LIS-S 202 Data Organization and Representation
3 credits
- Prerequisite(s): None
- Delivery: Online
- Semesters offered: Fall (Check the schedule to confirm.)
Description
This course introduces approaches for organizing and representing data and information resources. Students learn the principles of data organization, documentation, description, and classification devised to provide access to these resources and methods to evaluate and improve them for future retrieval and reuse.
The organization and representation of information are vital to understand how information and data are structured. As the value of data has become more important to society, the need to understand how these data are structured has become more imperative. In this course, students will gain an understanding of the key approaches and structures to organize and represent information and data. This course is a required course for the Applied Information Science Minor and Applied Data and Information Science Major curriculum.
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.
- E1: Other Topics - Design, conduct, and write up results of research.
- E2: Other Topics – Understand tools and techniques of project management.
Learning Outcomes
- Recognize distinctions between data, information, and knowledge.
- Understand the basic principles and functions of representational structures such as taxonomy, ontology, thesauri, metadata, and folksonomy.
- Compare and discriminate between various organization systems.
- Understand the basic principles of data organization including file name conventions, version control, and data documentation.
- Apply the principles of consistency and uniformity to recognize the need for authorized terms for describing various types of data.
- Understand the need for data standards and metadata standards.
- Understand and effectively apply principles of representation and systems of organization to provide access to resources in a variety of information environments.
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
- P3.1 Innovator – Investigates
Course Overview
Module 1: Introduction to Data Organization and Representation
- Provides a historical view of data organization and representation
Module 2: Data and Representation
- Examines data from the perspective of computing systems
Module 3: Encoding Standards
- Brief history of encoding and how it is used in computing systems
- Encoding types
- Encoding standards
Module 4: Introduction to Metadata
- Overview of metadata
- Metadata types
- How metadata is used to represent and organize data in computing
Module 5: Metadata, Part 2
- Implementation
- Tools and techniques
- Schemas
- Everyday use
Module 6: Access and Authority Control
- Addresses how data are made available to users, how relationships about information objects are identified, and how access points and authority control impact those relationships among information objects
Module 7: Describing Relationships and Structures
- Explores the relationships and structures among digital objects in organizational systems
Module 8: Resource Description
- Examines resource descriptions from the conceptual perspective
- Metamodels (JSON, XML, and RDF) and data structures
- Syntax and real-world application
Module 9: Metadata and XML
- Discusses practical aspects of metadata
- How metadata is applied and the mechanisms that metadata performs
- Sharing data using XML
Module 10: Taxonomies, Ontologies, & Folksonomies
- Defines and differentiates among each of these terms
- Roles and uses in computing systems
Module 11: Semantic Web
- Provides a historical overview of the Semantic Web and how it is implemented to connect information
Module 12: Linked Data
- Examines the concept of linked data and explains why/how it is necessary to ensure full-scale integration of the Semantic Web, with the assistance of RDF and OWL
Module 13: FAIR Data
- Introduces and explores the concept of FAIR data -- a recent development in finding ways to improve scientific data management to ensure that data is findable, accessible, interoperable, and reusable (FAIR)
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.