backup, preservation, and security
- Importance of data preservation
- Best practices for research data storage, backup, access control, migration to newer storage media, and security
Module 11: Data archives and repositories
- Types of available repositories/archives (discipline-based, institutional, etc:)
- Data ingest and manipulation in repository context (repository perspective)
- Understand process issues for depositing data in repository (sharer perspective)
Week 12: Intellectual property, copyright, and data licensing
- Data ownership considerations related to data sharing
- Publisher and licensing restrictions on re-use of data (difference between CC0, Public Domain, and OpenData Licenses)
- Ethical considerations related to data sharing
Module 13: Legal and ethical consideration
- Privacy levels for research data as required by potential funding agencies
- Confidentiality issue in data
- Ethical data reuse
Module 14: Technologies associated with data curation and management
- Persistent identification
- Unique identification of digital objects
- Digital Object Identifiers
- CrossRef
- Open Archives Initiative protocols OAI-PMH and OAI-ORE
- Research Objects and provenance
- Linked open data for data
- Namespaces, URLs, and versions of record
Module 15: Thanksgiving Break
Module 16: Roles of Informational professionals in data curation
- What’s the value of archives and libraries?
- What’s the role? How do they respond?
- New jobs
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.