Cliff Lynch’s opening plenary at the Coalition of Networked Information (CNI) Fall ‘23 Member Meeting framed the meeting by diving into an overview of work being done in three broad areas: computational and networking infrastructure, artificial intelligence (AI) and machine learning (ML), and scholarly communication. Yet, it was the cross-cutting themes of openness and collaboration that really stood out as he provided examples of new and innovative work in these topical areas. These themes rose to the surface in presentation after presentation and were made explicit by funders during their panel discussions ‘The Federal Year of Open Science’ and ‘Update from Funders: Priorities and Trends.’
Ashley Sands, representing the Institute of Museum and Library Services (IMLS), stated that IMLS celebrated the Year of Open Science in part by funding the collaborative Association of Research Libraries/DCN project (phase two of the Realities of Academic Data Sharing [RADS] Initiative) on the economics of public access of research data investments. She emphasized a clear directive: when it comes to IMLS’s larger applied-research awards, they are looking to fund projects that will impact the field, impact patrons, or impact the average American, not just top researchers at well-funded institutions. Martin Halbert, representing the National Science Foundation (NSF), stated that the NSF is supporting research conducted in ways that seek to foster or advance open science principles, and referenced awards made under the Findable Accessible Interoperable Reusable Open Science Research Coordination Networks (FAIROS RCN) program. Brett Bobley, representing the National Endowment for the Humanities (NEH), highlighted the importance of the humanities in the age of AI, declining public trust, data privacy breaches, and civil liberties and civil rights conflicts. I could not agree more – the humanities are relevant and germane in tackling today’s problems where long-held values are in conflict or changing rapidly. The NEH has never been more important! Due to this, the NEH has shifted focus to prioritize awards that tackle issues such as these, and have initiated programs such as the Dangers and Opportunities of Technology: Perspectives from the Humanities program, the Collaborative Research program, both of which are under NEH’s Humanities Perspectives on Artificial Intelligence agency-wide initiative.
While the funder sessions reaffirmed the themes of openness and collaboration at a federal level, they emerged in the DCN-represented sessions as well. Jake Carlson, Joel Herndon, and Jon Petters presented results from a forthcoming RADS report in their session ‘Researcher and Institutional Impact of Data Management and Sharing Policies,’ which highlighted opportunities within institutions to align research data management and sharing services. Former DCN member Mara Blake, along with Emily H. Griffith, presented ‘Models for Sustainable and Inclusive Data Science Consulting and Collaboration in Higher Education‘, a project which focuses on the successful collaboration between North Carolina State University (NCSU) Libraries, the Data Science Academy, and the Department of Statistics at North Carolina State University. This model incorporates staff, faculty, and graduate students, and facilitates interdisciplinary data science consulting across all university colleges, demonstrating effective collaboration in higher education. And from Duke University, Tim McGeary, Rebecca Brouwer, and John Board presented work from Duke University’s IT Advisory Council, where they conducted a comprehensive assessment of research IT needs, and subsequently developed 12 recommended implementations focused on supporting researchers, enhancing computational services, and balancing security with flexibility.
While there is not enough space in a short blog post to showcase all the remarkable work featured at CNI, Gary Price’s curated list of AI tools that provide source information serves as a noteworthy final highlight. In the rapidly evolving information environment shaped by AI, navigating it collectively through collaborative efforts is key – sharing information openly about the tools we are using, as well as the benefits and drawbacks of each, is essential. As we learn more about how AI tools will improve our workflows and expand institutional capacity, we must recognize that these tools require human-in-the-loop interventions for responsible and ethical application.