LIS-S 400 Topics in Applied Data and Information Science
3 credits
- Prerequisite(s): None
- Delivery: On-Campus, Online
- Semesters offered: Spring (Check the schedule to confirm.)
Description
This course covers specific topics in applied data and information science. It may be repeated for credit when the topic varies. The same course number is used for different courses.
Topics include:
Global Digital Services
This is a course for Study Abroad: Finland. This experience is comprised of two learning components. The first is a semester-long course taken by local students alongside others from Finland for a global classroom experience (graduate: LIS S531, undergraduate: INFO I400), and those traveling abroad will take an additional 3 credits starting in spring but terminating during summer session 1. LIS S604/S400 will offer students the opportunity to collaborate with students at Haaga-Helia University of Applied Sciences in Helsinki, Finland. This course will begin in the spring semester and continue at our cooperating institution during summer I. In the spring semester, students from the IU Indianapolis campus will be partnered with students from the Haaga-Helia campus and follow the course together via Canvas and other tools. The online course in the spring will provide technological and conceptual knowledge in skills such as HTML, CSS, and information architecture that will be practiced and refined in collaborative course projects. For Indiana University students who wish to go abroad, part of spring semester will also be devoted to academic sessions in anticipation of the international travel. All projects will be finalized at the end of spring semester but with the option to further collaborate with their partners. In the first half of summer session 1, students will have the opportunity to reconvene in Helsinki to discuss and pursue their projects with their collaborators at Haaga-Helia University. In Finland (not limited to Helsinki) the students’ activities will be supplemented by field trips and site visits relevant to the class as well as to Finnish culture in general via visits to historic sites, museums, industries, and cultural events. Our partner institution is Haaga-Helia University of Applied Sciences in Helsinki, Finland. However, we will not need to use classroom facilities at the University, although that is an option. Most lectures will have been accomplished before arrival. On-site activities include meetings, class visits, and lectures.
Learning Outcomes
Data Literacy
- Distinguish between data, information, and knowledge.
- Recognize that data can have value and play a key role in society by providing opportunities to expand knowledge, to innovate, and to influence.
- Analyze datasets in context to determine data veracity including bias in data collection or representation.
- Assess values with respect to the use of data technologies.
Data Science
- Organize, visualize, and analyze large, complex datasets using descriptive statistics and graphs to make decisions.
- Apply inferential statistics, predictive analytics, and data mining to informatics-related fields.
- Assess the purpose, benefits, and limitations of visualization as a human-centered data analysis methodology.
- Conceptualize and design effective visualizations for a variety of data types and analytical tasks.
- Identify, assess, and select appropriately among data analytics methods and models for solving real-world problems, weighing their advantages and disadvantages.
- Understand data science concepts, techniques, and tools to support big data analytics.
Information Science
- Demonstrate an understanding of the data lifecycle, including data curation, stewardship, and long-term preservation.
- Apply the principles of consistency and uniformity to recognize the need for authorized terms for describing various types of data.
- Understand the principles of data organization including file name conventions, version control, and data documentation.
- Understand the characteristics of various data types generated and used by a variety of disciplines, subdisciplines, research communities, and government organizations.
- Understand critical issues associated with the storage, backup, and security of data.
- Analyze data policies to compare possible outcomes.
Data Ethics
- Understand the relation between data, ethics, and society.
- Identify and understand the social, political, ethical, and legal aspects of data creation, access, ownership, service, and communication.
- Develop substantive arguments using ethical reasoning to suggest improvements to data-driven systems and practices.
- Differentiate between surveillance systems that promote and inhibit values.
Other Topics
- Design, conduct, and write up results of research.
- Understand tools and techniques of project management.
- Understand legal and business aspects of technology and media.
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.