Data-Science-MS-degree-proposal

The major will provide graduate students with advanced education and training in the rapidly emerging fields of data analytics and discovery informatics, which integrates mathematics and

New Academic Programs - Submission Template

Review Guidelines Prior to Submitting Materialshttp://www.mass.edu/forinstitutions/academic/documents/expeditednprogramapprovalguidelines.pdf

Information requested may be typed directly onto form rows Boxes will expand

Submit one hard copy and one copy on CD

Submit complete application between August 15 – April 15

Proposed Degree Title: Master of Science in Data Science

Proposed CIP Code:

Date of Trustee Board Vote:

Date Letter of Intent (attach copy) submitted to Chancellor: (must be 30 days prior to application submission)

Chief Academic Officer (CAO) Name and Title: Mohammad Karim, Provost and Executive Vice

Chancellor for Academic and Student Affairs.

CAO Phone Number: 508-999-8024

CAO Email: mkarim@umassd.edu

Has the Chief Academic Officer reviewed this petition? Yes

A Alignment with Institution Mission Priorities.

How does the proposed program align with the institution’s mission priorities?

This proposal is to establish a new interdisciplinary Master of Science degree program in Data

Science (DSC) The major will provide graduate students with advanced education and training in

the rapidly emerging fields of data analytics and discovery informatics, which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (e.g., science, engineering, business, sociology, healthcare, planning) Emphasis is

placed on merging strong foundations in information theory, mathematics and computer science with current methodologies and tools to enable data-driven discovery, problem solving, and decision

making

The proposed major will embody the mission of UMass Dartmouth through education, research,

economic development, and public service

1 It will prepare students of diverse backgrounds for success in technologically-oriented careers in the knowledge-based economy

2 It will increase innovation and scientific advancement through research

3 It will provide a pathway for women and men from diverse fields to rapidly transition to informationscience career paths

4 It will prepare a citizenry capable of bringing insight to complex information in an ethical and

socially responsible way

5 It will support the needs of the business community in Massachusetts and the nation

6 It will sustain the university's reputation for innovative academic programs and overall excellence

in graduate and professional education

Interdisciplinary graduate programs are an important component of the UMD long-range plan This program creates such a program directly aligned with industry needs in the rapidly evolving age of

'big data'

B Alignment with System Priorities

1 Will this proposed program address a regional/local/state workforce shortage? Explain

Research and industrial scientists are generating enormous amounts of data that need management, interpretation, and visualization Data centers with terabytes of scientific, consumer, health, and

social/sensor network data are being established nationally and internationally Researchers are

inventing new ways to discover knowledge, teachers are developing new ways to help students learn, and communications experts are exploring new ways to explain complex information to the public

The era of 'big data' has arrived and all of the science and engineering disciplines and

business/information organizations are exploiting these new opportunities Recent articles from the scientific and business community attest to the significance of this transformation, e.g., S Lohr, The Age of Big Data, New York Times, February 11, 2012 and The Economist, Data, Data Everywhere,

February 27, 2010 The U.S government has launched a major initiative to advance 'big data' to

address national priorities, i.e., Whitehouse Press Release, March 29, 2012 and Massachusetts just announced a Big Data Initiative that joins industry, academia, and government to accelerate growth and innovation in this new domain of information technologies

Data science is recognized by economists and financial analysts as one of the leading opportunities for developing the innovation economy in coming decades See, for example, Big Data, Big Impact: New Possibilities for International Development, World Economic Forum (2012) and Analytics: The New Path to Value, MIT Sloan Management Review, (2010) A 2011 report of the McKinsey Global Institute projects a talent gap of 140,000 - 190,000 in this emerging field (see figure below) The

Department of Labor also projects significant growth (>20%) in this field over the next ten years

McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition and Productivity (May 2011)Information technology is also identified as a major component of economic development in

Massachusetts by the Executive Office of Labor and Workforce Development, the MA Technology

Collaborative and the Economic Development Planning Council A recent study by the Mass

Technology Leadership Council, Big Data and Analytics: A Major Market Opportunity for

Massachusetts (2012) reports the following job growth potential in the big data sector

Another study by the University of Massachusetts Donahue Institute, The IT Industry: Hub of the

Massachusetts Technology Economy (November 2009), states that "every 100 IT jobs support an

additional 163 jobs in the broader Massachusetts economy."

