MS in Information Science

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The information and data sciences disciplines are expanding rapidly thanks to the pressing demand for new innovations in information retrieval, storage, processing and analysis tools and techniques. The Master of Science in Information Science (MSIS) degree is a 33 credit hour program which is designed to give individuals advanced knowledge and skills in the concepts and technologies for working with large amounts of complex data. This degree can also be a stepping stone towards pursuing the PhD in Computer and Information Science, and the Graduate Certificate in Data Science can be earned as a subset of the MSIS requirements.

Student Learning Outcomes for the Master of Science in Information Science

  1. Graduates will be able to design database schemas, as well as create and maintain databases.
  2. Graduates will be able to process large data sets, including both manipulation and mining operations.
  3. Graduates will be able to explain and implement data manipulation processes that provide appropriate guarantees of privacy of personal data.
  4. Graduates will be able to use tools and techniques for visualization to summarize large data in ways that enhance comprehension and analysis.
  5. Graduates are proficient in written and oral communication.
  6. Graduates are able to maintain their technological currency through life-long learning in the field.

Program Delivery

The MS in Information Science can be completed in a traditional in-class setting on the Little Rock home campus, through the Online Campus, or with a mix of in-class and online course sections. Class lectures are webcast live on the internet as they are taught in class, and also recorded for students to view later. Most courses are scheduled one time per week starting at 6:00 pm Central Time (US) and lasting for 2 hours and 40 minutes, but some classes may be scheduled at other times. The fall semester runs from about August 21 through December 15 and the spring semester from about January 5 to May 15. The exact dates for each semester vary and can be found on the calendar on the UA Little Rock homepage.

To learn more about Distance Learning, please check out the following link: Distance Learning and Proctoring.

Course Requirements

  • Four core courses. These also constitute the Graduate Certificate in Data Science curriculum, so you can get that certificate along the way to your master’s degree.
    • IFSC 7320 Database Systems or CPSC 7351 Database Design: Database systems and data modeling, including entity-relationship model, relational data model, normalization, structured query language (SQL), transaction management, object-oriented databases, and basics of physical database design and query evaluation. This course is offered each Fall semester.
    • IFSC 7370 Data Science and Technologies: This course provides a survey of the skills and concepts needed for managing, processing, and analyzing massive amounts of data in real time. Topics covered include data sourcing, storing and sharing, integration, and data mining strategies along with hands-on experience working with sample technologies selected from a complex ecosystem of tools and platforms. This course is offered each Spring semester.
    • IFSC 5345 Information Visualization: The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. This course is offered each Fall and Spring semester.
    • IFSC 7360 Data Protection and Privacy: Concepts and methods for creating technologies and related policies with provable guarantees of privacy protection while allowing society to collect and share person-specific information for necessary and worthy purposes. Methods include those related to the identifiability of data, record linkage, data profiling, data fusion, data anonymity, de-identification, policy specification and enforcement and privacy-preserving data mining. This course is offered each Fall semester.
  • 5 courses at the graduate level (that is, with course numbers of 5000 or higher) with particular emphasis placed on Information Science, Business Information Systems, Computer Science, and Systems Engineering. Up to two INFQ (Information Quality) courses may be selected. Some possible strategies include:
    • A focus on data science & analytics
      • BINS 5351 Data Analysis and Reporting
      • BINS 7304 Business Applications for Decision Making
      • BINS 7309 Cloud-Based Business Intelligence
      • IFSC 5325 Data Mining
      • IFSC 5360 Social Computing
      • IFSC 7321 Information Science and Theory
      • STAT 7340 Advanced Statistical Methods I
      • STAT 7341 Advanced Statistical Methods II
    • A focus on database systems design, development, and management
      • CPSC 7352 Advanced Database Issues
      • IFSC 5330 Database Security
      • IFSC 7310 Information Systems Analysis
      • INFQ 7303 Principles of Information Quality
      • INFQ 7342 Information Quality Tools & Industry Landscape
      • INFQ 7367 Information Quality Policy and Strategy
    • A focus on emerging information technologies
      • BINS 7352 Emerging Technologies and Strategic Issues
      • CPSC 7373 Artificial Intelligence
      • IFSC 5399 Special Topics in Augmented and Virtual Reality
      • INFQ 7348 Entity Resolution and Information Quality
      • IFSC 5301 Information, Computing & the Future
  • Project or thesis. This must total at least 6 credit hours. Students normally divide this across two semesters, but students can vary their credit hours if they wish to spread the project across 3 semesters (ex. IFSC 7286 Graduate Program taken 3 times). Note: Other combinations are available.

