Place-based Open Science Joint Session

The relationship between people, place, and data underpins some of the greatest challenges, and opportunities, of the 21st century. Relationships between human communities and their natural and built environments are increasingly mediated through digital data. These data feed models and algorithms, including applications of Machine Learning and Artificial Intelligence, that impact decision-making in a range of contexts and at nested scales of governance from the stewardship of smart cities and Indigenous lands to international agreements over global commons such as the High Seas, Antarctica, or the Earth’s atmosphere. Digital representations of complex systems (digital twins or avatars) are emerging as technology platforms that harness the predictive power of scientific understanding (e.g., the consequences of climate change), while raising vital ethical, legal and social issues, including who should control these capabilities and how.   

Place-based data have a unique quality in that they span the sciences and humanities with time and space (geolocation) acting as foundational metadata used to assign data to “place” (or nested “places”). Furthermore, all place-based data are tightly bound up with personal and social identity, as place is an inherently human construct - even wilderness being designated to some degree by policy-makers. While the issues for Research Data Management are thus as diverse as the diversity of people and places, they share common underlying themes and issues (scientific, ethical, legal, and social) and much can be learned from shared experience informing common standards, useful tools and best practices, which in turn enable comparisons among and between places enabling mutual learning networks to emerge to achieve common goals, such as those laid out in the UN 2030 Agenda for Sustainable Development and associated UN “Decades”.