The worlds of science and business are changing drastically and rapidly Both now depend upon the ability to analyze and learn from huge amounts of collected and streaming data There is most

definitely a shortage of people who can work with these data, especially those who have a solid

grounding in science Our graduates will be in the position to work with scientists and engineers as well as organizations, educators, and the public who can benefit from having the data made

accessible but don’t have the time or capability to work with the original data themselves Graduates

of the program will be prepared to participate on teams developing applications across a wide

spectrum of scientific, engineering and business domains

The proposed Data Science degree will be a ground-breaking program that specifically challenges

students to be leaders in the next stage of the revolution in data analytics, information management, and knowledge engineering In the short-term, the educational opportunities offered by this new

degree (and its related activities) will help graduates gain advanced knowledge; hence, improved

productivity and enhanced competitiveness for local economies In the long-term, the educational

varieties and its related applications well help enterprises in the South Coast (and by extension, the Commonwealth of Massachusetts) to more effectively retain their existing IT infrastructures and

promote expansion As the only university in the region to offer this degree, student interest and

employer demand for graduates is expected to be significant

2 With what other institutions have articulation agreements been arranged for this program? (attach agreements)

Not applicable

3 How will the proposed new academic program broaden participation and completion at the

institution by underrepresented and underserved groups?

The South Coast of Massachusetts is educationally underserved Only 19% of South Coast residents have a bachelor’s degree or higher which is about half the state average More than 24% of our

residents lack even a high school diploma [1] We are the only university in the South Coast region that can provide access and opportunity to these students STEM education is at the core of what it will take to thrive in the digital economy The proposed major in a STEM discipline is central to a

recently announced UMass System initiative (ABLE 4 STEM) to double the number of

underrepresented minority students graduating with degrees in these fields

This new degree provides STEM students with a new pathway to a career in IT We will work actively

to attract underrepresented students into the program by the following methods: (1) build awareness

of the career benefits this degree offers to diverse populations, (2) reach out to minority businesses, (3) increase accessibility through online course offerings, and (4) enhance the learning environment toinclude best practices to improve retention of diverse student populations

C Overview of Proposed Program

1 Context Describe the program’s development, as well as its proposed administrative and

operational organizational structure

This program was conceived by faculty in the Department of Mathematics to provide new educationalopportunities for students in the rapidly emerging field of 'Big Data' The Dean of the College of

Engineering began working with faculty to design innovative, interdisciplinary undergraduate and

graduate degree programs Ultimately, committees were formed to represent the different academicsunits that would participate in the program The committees worked together to create a flexible,

interdisciplinary curriculum giving students unique qualifications to lead successful careers in the

field

Since Data Science is a trans-college program, an alternate administrative organization is needed to oversee curriculum design, student recruitment/progress, quality assurance, and program

assessment At the outset, the program’s implementation and assessment will be guided and

managed by both the Mathematics and the Computer Science Departments through a steering

committee with faculty representatives from both departments and other participating academic units (departments/colleges) This committee will administer the program through such procedures as

developing and maintaining specific admission and operational procedures, preparing advertising

materials, evaluation applications, and making admission decisions The representatives from each department are expected to rotate over time

Administrative oversight for the program will be provided jointly by the Dean of Engineering and the Dean of Arts and Sciences A Program Steering Committee (PSC) responsible for program academicadmissions/advising/ standards/curriculum/assessment will be comprised of two faculty

representatives from each of the participating departments – appointed by the department

chairperson and approved by the Dean(s) The PSC will nominate one faculty member to serve as under/graduate program director (GPD), to be approved by the Provost/Dean(s) This structure,

similar to the administrative structure of some existing programs (e.g., Women's/Gender Studies;

Sustainability Studies), is very effective since the vast majority of the courses are taken in other

programs The structure is cost-effective and reduces the startup costs for the program At first theremight be two faculty solely associated with the Data Science program (the director and a tenure-trackfaculty member) The number might increase in time as the program grows An advisory committee

of industry representatives in related areas is also planned Any course proposals/changes will followthe standard committee approval process

2 Description What is the intent /purpose of the program? What knowledge and skills will students

acquire? For what careers will graduates be prepared?

