Final Version
Last modified: August 15, 2024

MSU Institute for Cyber-Enabled Research 2024 Strategic Plan

Executive summary 

Michigan State University faces three key issues relating to research computing and research data: (1) The increasing complexity of cyberinfrastructure, which is driven by the growing breadth of researchers’ needs; (2) the broadening of participation in research computing, particularly in scholarly areas where there is not a strong pre-existing culture around these types of methods; (3) the increasing need for custom software both as a tool for research and as an artifact of the research process. In addition, the Institute for Cyber-Enabled Research (ICER) faces crucial challenges in promoting the success of its staff and minimizing the climate impact of MSU’s research computing efforts. This document describes these challenges in detail, explains ICER’s goals relating to them (some of which span multiple campus units, and thus will be pursued in the form of partnerships), lays out specific actions that will be pursued over the next 4 years in pursuit of these goals, and defines metrics for success that can be used to quantify our progress.

Where are we now?

The Institute for Cyber-Enabled Research (ICER; https://icer.msu.edu/) provides MSU scholars with advanced computational systems, tools, and user support to facilitate computational and data science research and related instructional activities. In addition to housing MSU’s High Performance Computing Center, ICER supports researchers and instructors through training, one-on-one consulting, and the development of hardware and software infrastructure solutions. ICER’s current initiatives include the expansion of support for scholarly disciplines that are not traditional users of research computing by lowering barriers to entry through both software and training solutions. As of May 2024, ICER has 2,757 active accounts, 1,288 of whom have used the system in the past five months. This includes 692 graduate students and 233 undergraduate students, most of whom are engaged in research with an MSU faculty member. In 2024 ICER has supported 13 undergraduate and graduate courses and NSF-supported Research Experience for Undergraduates programs by providing computing resources, disk space, user training, and consulting services, and is actively engaging with faculty to broaden its support of instructional activities and student groups such as the MSU Artificial Intelligence Club and Data Science Club.

What are MSU’s key challenges with regards to research computing and research data?

Michigan State University (and, by extension, the Institute for Cyber-Enabled Research) face several challenges relating to the rapid growth in demand for research computing across many fields, coupled by an increased complexity of needs for resources, training, and tools. This boils down to four key challenges: 

Challenge #1: Increasing complexity in cyberinfrastructure.

The breadth of user needs with regards to cyberinfrastructure has grown substantially, driven by data-intensive computing, artificial intelligence (AI)/machine learning, and researchers with complex workflows that include both cloud computing and high performance computing. This expansion of needs and solutions is likely to continue in the next decade with the rapid growth of generative AI technologies, the ability to produce more data, and greater varieties of data, becomes increasingly easier and widespread among scholarly disciplines. This presents three related challenges. First, the hardware required to address these needs is very expensive. Second, the increased scope of hardware and software translates directly to increased complexity in setup and administration, and thus needs more personnel. And, third, data-oriented work intersects heavily with the purviews of MSU IT Services and the Library, which requires thoughtful collaboration.

Challenge #2: Broadening participation in research computing.

Research computing - driven primarily by the increase in the amount of data and resulting adoption of quantitative methods (including generative AI) - has become a tool for cutting-edge scholarship in many disciplines that have not historically been consumers of these resources, and even in more computing-oriented disciplines a larger proportion of scholars and their students are incorporating computational methods into their work. Supporting scholars that are new to research computing is crucial, but the needs of practitioners in these disciplines are often quite different than those of traditional HPC users. As a consequence, the user support, training, and tools required to enable them is also different. This presents a challenge to ICER because it requires substantial staff time to support these users, which includes training, documentation, community engagement, and one-on-one support. A second challenge relates to courses: the regularly taught courses that might be available to train students in fundamental computing and data analysis methods are typically not targeted at students from disciplines that are not traditionally quantitative and faculty in those disciplines who have the appropriate expertise often have other demands on their instructional time, making it hard to sustainably provide education to the students who need it.

Challenge #3: Software as a research tool and artifact.

