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Information Science Ph.D. With a Concentration in Data Science
Doctoral Degree
Program type:
Major
Format:
Hybrid
Est. time to complete:
3-4 years
Credit Hours:
60 (with master's) or 72 (with bachelor's)
Transform massive amounts of data into actionable insights with information science
and technology.
UNT's Interdisciplinary Information Science Ph.D. program (or IIS Ph.D. program) responds
to the varied and changing needs of the information age by offering a concentration
in Data Science. The concentration is offered jointly with UNT's Department of Information
Technology and Decision Sciences and the Department of Computer Science and Engineering
with the ultimate goal of providing the opportunity for interdisciplinary training,
research and professional services in consumer behavior and experience management.
With this concentration, students will take courses that will prepare them for conducting
research on critical issues in consumer behavior and related areas as they pertain
to the information science perspective.
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Request More InfoWhy Earn an Information Science Ph.D. With a Concentration in Data Science?
The UNT Information Science Ph.D. program with a concentration in Data Science responds to the varied and changing needs of an information age, increasing recognition of the central role of information and information technologies in individual, social, economic, and cultural affairs.
The mission of UNT's Information Science (IS) Ph.D. program is to provide a center of excellence in graduate education and research. Its primary goals are to:
- Nurture critical and reflective thinking on the fundamental issues and elements of problems of utilization of information
- Foster an environment of substantive and productive mentoring and apprenticeship
- Prepare scholars passionate about the role of information in human affairs
- Foster cross-disciplinary thinking and research
Students are recruited to the program from a wide range of disciplines and encouraged to expand and refocus their expertise and skills in cutting-edge areas of information science that cross disciplinary boundaries. The multifaceted nature of information science warrants the focusing of resources, courses, and faculties from a broad range of academic units.
Marketable Skills
- Research and publication
- Pedagogical practices
- Critical thinking
- Leadership ability
- Data analysis
Information and Data Science Ph.D. Highlights
Special lectures hosted by the college and the department feature renowned scholars
who provide different perspectives and insights into the information science field.
Our students and faculty are active members of different professional associations
and learned societies, such as the iSchools consortium, the American Library Association,
the Association for Information Science and Technology, and the Knowledge & Information
Professional Association.
The structure of the IS Ph.D. program deliberately encourages and supports interactions
among students and faculty in different academic units. Faculty and doctoral students
together pursue research in a variety of areas.
The Department of Information Science offers financial support and scholarships to
its students to recognize exceptional academic and creative accomplishment.
The Career Center is one of the many valuable resources available to you at UNT. The
Career Center can provide advice about internships, future employment opportunities
and getting hands-on experience in your major.
Instruction is offered in a variety of formats, including face-to-face, online and
blended, that allows you to balance classes with full-time or part-time employment.
What Can You Do With an Information Science Ph.D. With a Concentration in Data Science?
Graduates of the program are prepared to contribute to the advancement and evolution of the information society in a variety of roles and settings as administrators, researchers, and educators.Information and Data Science Ph.D. Courses You Could Take
Seminar in Research and Research Methodology (3 hrs)
This course will cover advanced topics in research methodology, research proposal
development and directed research study.
Introduction to Big Data and Data Science (3 hrs)
This course provides an introduction to Big Data and Data Science including an overview
of the field, technical challenges, computational approaches, practical applications,
structured and unstructured data processing, empirical methods in computer science,
data analytics and learning, data visualization, privacy and ethics. Emphasis on Big
Data and its effect on other topics within Data Science, its technical characteristics
and state-of-the-art Big Data analytics architectures and tools.
Foundational Principles in Knowledge Management (3 hrs)
This course includes the data, information, knowledge, intelligence continuum, forms
and sources of knowledge, challenges and best practices to preserve it in organizations.
Covers the knowledge market, including players, dynamics and pathologies, and theories
and principles of knowledge management.
Data Visualization for Analytics (3 hrs)
This course teaches students to create insightful displays from complex, large and
possibly unstructured quantitative and qualitative data. Data visualization for analytics
goes beyond traditional static graphs and charts by seamlessly connecting data analysis,
data-based optimization and data presentation to create visualizations.
Usability and User Experience Metrics (3 hrs)
Focuses on the usability of web-based information systems and the significance of
user experience (UX) in the lifecycle of information system development. Students
learn a set of key techniques (heuristic evaluation, persona development, card-sorting,
and usability testing) for formative and summative usability evaluation of web-based
applications on computer interfaces, tablets and smartphones.
Seminar in Communication and Use of Information (3 hrs)
This course covers the nature of information as a phenomenon and of the communication
processes. Conceptual linkage to treatments in various fields. The role of information
and communication in individual, social and institutional behavior.
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