Establishment of the proposed MS degree program would directly address the above shortfall in

human talent and be advantageous to UMass Dartmouth, the Commonwealth of Massachusetts, and

to the South Coast region UMD has the resources in place to support this innovative,

interdisciplinary degree, including faculty, library facilities, computer labs, networking, and general

technology support

This program is designed for professionals and organizational leaders who want to take on greater ITresponsibilities and for people who want to transition into a career that uses computer information

science to support decision making The purpose of the program is to prepare students for

employment in professional fields that require data analysis and representation, and a flexible, broad understanding of informatics It is intended to appeal to students who want to learn technological andanalysis tools used by leading science, engineering, business, academic, government and social

organizations Further, this new program is expected to accommodate individuals with career or

undergraduate degree backgrounds in business, engineering, computer science, physical/life/social sciences, mathematics, liberal arts and education who desire to enhance their data analytics and

information science skills and credentials

The program is designed to provide students with advanced skills and practice in applied computer science, mathematics, statistics, and a relevant substantive field of study with databases of

exceedingly large size, so that students can learn statistical modeling and computer-based

operations to index, store, extract, analyze, display and interpret from those computerized databases.The growth in size of databases and the need to be able to “analyze and mine” them is one of the

chief challenges for knowledge development and discovery in the 21st century

Program Goals

The new major is intended to be an innovative offering that will attract new students to UMass

Dartmouth Programmatic goals are to:

1 Meet the growing regional and national demand for high-level information systems/science skills;

2 Provide a path for individuals from diverse fields to rapidly transition to data science career paths;

3 Enable established information technology and computing professionals to upgrade their

technical management and development skills;

4 Prepare graduates to apply data science techniques for knowledge discovery and dissemination

to assist researchers or decision makers in achieving organizational objectives;

5 Establish stronger ties to alumni to enhance opportunities for continued learning and leadership;

6 Create innovators, entrepreneurs, business professionals who will lead the development of next generation information systems

Data Science is an interdisciplinary area that draws upon the traditionally distinct areas of computer science, applied mathematics and statistics, and applications from natural and social sciences,

engineering, and business Graduates from the MS program in Data Science will acquire the skills necessary to manage and analyze massive data sets A Body of Knowledge for the subject is

presented below:

 Statistics

o Exploratory data analysis

o Stratified sampling

o Regression, linear models

o Goodness of fit of statistical models

o Analysis of variance

o Design of experiments

o Digital signal processing

 Machine learning (quantitative analysis)

 General programming ability

o Python and pandas

o Web programming: HTML 5, CSS, php, javascript

Graduates from the proposed MS program will be highly marketable and have many employment

opportunities in both the public and private sectors As the only institution in the region to offer this innovative degree, UMass Dartmouth is well positioned to enjoy significant student demand and in sodoing to prepare students for challenging and exciting careers Regional employers that would be

interested in recruiting graduates of the proposed MS program in Data Science include NUWC,

Raytheon, General Dynamics, Lockheed Martin Sippican, Oracle, EMC, MathWorks, Meditech,

Microsoft Research New England and many others Other employers include: Google, IBM, SAS,

HP, Twitter, Facebook, Intuit, Splunk, big data startup companies, e.g., Cloudera, Locu, Essess,

Coursera, Guavus, BIScience, Quantivo, and Massachusetts notables Hadapt, Paradigm4, VoltDB,

Bluefin Labs, Kyruus, and INEX Advisors and government centers/laboratories, e.g., LLNL, NASA,

NOAA, NIST, Census, and NIH

Graduates of the Data Science MS program will also be very well prepared for advanced study in

information science or data analytics Students can pursue the PhD degree in Engineering and

Applied Science if they desire to teach at the college or university level or carry out academic or

industrial research It is also possible for students who obtain the MS in Data Science degree to

teach in secondary schools (with the proper teacher certification) or in community colleges

3 Curriculum, Requirements Provide a complete description of the curriculum Attachcurriculum outline (see page 5) and course syllabi Describe procedures and arrangements for independent

work, internship or clinical placement arrangements, if applicable Describe role and membership of external advisory committee, if any

A successful data scientist must be proficient in quantitative analysis and data processing to aid

discovery and decision support General attributes include: technical skills, communication/

teamwork skills, and an understanding of the scientific, business, or organization context of

data-driven inquiry, decision making, and problem solving Thus, the Data Science program offers a broadarray of learning and discovery opportunities aimed at drawing insights from extremely large amounts

of data, including: data collection, preparation and integration, statistical methods and modeling, and other sophisticated techniques for analyzing and displaying complex data Data Science is an

integrated curriculum with a unique blend of statistics, applied mathematics, computer science and application domains designed to meet the specific needs of both students and employers