Many researchers need to develop custom software (or modifications to existing software) in order to enable their research goals, but do not have the in-house expertise to do so in a way that would result in a high-quality, usable tool that would increase their scholarly impact. This is compounded by the fact that an individual researcher’s needs tend to wax and wane on a fairly rapid timescale and it is difficult to get external long term support for a full-time software developer. As a consequence, researchers have pursued a variety of complex, short term, and typically insufficient solutions to this problem. Most of MSU’s Big 10 peers (and many research-intensive universities across the US) have “Research Software Engineering” groups that can meet these needs, which results in MSU researchers being less competitive for external funding compared to peers at those schools - particularly as funding agencies institute requirements that the software and datasets produced as a part of that research will be made publicly available (a requirement that will be ubiquitous across federal agencies by the end of 2025).

Challenge #4: Promoting the success of ICER staff.

ICER’s staff is composed of highly trained and experienced individuals who are dedicated to ICER’s mission of providing high-quality cyberinfrastructure and research computing user support to MSU’s scholars and partners. Simply put, the people that comprise ICER are its most valuable resource and the most important aspect of its success, and thus the nucleus of ICER’s value to its users and other stakeholders. It is crucial to ensure that ICER staff have the professional development and career advancement opportunities that they need to keep them at the forefront of research computing and user engagement.

Challenge #5: Minimizing the climate impacts of research computing at MSU.

Data centers consume a substantial amount of electricity to both power and cool the computers within them, both globally and at Michigan State University, and this has a significant climate impact. Hardware designed for artificial intelligence applications is particularly power-hungry, with proportionally more impact. Given current trends in computing hardware, it is crucial to consider the climate impacts of research computing and its impact on the global climate crisis. 

Where are we going?

Goal #1: Manage the increasing complexity in research cyberinfrastructure.

ICER will continue to provide MSU scholars access to sufficient amounts of high performance computing, broadly defined - this includes CPU- and GPU-based computing resources, the ability to do interactive data analysis on large datasets, AI Workflows, both high-speed and large-scale data storage, and high-speed data movement. In addition, we will continuously work to understand the MSU community’s evolving needs, and will thoughtfully renew and expand our computing and data storage infrastructure in response to those needs. For example, recent reviews indicated growing needs for long term storage of data as well as mechanisms for sharing the data with collaborators outside the University, and we are working with other units on campus to ensure these needs are supported within the MSU community and that they are properly connected and supported by HPC systems. Furthermore, when users have needs that we cannot effectively meet we will work with them to find and efficiently utilize the appropriate resources through other MSU units, federally-supported regional and national providers (e.g., the NSF ACCESS program, the Open Science Grid) or through commercial cloud providers. We will also work with the MSU Research Facilitation Network to ensure that cross-cutting cyberinfrastructure needs are being met.

Goal #2: Support the broadening of participation in research computing.

ICER will continue to provide support to long-standing users of high performance computing through training, one-on-one interaction, documentation, and extended collaborations, and will continue to expand our support to users coming from scholarly areas that are not traditional users of research computing at MSU (e.g., social sciences, humanities, medicine, etc.) as well as for the increasing proportion of users from more typical usage areas. With regards to new subject areas we will do this through direct engagement with members of these communities, through partnerships with relevant units representing those communities (e.g., the Digital Scholarship Lab and Digital Humanities Program) and through the MSU Research Facilitation Network, and by facilitating the development of faculty as both practitioners and instructors by building connections with departments that can promote their success (e.g., the Department of Computational Mathematics, Science, and Engineering). This plan includes adding support for interactive tools that can facilitate exploration of advanced AI workflows. This will include open source instances of Large Language Models (LLMs) running privately on our secure OnDemand systems, with enough computational resources to enable academics to explore these new technologies without risking unintentional sharing of secure data. In addition, we will work with MSU leadership (in particular, deans) and relevant interest groups on campus (e.g., Digital Humanities) to educate them relating to instructional challenges and potentially opportunities. 

Goal #3: Create mechanisms to support software as a research tool and artifact.

