Digital Curation and Management (GRAD)
The master of professional science (M.P.S) in digital curation and management is a 30-credit-hour, online or hybrid degree that focuses on digital curation. This comprehensive degree includes flexible electives and a set of core courses that prepare students to understand the complexities of data management and digital assert stewardship in relation to longevity, discoverability, and usability. All students will also get hands-on training with a remote or in-person digital curation internship.
Digital Curation and Management, M.P.S.
Course Requirements
| Code | Title | Hours |
|---|---|---|
| Core Courses | ||
| INLS 722 | Introduction to Metadata Architectures and Applications | 1.5 |
| INLS 750 | Introduction to Digital Curation | 3 |
| INLS 751 | Data Governance and Curation | 3 |
| INLS 765 | Information Technology Foundations for Managing Digital Collections | 1.5 |
| INLS 766 | Audit and Certification of Trustworthy Digital Repositories | 1.5 |
| INLS 767 | Information Assurance | 3 |
| INLS 800 | Seminar Series in Digital Curation | 1.5 |
| GRAD 712 | Leadership in the Workplace | 1.5 |
| GRAD 713 | Applied Project Management: Frameworks, Principles and Techniques | 1.5 |
| GRAD 714 | Introduction to Financial Accounting | 1.5 |
| GRAD 715 | Business Communication | 1.5 |
| Electives | ||
| Students must take 6 credits as electives from the pre-approved list below, or seek Director approval upon request. | 6 | |
| Thesis/Substitute or Dissertation | ||
| INLS 992 | Master's (Non-Thesis) | 3 |
| Minimum Hours | 30 | |
| Code | Title | Hours |
|---|---|---|
| Electives | ||
| INLS 556 | Introduction to Archives and Records Management | 3 |
| INLS 560 | Programming for Information Science | 3 |
| INLS 561 | Digital Forensics for Curation of Digital Collections | 3 |
| INLS 572 | Web Development I | 3 |
| INLS 712 | Introduction to Text Mining | 1.5 |
| INLS 714 | Introduction to Information Analytics | 1.5 |
| INLS 724 | Introduction to Electronic Records Management | 1.5 |
| INLS 726 | Big Data and NoSQL for Data Science | 1.5 |
| INLS 761 | Data Analysis | 1.5 |
| INLS 772 | Applied Statistics, Machine Learning, & Data Communication | 3 |
| INLS 773 | Database for Data Science | 1.5 |
| INLS 774 | Applied Data Ethics | 1.5 |
Milestones
The following list of milestones (non-course degree requirements) must be completed; view this list of standard milestone definitions for more information.
- Master's Committee
- Master's Written Exam/Approved Exam Substitute
- Thesis Substitute
- Residence Credit
- Master's Exit Survey
Recommended Checklist
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Approved to register for INLS 992 internship or paper
-
Comprehensive exam, written (oral only if failed written)
-
Master’s non-thesis substitution (internship or paper)
-
Applied to graduate
-
Grades met
-
Degree credit hour met
-
Exit Survey
Professors
Jaime Arguello
Jeffrey Bardzell, Dean
Robert Capra
Tressie McMillian Cottom
Melanie Feinberg
David Gotz
Sandra Hughes-Hassell
Mohammad Hossein Jarrahi
Diane Kelly, Wilson Distinguished Professor
Daniel Kreiss
Christopher (Cal) Lee
Gary Marchionini, Cary C. Boshamer Distinguished Professor
Lukasz Mazur
Marijel (Maggie) Melo
Arcot Rajasekar
Brian Sturm
Associate Professors
Bradley M. Hemminger
Ryan Shaw
Francesca Tripodi
Danny T.Y. Wu
Fei Yu
Assistant Professors
Alexandra Chassanoff
Antia Crescenzi
William (Willie) Payne
Yue (Ray) Wang
Joseph Winberry
Professors of the Practice
Ericka Patillo, Associate Dean for Academic Affairs
Matt Perault
Research Assistant Professor
Anita Crescenzi
Teaching Associate Professor
Ronald Bergquist
Teaching Assistant Professors
Michael Fox
Elliott Kuecker
Casey H. Rawson
Megan A. Winget
Digital Curation and Management