Requirements for the MS degree in Data Science include completion of 30 credit hours of

coursework and passing a comprehensive examination 24 credits must be earned at UMD; 24

credits must be earned at the 500-level or above 9 credits may be earned at UMD before formal

admission The minimum GPA in all coursework applicable to the degree is 3.00 out of 4.00

Entering students may hold a Bachelor's degree from a wide array of disciplines, but will be expected

to have a prerequisite background in calculus, programming, statistics, and information science

They then take a 6-credit foundation in discrete math, computing and data structures, 6-credit core in data science, 15-credits in a student-selected application area such as informatics or analytics, and 3credits of practical training The latter practicum provides a team-based learning experience that

gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources The program emphasizes a

strong foundation, domain depth, and interdisciplinary training to foster effective communication with end users Data Science courses will carry the designation DSC Curriculum details can be found

on page 18 and course syllabi are appended

At the outset there is no significant research component embedded in this proposed graduate

program However, because many of the affiliate faculty conduct research in related areas the

expected synergy between research and teaching will enhance the student educational experience Abundant internship opportunities in many business/industry sectors will be available for experiential learning The university Career Development Center and the COE COOP/Internship program can

assist with placement

Learning Outcomes

At the time of graduation, students will:

 be able apply contemporary techniques for managing, mining, and analyzing big data across multiple disciplines;

 be able to use computation and computational thinking to gain new knowledge and to solve real-world problems of high complexity;

 have the ability to communicate their ideas and findings persuasively in written, oral and

visual form and to work in a diverse team environment;

 apply advanced knowledge of computing and information systems applications to areas such

as networking, database, security and privacy, and Web technologies;

 be better prepared for career advancement in all areas of information science and technology;

 be committed to continuous learning about emerging and innovative methods, technologies, and new ideas, and be able to bring them to bear to help others; and,

 have an appreciation for the professional, societal and ethical considerations of data

collection and use

Learning/Outcomes Assessment

Student progress and performance will be monitored on a continuing basis by the Data Science

faculty Students in the MS program in Data Science must maintain a GPA of 3.00 or higher to

remain in good academic standing

An ongoing process of quality control and outcomes assessment will contain the following elements.1) End of Course Evaluations

Each course will have an end of course evaluation, which in addition to asking for feedback on the

course experience, will ask questions related to the learning goals of the program

2) Small Group Instructional Diagnosis

Each year, we will perform small group instructional diagnosis (SGID) in at least one of the core

courses This facilitated group feedback often gives more constructive information for the

improvement of student learning than course evaluations A rate of one or two SGID’s per year will not be too burdensome for the administrators and instructors of the program

3) Exit Interview and Survey

All graduates will be interviewed using a standard consistent format Students will also be asked to fill out a web-based graduate exit survey/evaluation of the program

4) Transcript Analysis

Especially for the first five years of the program, we will track the paths students took through the

program in order to assess the appropriateness and effectiveness of the course sequencing we have put in place and to make adjustments if necessary

5) Long-term Career Tracking

With the assistance of the Alumni Office, we will maintain a database of our graduates, keeping track

of their careers to the extent possible We will periodically survey them and their employers

especially about the program changes to keep the program effective and up to date

Data Science is a trans-college degree program administered by a director and faculty

representatives (PSC) from both the mathematics and computer science departments (initially) who will be responsible for curricular design/implementation, student recruitment/success, quality

assurance, and program assessment The above data will be reviewed annually by the PSC

Comparisons to performance criteria will provide a basis for recommended improvements An

external advisory board consisting of 10 – 15 professionals from industry/business/government/

academe (see Appendix G) will be convened to advise on recruitment, curriculum/program

development, practicum projects, internships, strategic planning, fundraising, and advances in the

field The Board will meet twice per year, probably once physically and once virtually

4 Students For first year and transfer students, outline requirements for admission and graduation,

expected time from admission to graduation, projected degree completion rates, and transferability ofprogram participants’ credits to other institutions