ICER will take a multi-pronged approach to support the creation and dissemination of the software needed for the success of MSU scholars. First, we will promote the creation of a community for MSU scholars who develop software as a component of their job, which will provide them with a peer group, a mechanism to learn new technical and professional skills, and opportunities to learn about career paths. Second, we will create an “Open Scholarship Fellowship”, analogous to the Cloud Computing Fellowship that is jointly supported by ICER and IT Services, which will train graduate students, postdocs, and faculty to create and disseminate high-quality open source software, datasets, and educational materials in a way that maximizes their scholarly impact. And, finally, we will advocate for funds to create a Research Software Development group that partners with MSU scholars to develop and maintain the custom software that is crucial to their success and, if these funds are granted, will build this group. We anticipate that, once instantiated, this group will be primarily funded by external grants.

Goal #4: Promote the success of ICER staff.

ICER will empower its staff to be autonomous, creative, and flexible in responding to both internal needs and the needs of MSU scholars and our partners. We will do this by aggressively promoting opportunities for ICER staff to learn new technical and professional skills, to engage with regional and national communities of practice and professional organizations as both participants and leaders, and to partner with MSU scholars on research, software, and cyberinfrastructure projects. The ultimate goal is to ensure that ICER staff are satisfied with their jobs and continue to find value in their work and its positive impact on MSU, its partners, and the broader community.

Goal #5: Make climate impact a factor in decision-making and resource allocation.

ICER staff will work to understand the resources used by research computing on campus, to educate its users and campus decision-makers about this issue, and to reduce the overall climate impact of MSU’s research computing and research data efforts. This means that we will make energy utilization a key consideration in the purchase of hardware and software, that we will work with individual users to make their software and workflows more efficient (and thus use less energy), and to communicate more broadly about both our climate impact and efforts to minimize it while still accomplishing the scholarly goals of the MSU community.

How do we get there, and when will we know we’ve arrived?

It is difficult to predict the trajectory of research computing beyond the next few years. The increasing ubiquity of generative artificial intelligence, the assimilation of artificial intelligence and machine learning techniques into new fields, the continued growth of experimentally- and observationally-derived research data (from, e.g., gene sequencers and drone imaging), and substantial uncertainties about the trajectory of computing platforms add to the challenges in making concrete long-term plans. That said, the challenges and goals articulated in the previous sections are independent of these issues. As such, we can confidently take actions in pursuit of these goals, as well as create metrics that allow us to assess our success. In the following text, we describe the specific actions and metrics that will help us to address the challenges described above. These actions will be pursued over the next 4 years, with an interim check-in after roughly two years to assess our progress.

Goal #1: Manage the increasing complexity in research cyberinfrastructure.

Actions:

1. Addressing Hardware Costs

a. Assessment of needs: Perform annual needs surveys for current and potential users that track hardware, software, and support needs and an annual assessment of ICER and MSU’s capabilities (both qualitative and quantitative) compared to peer institutions, with the goal of informing investments. A particular area of assessment will be data-oriented resources such as data storage facilities and high-speed networks.
b. Funding and Grants: Secure internal funding and external grants to cover the costs of necessary hardware for data-intensive computing, AI/ML, and complex workflows. A key goal in this regard is to ensure that MSU’s computational resources are sufficient to meet researcher needs and are competitive with peer institutions.
c. Cost-sharing Initiatives: Develop cost-sharing models where multiple units contribute to the purchase and maintenance of expensive hardware (as a part of, e.g., faculty startup and retention packages).
d. Strategic Partnerships: Form strategic partnerships with hardware vendors for discounts or donations of high-performance computing (HPC) and cloud computing resources.
e. Leveraging external federal computing resources: direct researchers to appropriate NSF ACCESS, NSF NAIRR, DOE, and other computing and data resources (using, e.g., the ACCESS Campus Champion program).

2. Managing Increased Complexity in Setup and Administration

a. Hiring Specialized Personnel: Recruit and train additional IT staff with expertise in HPC, cloud computing, Artificial Intelligence, and complex workflows to manage the increased scope of hardware and software.
b. Training and Professional Development: Provide ongoing training and professional development opportunities for current staff to keep up with the latest technologies and administrative best practices.
c. Streamlined Procedures: Develop and implement streamlined procedures and automation tools to simplify the setup and administration of complex systems.