Some additional tips on completing a MS Project/Thesis are available on Blackboard. Go to and search on Information Science to bring up the Information Science Graduate Student Resources course shell.  This course shell has an assortment of information on how to propose, develop, and defend your MS Thesis or Project.

Here are some more details on how to choose between a project and a thesis and what procedure to follow to succeed:

Master’s Project or Master’s Thesis

Q: How should I fulfill the thesis or project requirement?

The first steps are to identify a project or thesis topic and an advisor. You can choose any faculty member you like, or an external community member who is qualified to advise. For a topic, one option is for the advisor to suggest the topic. In fact, if a faculty member needs research work done in his or her lab, this can be a reason for the faculty member to agree to serve as your advisor. A second option is to define a topic yourself and then find a faculty member or qualified community member who is willing to serve as advisor for that topic. This can be something you simply want to do, or you can find possible topics by checking sites like, or other sites that provide data challenges or similar ideas. A third option is to ask the program coordinator for a list of suggestions for topics. We have had students who were able to use their MS Project as a bridge to finding employment. Consequently, give some thought as to what you would like to do career wise and select a project that will help you along the way.

The next steps are to decide on some details:

(A) If the topic will lead to some advance in human knowledge (for example, it might lead to a publishable paper), it would be most likely suitable as a thesis, and you would register for a thesis course. If it is a contribution to the needs of a client or a personal learning experience but not intended to advance the field of information science, it would most likely be suitable for a project, and you would register for a project course. Whether thesis or project, a total of six credit hours of work on it is required, typically spread over two consecutive semesters.

(B) Although the advisor is your primary intellectual resource, you also need two others to be on your advisory committee. The advisor can help suggest or recruit these others. Sometimes an advisor or committee member does not have formal permission from the university to serve, in which case they will need to apply for it. The coordinator can help with this.

The remaining steps involve completing the thesis or project:

First, a proposal describing what similar work has been done by others and what you plan to do yourself needs to be written. Your committee needs to approve the proposal and the coordinator will need the form indicating committee approval.

Second, you will need to do the work you proposed.

Third, there is the writeup. A thesis will need to conform in format to graduate school specifications so it can be made available to others. A project report will need to conform to typical guidelines widely available by, for example, a web search engine query like:

how to write a masters project report

Fourth, you will need to gain approval of your committee for the results of your work and the thesis or project report document. Start by sending your thesis or project report to the committee members. At around that time, communicate with them to schedule your defense, which is a meeting in which you present your work to them for their approval. Once it is scheduled (and a room reserved), email Dana Ball ( with your name, the name of the degree (which is MSIS), the title, the location, the date and time, your advisor’s name, and the abstract of your thesis.

It is best to work with your advisor to get that person’s suggestions and help as you prepare your presentation for your defense. After the defense, the committee will often request changes to the writeup and/or additional technical advances before they approve it. The program coordinator will need the form indicating their approval of the defense and the written document. The deadline is May 1 for Spring graduation, Dec. 1 for Fall graduation, and Aug. 1 for Summer graduation. If you are doing a thesis, that must be approved by the Graduate School and uploaded as they specify.

Finally, you must take the bureaucratic step of applying for graduation, so the university registrar will check to make sure you have met all requirements and put you on the graduation list. This is the step that causes you to get your degree!

Helpful references:

  • For the Graduate Catalog, which contains the official program requirements (strictly speaking, the requirements in the one corresponding to the academic year you were admitted or any more recent one may be chosen), please click here.
  • For the Dissertation and Thesis Guidelines Handbook, please click here.
  • For the Graduate Student Handbook, please click here.
  • For the MSIS Program Process Flow, please click here.


Early in the semester in which you plan to graduate, you must apply to graduate. This causes the university to add your name to the list of graduating students. You must also pass an oral defense, at which you present your results to your committee, and submit a report or thesis.

Admission Requirements

Anyone with a baccalaureate from an accredited school can apply for admission to the MS in Information Science program. Candidates who have an appropriate background in computing or who have relevant professional experience will be the most prepared to enter and successfully complete the program. Candidates who wish to enter computing as a new field are often interested and will be considered.

Requirements for Regular Admission

  • Baccalaureate degree from an accredited institution.
  • Cumulative grade point average of at least 3.0 on a 4.0 scale.
  • Completion of any remedial course work that may be specified by the department. Students seeking regular admission to the program will be best prepared if they have completed (with a grade of B or better in each course) course work or have professional experience equivalent to the following UA Little Rock courses:
    • IFSC 2300 Object-Oriented Technology
    • IFSC 3320 Database Concepts
    • STAT 2350 Intro to Statistical Methods

For more information, please visit the FAQ page, or contact Dr. Daniel Berleant at

To apply, please visit the UALR Graduate School portal.