Admissions Criteria

A student who meets the University’s general eligibility requirements may apply to the MS program inData Sciences All students apply through the Office of Graduate Studies Students must be

admitted to the DSC graduate degree program by the MS - DSC steering committee Entering

students must have a earned a baccalaureate degree from an accredited college or university with a minimum GPA of 3.00 (on a 4.00 scale) and be proficient in mathematics and computing

Applications must also include a statement of purpose (including career goals), resume, GRE scores,TOFEL scores (for international students), and three letters of recommendation

Graduation requirements include completion of all required courses and earning 30 total credits

toward the degree and a minimum cumulative grade point average of 3.00 in course work taken in

the program of study In addition, the student must pass an exit comprehensive exam covering core competencies in data science

The requirements of the MS program in Data Science can be successfully completed in 3 or 4

full-time semesters of 9 hours each Part-full-time students should finish the degree within 4 - 5 years An 85% completion rate expected Plans to deliver many of the courses online should accelerate the

graduation rate

5 Feasibility Describe faculty, staffing, library and information technologies, facility (including lab

and equipment), fiscal and or other resources required to implement the proposed program

Distinguish between resources needed and on-hand Complete faculty form (page 8) Display

positions to be filled with qualifications Attach vitae for current faculty

This program represents an optimum use of existing resources to attract new students and to providecurrent students with new career opportunities The program does not duplicate any existing

programs at the University and the faculty and infrastructure necessary to support the proposed

program are already in place The proposed curriculum utilizes many existing courses and only a

few new courses that will be taught by UMD faculty An assessment of existing resources and the

desire to deliver courses online suggests that the degree program should initially be offered as a

coursework degree program with no requirements for a thesis

a) Faculty

The proposed program draws on existing faculty resources and classes at UMD through cooperation among multiple faculty members from diverse academic disciplines The proposed curriculum

creates only four (4) genuinely new courses (DSC510, DSC520, DSC530, DSC550) to be delivered

by one FTE faculty All other courses are existing courses in CAS, COE or CCB departments or

modifications of existing courses The number of faculty solely associated with the program will be relatively small as identified on the Faculty Form In AY2012-13 the mathematics department added two new faculty In AY2013-14 the computer and information science department added a faculty

member with expertise in informatics and crowdsourcing Searches are planned for two additional faculty with data science related expertise

Current faculty members have the necessary skills to offer the proposed master's program The

program is built around the strength of the faculty, both in terms of their teaching and research As the program grows, and we consider additional faculty positions, we will look for individuals that both complement and augment the current faculty If enrollment grows above the projected yearly

enrollment of 50 students per year, it may be necessary to add more course sections and faculty

b) Infrastructure

A multipurpose Data and Visual Analytics Laboratory is being developed to support instruction and

collaborative research in data science Approximately 600sf of floor space is needed to

accommodate work/collaboration stations for 12 students (with expansion up to 24) Resources are available to cover space renovations (~$100,000), furnishings, and computer hard/software

(~$50,000 est.) costs We also anticipate students will have opportunities to utilize facilities in the

Center for Scientific Computing and Visualization Research, which will include an interactive

visualization wall

c) Program support

Program support will consist of a stipend and/or release time for the director and for course

development The library will require an expenditure of $8,000 for new materials in order to

accommodate the Data Science major Relevant journals include: Journal of Data Science, Data

Science Journal, Journal of Database Management, Computational Statistics and Data Analysis,

Computers and Graphics, ACM Transactions on Graphics, Data Mining and Knowledge Discovery, and Information Visualization

d) Operational support

Operating costs such as supplies, computers, telephones, photocopying, etc will be covered by

departmental budgets Additional expenses associated with seminars, student activities, recruitment,and publicity are estimated at about $50 per student and will be recovered through major fees The proposed curriculum is computationally intensive Additional IT technician/consulting support from departmental technicians or CITS will be allocated as needed to install/upgrade/maintain computer hardware and software Central support for program marketing and student services will be fulfilled

by the Office of Graduate Studies

6 Licensure and Accreditation Is this program intended to prepare students for licensure? If yes,

name licensure organization and licensing exam Project student passing rates What professional

or specialized accreditation will be pursued for the program? Project accreditation timelines