3. Enhancing Collaboration with MSU IT Services and the Library

a. Joint Task Force: Establish a joint task force with MSU IT Services and the Library to collaboratively address data-oriented work and cyberinfrastructure needs.
b. Regular Communication: Schedule regular meetings and communication channels between ICER, MSU IT Services, and the Library to ensure alignment and promptly address issues. 

Metrics for Success:

1. Addressing Hardware Costs

a. Assessment of needs: Annual report of trends and needs in research computing and data.
b. Funding Secured: Amount of funding and grants obtained specifically for hardware acquisition.
c. Cost-sharing Contributions: Number and value of cost-sharing agreements established with different units.
d. Vendor Partnerships: Number and value of partnerships with hardware vendors, including discounts and donations received.
e. Leveraging external federal computing resources: Number of researchers who successfully utilize these resources for research and/or training.

2. Managing Increased Complexity in Setup and Administration

a. Personnel Hired: Number of specialized IT staff hired to manage HPC, cloud computing, and complex workflows.
b. Training Hours Completed: Total hours of training and professional development completed by IT staff.
c. Efficiency Improvements: Metrics on the efficiency of setup and administration, such as reduced setup times and decreased downtime.

3. Enhancing Collaboration with MSU IT Services and the Library

a. Task Forces Established: Number of joint task forces created and their meeting frequency.
b. Collaboration Effectiveness: Feedback from regular meetings and surveys assessing the effectiveness of collaboration efforts between ICER, MSU IT Services, and the Library.

Goal #2: Support the broadening of participation in research computing.

Actions:

1. Support Long-standing Users

a. Training Programs: Continue to develop and deliver regular training sessions tailored to the needs of long-standing users of research computing.
b. One-on-one Interaction: Offer personalized consultations to address specific research computing challenges faced by individual users.
c. Comprehensive Documentation: Maintain and update detailed documentation to support users in their research computing tasks. 
d. Extended Collaborations: Foster long term externally-funded collaborative projects with individuals and research groups (with or without an HPC component) to enhance their research outcomes.

2. Expand Support to Non-traditional Users of Research Computing

a. Direct Engagement: Conduct outreach activities to engage with non-traditional users in social sciences, humanities, medicine, and other areas.
b. AI Tools and workflows: Build and test generative AI tools in our OnDemand system designed specifically to give academics a secure way to explore these tools instead as an alternative to external cloud resources such as ChatGPT.
c. Partnerships with Relevant Units: Establish and strengthen partnerships with units such as the Digital Scholarship Lab and the Digital Humanities Program to support non-traditional users.
d. Advocacy: Advocate for the need for these types of skills with leadership at the department and dean level, in collaboration with partners.
e. Development of Faculty as Practitioners and Instructors: Collaborate with departments like Computational Mathematics, Science, and Engineering to develop faculty skills in research computing and teaching and to develop curricular materials for their courses.

3. Advocacy for computational instruction

a. Development of Partnerships: Collaborate with interested parties on campus to develop an advocacy plan relating to computational instruction and engage with appropriate leadership.

Metrics for Success:

1. Support Long-standing Users

a. Training Participation: Number of training sessions conducted and the number of participants attending each session.
b. User Satisfaction: Feedback from one-on-one interactions measured through surveys and user satisfaction scores.
c. Tool Usage: Number and variety of people using the newly developed AI tools.
d. Documentation Usage: Analytics on the usage of documentation resources (e.g., number views, user ratings, and user requests for new/updated documents).
e. Collaboration Outcomes: Number and impact of extended collaborative projects (e.g., publications, grants, and research outputs).

2. Expand Support to Non-traditional Users

a. Engagement Activities: Number of outreach activities conducted and the level of participation from non-traditional user groups.
b. Partnership Success: Effectiveness of partnerships measured by joint initiatives, projects, and events with units like the Digital Scholarship Lab and Digital Humanities Program.
c. Advocacy Success: Effectiveness of advocacy efforts measured by new hires and new courses and workshops taught.
d. Faculty Development: Number of faculty members trained and their subsequent involvement in research computing projects and instructional roles. 
e. Departmental Connections: Number of successful collaborations and projects initiated with departments that promote the success of faculty as practitioners and instructors.
f. Courses impacted: Number of courses with new modules/lessons emphasizing research computing and research data skills and practices.

