Academic researchers are rapidly moving from publishing only articles to a broader package of scholarly outputs, including datasets, code, protocols, and workflows. A new system of open data is emerging that is findable, accessible, interoperable, and reusable (FAIR), holding the promise of accelerated scientific discovery. At the same time, open science presents opportunities for AI parsing and integration in the discovery and publishing processes. Researchers are navigating a new decentralized landscape of voluminous data, spread across repositories and platforms, with the promise of AI-driven science as a new scientific partner to navigate the overflow of information.

How should scientists, universities, libraries, and academic publishers navigate these new research ecosystems? Are there promising ways to integrate the diverse functions of publishers, data and code repositories, and preservation platforms? And what role will AI play in these processes? Join Swissnex and Frontiers for a discussion on the future of scientific publishing, including a demonstration of how one publisher is pushing the integration of data generation, compliance, peer review, and dissemination. Speakers from Harvard, Boston University, Suffolk University, and Frontiers will cover journal editing, research data management, research administration, science journalism, and AI-ready data — full lineup to be announced soon.