Not applicable

7 Program Effectiveness Goals, Objectives, and Assessment Linked to each goal should be

measurable objectives – such as job placement rates, faculty additions, facility or programmatic

enhancements, etc – timetable, and, if applicable, strategies for achieving them Attach goals table (see page 4) (Please note that this section is intended to focus on overall effectiveness, not student learning, which is addressed elsewhere.) Describe program assessment strategies that will be used

to ensure continuing quality, relevance and effectiveness Include plans for program review includingtimetable, use of assessment outcomes, etc

Benchmarks of Success

The success of the entire program will be assessed against the following benchmarks:

 Meeting enrollment targets (maintaining a minimum of 40 students, beginning in the third year);

 Graduation rates and degrees awarded (85% two-year graduation rate);

 Satisfaction of students with the program, measured by course evaluations and web-based exit surveys with graduating students (at least 85% satisfied or very satisfied);

 Success of graduates in pursuing advanced degrees, obtaining high-quality employment or

advancing to higher positions within their present organization; and,

 Long-term professional success of the graduates, measured by 5-year alumni and employer

surveys

Benchmarks will be evaluated annually by the PSC/DSC faculty and used to revise policies,

curriculum, and recruitment efforts accordingly Student placement and success will also be

monitored and presented annually to the External Advisory Board for review and feedback

After the program has been fully implemented for three years, a review of the overall program will be accomplished by reviewers external to the university The external reviewers will be drawn from

members of relevant businesses and from other graduate programs The review panel will be

chaired by the Associate Provost for Graduate Studies and will work closely with the External

Advisory Board The review will include an assessment of whether graduates and employers of

graduates have been satisfied with the program and whether the program is self supporting

Quantifiable as well as subjective benefits and costs of the program will be fully explored in the report

of the external review committee

D External Review

Attach the review team report and institutional response (obtain BHE approval of reviewers in advance; provide

review standards – see appendix - to team)

See Appendix E and F

E Market Analysis

1 Need for graduates What is the local/regional/state labor market outlook for graduates of the

proposed program? Include data and data sources that form the basis for need assessment

The demand for graduates of MS-level information/data science programs both in-state and

nationally is high and predicted to grow rapidly in the years ahead This degree program is designed

to produce professionals prepared to support the needs of information-intensive service

industries/businesses/agencies US Department of Labor employment projections in data science related fields are shown in the following table:

Occupation %Δ

Computer and information research scientists +19

Operations research analysts +15

Database administrators +31

Computer systems analysts +22

Market research analysts +41

systemsmanagers+18Ref Occupational Outlook Handbook 2012-13 ed , Bureau of Labor Statistics, 2012

A recent survey done by EMC also underscores the emerging talent gap for data scientists and the need for university programs to train the workforce

EMC Data Science Study, December 11, 2011

http://www.emc.com/collateral/about/news/emc-data-science-study-wp.pdf

It is imperative that if the required technical expertise is not grown locally (i.e., if our local industries are not provided with appropriately educated and skilled graduates), it will have to either be imported

or related jobs outsourced

2 Student Demand / Target Market What is the student market for the proposed program?

Discuss demographics, location, proposed market share, etc Provide data, e.g., survey results,

etc., that form the basis for enrollment projections (see page 4)

The proposed program is expected to draw a significant number of students beyond the 50+

currently enrolled in mathematics and computer science graduate studies The program is designed primarily for 3 types of students: 1) students and practitioners with an undergraduate degree in

Information Science, Computer Science, Applied Mathematics/Statistics, Engineering or the

equivalent; 2) students and practitioners with an undergraduate degree in a different field, e.g.,

science, business, economics, or social science, interested in switching into Data Science; and 3)

students in UMDs accelerated (4+1) Bachelor's-Master's Program Students entering the MS in

Data Science program without a CS/Applied Mathematics degree or equivalent knowledge in

computing technology will be asked to take additional course work before continuing on to graduate studies

The program will appeal to working professionals with technical degrees who want to be better

prepared for management opportunities in data-intensive companies/organizations Although the

program is fully justified as an on-campus graduate program, we think the proposed master's

program also presents a considerable opportunity to have a direct impact on the information

technology education needs of the state's current work force and businesses through distance

education

3 Duplication Identify existing public and private programs/institutions in the region or state that

offer the same or similar programs Discuss size / enrollment trends for these programs

At UMass Dartmouth the proposed interdisciplinary MS in Data Science bridges data analytics and information science with other existing degree programs In the UMass system there are no similar master's degree programs UMass Boston offers a Graduate Certificate in Database Technology Other programs in the state include an M.S in Computer Information Systems at Boston University and an M.S in Information Systems at Northeastern University which draws 230 full-/part-time

students However, those programs emphasize data management software systems instead of the big data analytics focus of this degree proposal A national survey of relevant programs is included

in Appendix B

4 Competitive advantage Apart from the obvious pricing advantage of public institutions, what will

distinguish the proposed program in the academic marketplace?