3. Advocacy for computational instruction.

a. Partnerships and plans: Number of partnerships developed, development of an advocacy plan, and number of meetings with deans and departmental leadership to advocate for this change.

Goal #3: Create mechanisms to support software as a research tool and artifact.

Actions:

1. Promote the Creation of a Community for MSU Software Developers

a. Community Building Initiatives: Organize regular meetups, workshops, and conferences for MSU scholars who develop software.
b. Skill Development Programs: Offer training sessions and workshops focused on technical and professional skills relevant to academic software development, with an emphasis on open source software.
c. Career Pathway Guidance: Provide resources and sessions on different career paths available for software developers in academia and industry.

2. Create an Open Scholarship Fellowship

a. Fellowship Program Development: Design and implement the Open Scholarship Fellowship program.
b. Training Curriculum: Develop and deliver a curriculum that includes training on creating and disseminating open-source software, datasets, and educational materials.
c. Mentorship Opportunities: Establish mentorship connections between fellows and experienced software developers and researchers.

3. Create a Research Software Development Team

a. Advocacy: Create a business model and proposal to the Office of Research and Innovation to instantiate a Research Software Development group.
b. Team Formation: Recruit and hire skilled software developers to form the Research Software Development group.
c. Partnerships with Scholars: Develop formal processes for scholars to request and receive support from the Research Software Development group.
d. Project Management: Implement project management practices to ensure efficient development and maintenance of custom software for researchers.

Metrics for Success:

1. Promote the Creation of a Community for MSU Software Developers

a. Participation Rates: Number of scholars participating in community events and workshops.
b. Skill Improvement: Feedback and assessments indicating improvement in participants’ technical and professional skills.
c. Career Development: Tracking the career progression of community members and their satisfaction with career guidance received.

2. Create an Open Scholarship Fellowship  

a. Fellowship Enrollment: Number of graduate students, postdocs, and faculty enrolled in the fellowship program.
b. Training Outcomes: Completion rates of the training curriculum and participants’ self-reported gains in skills and knowledge.
c. Scholarly Impact: Number of open-source software, datasets, and educational materials produced by fellows and their subsequent use and citation in scholarly work.

3. Create a Research Software Development Team

a. Advocacy: Approval of the ORI proposal for this group.
b. Team Size and Expertise: Number of software developers hired and their areas of expertise.
c. Project Completion: Number of custom software projects completed in partnership with MSU scholars. Amount of external funding acquired for these projects.
d. User Satisfaction: Feedback from scholars on the quality and impact of the software developed, including measures of usability, functionality, and overall satisfaction.

Goal #4: Promote the success of ICER staff.

Actions:

1. Promote Learning Opportunities for ICER Staff

a. Professional Development Programs: Offer regular training sessions and workshops to help ICER staff acquire new technical and professional skills.
b. Educational Support: Provide financial support and time allowances for staff to pursue certifications, courses, and higher education opportunities.
c. Knowledge Sharing Sessions: Organize internal seminars and lunch-and-learn sessions where staff can share their expertise and learn from each other.

2. Encourage Engagement with Communities of Practice

a. Conference Participation: Support staff attendance at regional and national conferences and workshops.
b. Leadership Roles: Encourage and support staff to take on leadership roles in professional organizations and communities of practice.
c. Networking Opportunities: Facilitate connections and networking opportunities with peers in similar roles at other institutions.

3. Foster Partnerships with MSU Scholars

a. Collaborative Projects: Actively involve ICER staff in research, software, and cyberinfrastructure projects with MSU scholars.
b. Joint Grant Proposals: Encourage and support staff to collaborate with scholars on joint grant proposals.
c. Project Management Training: Provide training in project management to ensure effective collaboration and successful project outcomes.

Metrics for Success:

1. Promote Learning Opportunities for ICER Staff

a. Training Participation: Number of staff participating in professional development programs and training sessions.
b. Skill Advancement: Staff feedback on the relevance and impact of the skills acquired through training.
c. Certification and Education: Number of staff obtaining new certifications or completing educational programs.

