Midwest Research Computing and Data Consortium
In this series, we dive into the world of the Midwest Research Computing and Data Consortium. We explore its members, their challenges, and prospects. Recently, we had the opportunity to speak with Corinne Adams, a Support Specialist from Advanced Research Computing (ARC) at the University of Michigan, who shared her insights on the field. Edited excerpts below:
My background started in math and philosophy, with a long-standing interest in programming and building computers from a young age. I found work in systems administration, networking support, and web development, accumulating over a decade of experience in various IT roles. This diverse background eventually led me to Advanced Research Computing (ARC) at the University of Michigan, where I now serve our research and student communities as a research computing support specialist.
Within my role at ARC, I support our users by giving guidance that helps them access and use our services, through directly addressing their questions and providing technical assistance, as well as contributing to ARC’s continuing development of support documentation and developing automation to meet regular support needs. I’m part of the team that handles front-line user support, evaluates requests, and delegates tasks to other technical and support teams. ARC consists of about 25 core members, but we also work very closely with local IT units from within the university that have significant research computing communities, altogether adding up to around 50 individuals who are primarily dedicated to supporting research computing. The work we at ARC do is often in direct support of (and with) these unit teams, and accomplishing this work helps to achieve the needs and goals of many researchers that the local teams are most often directly engaging with, and who use our services.
In the research computing field there will always be a mix of people who are unfamiliar with research computing and just starting to learn about how to leverage these technologies, and people who have been in this field for most of their career and are very familiar with it, particularly in specific areas of expertise. Exploring ways to coordinate bridges between those who are learning with those who have a particular kind of expertise that would be of the most benefit to meet a project or development need is, and will be, a constant activity for all of us in this field. Although providing and supporting research computing and data management infrastructure services is in a lot of ways a highly technical profession, openness to discussion and a willingness to contribute are critical.
With increasing academic and national awareness and attention on the incredible impacts that access to research computing services provide to the research and development community, as well as possible or likely beneficial contributions to many occupations across many workforces, we expect to continue to serve increasingly broad and diverse communities that will include more people of varying technical familiarities. This just isn’t a field where you encounter mostly people using these services and tools who already have a baseline of eight years or more technical experience, for sure, nor should it be limited in that way – the constant arrivals of people who are completely new to research computing, and may be coming from an entirely non-technical background, contribute new perspectives that really help bring balance, focus, and add spotlights to where a range of service and support improvements are possible and could make the most difference.
This is my third year with ARC, and during this time we’ve seen a significant spike in usage that’s in large part been driven due to the University of Michigan’s program that provides complementary annual allocations of Advanced Research Computing core services, making these services available to all our university researchers. This increase in demand has tripled our usage, but our staffing levels and hardware resources have remained at about the same as where they were four years ago, when this program was initially rolled out. We’re looking forward to continued expansion of our technical capabilities, and the challenge of rapid growth has re-emphasized the need for improving and maintaining our public documentation, streamlined communication, and utilizing automation wherever possible to manage workloads effectively.
A notable example of my work involves the creation and re-drafting of internal and public-facing service documentation. My regular interactions through providing technical support, paired with noting the patterns that emerge through observing and listening to the needs that our users and unit IT partners communicate to us, both inform the direction and priorities of my time and projects. Knowing what the challenges really are is the first step toward finding any solution. I have many colleagues who have in-depth knowledge and expertise in a variety of areas, and are generous with their time to help lift up the researchers, students, and colleagues they work with; so many solutions to challenges that I’ve helped to develop are overwhelmingly a result of team effort.
Looking ahead, AI tools and other machine learning models will play increasingly critical roles across various research disciplines. At ARC, we work towards growing access to cutting-edge hardware, software, and integrated research computing technologies. Our upcoming initiatives focus on providing additional tools and support within our integrated set of core research computing services that will help researchers and research groups develop short- and long-term strategies they can use to navigate the entire research data life cycle. This includes everything from increasing our service accessibility and ease-of-use for active research data, through simplified and graphical service interfaces and providing a service map for long-term data retention and sharing, by growing the tools we provide for researchers to use for managing their data, as well as maintaining compliance with recent university policies developed to align with NIH and NSF standards.
These regulations require proper data retention and sharing, which can be challenging for researchers to navigate on their own. There are many teams at the university who help researchers understand and meet these research data management requirements, ensuring their research data is managed correctly and securely. We want to refine our support model and computing research tools as effectively as we possibly can, so that these teams and researchers have as great of an ease-of-use experience as possible with the services we provide.
Our goal is to simplify data usage and management for researchers and students by making our services more accessible and user-friendly. By continually maintaining and finding ways to improve the information we make available, and centralizing highly-integrated research computing services, we aim to lower technical barriers for those who may find the technology intimidating, increase service accessibility through continuing our development of service platforms that are intuitive to use, and make sure we continue to broadly communicate that we welcome community engagement and feedback.
Outside of work, I enjoy spending time outdoors, going for walks, and reading. I always have several books on the go, which I pick up depending on my mood or the time of day. Finding a balance between work and personal life is crucial, and I am fortunate to have a supportive manager and director who encourage this balance. It takes mindfulness and intentionality to maintain this equilibrium, but it is essential for overall well-being and effectiveness in both personal and professional realms.