While the program being proposing is very innovative and has few direct analogues at other

academic institutions, the demand for programs in the general area of data science is expected to

grow rapidly The uniqueness and value of the DSC program lies in the interdisciplinary, integrated approach to big data industry needs The proposed MS program will provide graduates with the

knowledge and skills required to make important contributions to the development and use of data bases and information technology, and the tools for analysis and optimization of complex systems

used in the knowledge-based enterprises in the economy Data science is a new and unique field

fusing technology with knowledge from different disciplines to enable data-driven decision support

and discovery The program will maintain active engagement with IT firms through research,

consulting and course projects and internships Long-term plans are to increase access through

online course delivery

6 Marketing Plan Describe the institution's marketing plan, including time lines, for the proposed

program?

Marketing Strategy

A primary motivation of this degree proposal is to attract new students to UMass Dartmouth by

offering an innovative, contemporary educational opportunity tied to workforce needs These

students might fall in two broad (not necessarily disjoint) groups: students broadly interested in

science and technology careers not seeking specialization in a specific science and students

interested in business intelligence or data analytics As noted earlier the program will also appeal to working professionals who want to transition into a career that uses IT to support decision making or

to those already with technical degrees who want to be better prepared for management

opportunities in 'big data' companies/organizations Because the program is unique and serves a

rapidly developing field, we anticipate steady and increasing enrollment of such students

We will work with the Office of Graduate Studies and the External Advisory Board to devise a faceting marketing strategy for prospective students Once established, we will advertise widely the availability of the graduate program to Massachusetts businesses, state agencies, and other

multi-Massachusetts colleges and universities An attractive and informative website will also be

developed

We have established a collaborative relationship with the Indian Institute of Technology

Bhubaneswar, a brand new IIT whose students are among the most talented in the world Our

collaboration includes student internships as well as student and faculty exchange We also have aninternship host relationship with IIT Kharagpur, one of the oldest IIT campuses, and a recent MOU toestablish joint degrees with VIT in Vellore, India These programs will allow us to directly

communicate with and recruit some of their undergraduate and master’s students

F Budget Projection

a Budget Narrative Explain assumptions underlying expense and income projections, e.g.,

instructor status, enrollment projections, field and clinical resources, etc Describe additional

cost/revenue impacts within the broader departmental/institutional budget

Based on the expected demand for this unique degree program in a growing field, we are

confident in projecting an intake of 10 new students per year reaching an enrollment of 30 FTE

students in the program within three to four years when we expect the program to be completely

self supporting The number of faculty solely associated with the program will be kept small, one

or two, until the number of students justifies a larger faculty

New costs for the program are estimated by the institution to begin at $70,000 in year one andinclude program administration, supplies and materials, new course development, and onegraduate assistant This figure contains no costs for any of the other faculty members participating

in the program The program director will be given a course release, so coverage by a part-timelecturer is included ($4,000) An additional $70,000 is needed for laboratory development Thetotal estimate for new costs is $265,000 for the first four years of the program’s operationsalthough $94,000 of the total also supports the companion Bachelor's degree program

Enrollment /revenue projections are based on the following:

Year Projected

ment

enroll-CSF-FT/PT revenue @

$7,712/2571(FY13)

Major FT/PT revenue

fee-@ $690/230 (FY13)

Total Revenue

required for the addition of this program because plans to hire faculty into research clusters (e.g

computational mathematics/science/engineering), many of which will be supported by this

program, are already underway and will go forward whether or not this program is implemented

Future cluster hires could encompass economics, decision and information science,

industrial/financial engineering, computational social sciences, etc Faculty teaching graduate

courses affiliated with this program would be expected over time to migrate their course material toformats consistent with online delivery, if they have not already done so