2. Encourage Engagement with Communities of Practice

a. Conference Attendance: Number of conferences, workshops, and seminars attended by staff.
b. Leadership Roles Taken: Number of staff serving in leadership roles within professional organizations.
c. Networking Success: Staff feedback on the value and outcomes of networking opportunities, including new collaborations and ideas generated.

3. Foster Partnerships with MSU Scholars

a. Collaborative Projects Completed: Number and scope of collaborative projects between ICER staff and MSU scholars.
b. Grant Proposals Submitted: Number of joint grant proposals submitted and funded.
c. Project Outcomes: Success rate and impact of projects as measured by publications, software developed, and feedback from scholarly partners.

4. Overall Staff Satisfaction:

a. Job Satisfaction Surveys: Regular surveys to assess job satisfaction and engagement levels among ICER staff.
b. Retention Rates: Staff retention rates as an indicator of job satisfaction and organizational commitment.
c. Recognition and Awards: Number of internal and external recognitions or awards received by staff for their contributions. 

Goal #5: Make climate impact a factor in decision-making and resource allocation.

Actions:

1. Understand the climate impact of key aspects of MSU research computing efforts.

a. Hardware impacts: work with vendors, ICER staff, and MSU researchers to measure the climate impact of hardware being considered for purchase or retirement.
b. Software efficiency: work with ICER staff and MSU researchers to assess efficiency of software in terms of total power consumption.

2. Communicate with MSU community and ICER users about climate impacts of research computing.

a. Provide metrics to users about energy consumption and CO2 production.
b. Include discussion of climate impact and mitigation efforts in ICER’s annual report. 

3. Include climate impact in ICER decision-making.

a. Create usage policies to reduce unnecessary resource utilization (e.g., data storage and CPU/GPU utilization)
b. Make energy efficiency a key consideration for new hardware purchases and hardware retirement decisions.
c. Reduce unnecessary CPU and GPU utilization by increasing outreach, user assistance, and training for computational efficiency.
d. Increase number of users served per unit computing and storage capacity to reduce per-capita energy budgets.
e. Increase adoption of cloud computing-based solutions where appropriate if those solutions use renewable energy sources. 

Metrics for Success:

1. Understand the climate impact of all aspects of MSU research computing efforts

a. Hardware impacts:

i. Energy consumption per hardware unit: Measure the kilowatt-hours (kWh) used per server or hardware unit.
ii. CO2 emissions per hardware unit: Calculate the CO2 emissions in kilograms associated with the energy consumption of each hardware unit.
iii. Lifecycle energy cost: Measure total energy consumption (kWh) and associated CO2 emissions over the lifecycle of hardware (from purchase to retirement).

b. Software efficiency:

i. Energy consumption per software application: kWh used by specific software applications during typical operations.
ii. Software efficiency improvement: Percentage reduction in energy consumption after optimizing software or workflows.
iii. Power utilization effectiveness (PUE): Ratio of total amount of energy used by a computer data center to the energy delivered to computing equipment.

2. Communicate with MSU community and ICER users about climate impacts of research computing

a. Provide metrics to users about energy consumption and CO2 production:

i. User awareness level: Number of users receiving regular updates about their energy consumption and CO2 production.
ii. User engagement: Number of users actively participating in energy efficiency programs or training.

b. Include discussion of climate impact and mitigation efforts in ICER’s annual report:

i. Report distribution and readership: Number of copies distributed and readership metrics of the annual report.
ii. Community feedback: Number and quality of feedback responses from the MSU community regarding the report's content.

3. Include climate impact in ICER decision-making

a. Create usage policies to reduce unnecessary resource utilization:

i. Policy compliance rate: Percentage of users adhering to new usage policies.
ii. Resource utilization reduction: Reduction in unnecessary data storage and CPU/GPU utilization measured in percentage or absolute terms.

b. Make energy efficiency a primary consideration for all new hardware purchases and hardware retirement decisions:

i. Energy efficiency index: Average energy efficiency rating of newly purchased hardware compared to previous purchases.
ii. Retirement efficiency gains: Energy savings from retiring inefficient hardware and replacing it with more efficient options. 

c. Reduce unnecessary CPU and GPU utilization:

i. Utilization reduction: Percentage reduction in CPU and GPU utilization due to increased outreach, user assistance, and training.
ii. Training participation rate: Number of users participating in efficiency training programs.

d. Increase number of users served per unit computing and storage capacity:

i. User density: Number of users served per unit of computing and storage capacity.
ii. Energy per capita: Reduction in energy consumption per user.

e. Increase adoption of cloud computing-based solutions (if those solutions use renewable energy):

i. Cloud adoption rate: Percentage of computing tasks shifted to cloud-based solutions which use renewable energy.
ii. Renewable energy utilization: Percentage of cloud computing tasks powered by renewable energy sources.
iii. Energy savings from cloud transition: kWh saved by transitioning to cloud-based solutions.

How does this connect to the MSU Strategic Plan?

The MSU Strategic Plan and the Office of Research and Innovation Research Implementation of this plan each have an extensive set of objectives. ICER supports several of these objectives, as detailed below.

MSU Strategic Plan (goals are linked; detailed exposition omitted):

• Student Success, Objective 1: “Strengthen MSU’s ability to attract and meet the needs, goals and aspirations of dynamic undergraduate students from all backgrounds.” ICER Goal #2.
• Student Success, Objective 4: “Strengthen each student’s educational experience to eliminate opportunity gaps and support success through graduation and beyond.” ICER Goal #2.
• Staff and Faculty Success, Objective 1: “Create a workplace culture that advances DEI and supports all staff, faculty and postdoctoral research associates.” ICER Goal #4.
• Staff and Faculty Success, Objective 2: “Make MSU a workplace of choice — and a desirable place to stay — for discipline-leading, innovative, creative and diverse staff, faculty and postdoctoral research associates.” ICER Goals #1, 2, 3.
• Staff and Faculty Success, Objective 3: “Invest in leadership and career development opportunities for staff and faculty that contribute to a culture of care, respect and inclusion.” ICER Goal #4.
• Discovery, Creativity, and Innovation for Excellence and Global Impact, Objective 1: “Demonstrate excellence in science, scholarship and creative endeavors, both in pursuit of fundamental knowledge and research designed to improve the human condition and address problems of today and to prepare for the challenges of tomorrow.” ICER Goals #1, 2, 3.
• Sustainable Health, Objective 4: “Lead nationally in devising innovative educational pathways to careers in health, supplementing existing health and premedical majors and evolve curriculum to incorporate commitment to an inclusive and healthy society.” ICER Goal #2. 
• Stewardship and Sustainability, Objective 3: “Achieve climate neutrality by 2050 through technology innovation, fiscal stewardship and embedding sustainability into institutional culture.” ICER Goal #5.
• Stewardship and Sustainability, Objective 5: “Ensure faculty, staff, students and community members have access to MSU and its resources to address current and emerging issues that affect Michigan and the world.” ICER Goal #1, 2, 3.
• Diversity, Equity & Inclusion, Objective 3: “Recruit, retain and expand career development for staff from diverse backgrounds.” ICER Goal #4. 

ORI Research Implementation (some details added for clarity):

• Objective #1: “Demonstrate excellence in science, scholarship and creative endeavors, both in pursuit of fundamental knowledge and research designed to improve the human condition and address problems of today and to prepare for the challenges of tomorrow.” ICER Goals #1-4 will support MSU researchers and scholars by providing infrastructure, training, partnerships, and software that will allow them to more effectively pursue their goals.
• Objective #2: “Invest in research to advance partnerships that increase economic development and opportunity in our region and beyond and that helps understand, shape and improve the future of work and the workforce.” ICER Goal #2 will promote computational expertise in a broad swath of MSU students, staff, and faculty, which will ultimately help them be high-impact, effective members of the 21st century workforce. 
• Objective #3: “Develop and implement new strategies to recruit and retain highly talented and more diverse student and faculty researchers and scholars across all disciplines.” ICER Goals #1, 2, and 3 will broadly promote recruitment and retention of researchers and scholars by making MSU an appealing place to pursue their research and scholarly work and by enabling them to be productive and competitive in those endeavors.