The proposed 30-credit course-work degree program includes one course from each of the two

main participating departments plus an existing computational methods course and two new data science courses for a total of five mandatory courses to be taken by each student The remaining degree credits will be drawn from a list of approved electives from several disciplines Thus, the

only additional instructional need to launch the program amounts to 0.5 FTE faculty

b) Infrastructure

The university has already committed ~$150,000 for a Data and Visual Analytics Laboratory to

support instruction and collaborative research in data science Approximately 600sf of floor space

is needed to accommodate work/collaboration stations for 12 students (with expansion up to 24).However, we believe funding for computing and visualization equipment and software will beavailable through a number of federal granting agencies, corporations and foundations thatsupport innovative programs that wed technology and informatics Google, Microsoft, SAS, EMC,

MathWorks, Nvidia, Department of Education, National Science Foundation, James S McDonnellFoundation, and the Alfred P Sloan Foundation among others, have grant programs for thispurpose We will aggressively seek funding for equipment and programmatic support for the newprogram

Adequate computer laboratories already exist on campus, although students likely to enroll in thisprogram would usually have their own computers The campus network of virtual laboratorieswould provide remote access to instructional software Non-thesis students usually are notprovided with office space in university buildings beyond normal laboratory, library, and housingfacilities

c) Operational support

Operating costs such as supplies, computers, telephones, photocopying, etc will be covered bydepartmental budgets Additional expenses associated with seminars, student activities,recruitment, and publicity are estimated at about $100 per student and will be recovered throughmajor fees Additional IT technician/consulting support from departmental technicians or CITS will

be allocated as needed to install/upgrade/maintain computer hardware and software.Administrative support for the Graduate Program Director will derive from the base department.Central support for program marketing and student services (advising/tutoring) will be fulfilled bythe Office of Graduate Studies

Of course it may be argued that the economic stimulus for the state and the return in tax revenuesgenerated by new and existing businesses will return many times the state investment in thisinterdisciplinary Data Science graduate program Although these benefits are difficult to quantify,they are none the less real

b Program Budget Submit a line item income and expense budget for the proposed program for the first four years Budget categories include facilities, library, faculty, staff, field/clinical

experiences, revenues from grants, tuition or other sources, etc Reallocated funds should specifyreallocations from existing campus resources to support the proposed program, including funds

reallocated from discontinued or downsized programs Indicate one-time/start-up costs and

revenues

NEW ACADEMIC PROGRAM BUDGET - SAMPLE FORMAT

One Time/ Start

0 Part-Time/Adjunct Faculty (releasefor BS/MS program director)

(Salary & Fringe)

$4,000 $4,000 $4,000 $4,000

0 Instructional Materials, Library

Acquisitions (*includes companion 0 $8,000 $8,000 $8,000

UG program)

0 Facilities/Space/Equipment (also used in BS program) $25,000 $15,000 $15,000 $15,000

0 Tuition (1/4 of FT students on RA/TA fee waivers) 0 0 0 0

0 Fees (adding 5-10 self-supporting students per year) $42,010 $98,025 $154,040 $187,420

PROGRAM GOALS DESCRIPTION – SAMPLE FORMAT

academic program with outstanding faculty

groups

Diversity Focused recruitment

and support for women and minority students

employed in the

field or in graduate

school

opportunities aligned with industry needs

PROGRAM ENROLLMENT PROJECTION – SAMPLE FORMAT

# of Students Year 1 # of Students Year 2 # of Students Year 3 # of Students Year 4*

Graduate Program Curriculum Outline

(Insert additional rows as necessary.)

Major Required (Core) Courses (Total # of courses required = 5)

SubTotal # Core Credits Required 15

Elective Course Choices (Total courses required = 5) (attach list of choices if needed)

SubTotal # Elective Credits Required 15

Faculty Form Summary of Faculty Who Will Teach in Proposed Program Please list full-time faculty first, alphabetically by last name Add additional rows as necessary.

Name of faculty

member (Name, Degree

and Field, Title)

Check if Tenured Courses Taught Put (C) to indicate

core course Put (OL) next to any course currently taught online.

Number

of sections

Division of College of Employment

Full- or Part- time

in Program

Full- or part- time in other department or program (Please specify)

Sites where individual will teach program courses

nt (C)

 Research Methods (C)

(2)(3)(3)

part time full time in CIS main campus

part time full time in CIS main campus

part time full time in CIS main campus