The capability to bring computer science and technology as well as large and complex data sets to bear on interdisciplinary and transdisciplinary science is emerging. It is therefore critically important to establish and enable transnational frameworks so that data-driven scientific knowledge can transcend disciplines and geographical borders, ultimately increasing the scientific underpinnings of policy and action. International collaboration within global environmental change research fields holds the potential to establish international foundations for federated data integration and analysis systems with shared services, bring together best practices from the public and private sectors, foster open data and open science stewardship among the science communities including related areas such as publishing, and encourage data and cloud providers and others to adopt common standards and practices for the benefit of all.
This award supports U.S. researchers participating in a project competitively selected by a coalition of 29 funding agencies from 23 countries through the Belmont Forum Call for proposals on Science-driven e-Infrastructure Innovation (SEI) for the Enhancement of Transnational, Interdisciplinary and Transdisciplinary Data Use in Environmental Change. SEI is a multilateral initiative designed to support research projects that bring together environmental, social and economic scientists with data scientists, computational scientists, and e-infrastructure and cyber-infrastructure developers and providers to solve one or more of the methodological, technological and/or procedural challenges currently facing inter-disciplinary and transdisciplinary environmental change research that involves working with large, diverse and multi-source transnational data. The SEI call will intimately link research thinking and technological innovation toward accelerating the full-path of discovery-driven data use and open science and enable a broader scientific community to benefit from the identified new and potentially disruptive demonstrators or pilots toward solutions.
The historical record indicates that abrupt and unexpected change is the norm, not the exception and that these changes have direct consequences for many species and civilizations. Long‐term records from natural and historical archives have been essential to identifying these tipping elements, because past abrupt changes have occurred rapidly but infrequently, making them impossible to observe with instrumental records. The key limitations to addressing and communicating this major challenge in sustainability research is data access and incompatibility. Inaccessible or 'dark' data, unstructured data, the lack of e-infrastructure to integrate multinational and multidisciplinary databases and datasets, are fundamental limit our understanding of abrupt change. This project, run by a diverse, international consortium of ecologists, climate scientists and informaticists will seek to build e-infrastructure that enables efficient cross-resource data access between trans-disciplinary and transnational data resources; and create an analysis package that allows users to detect, map and investigate abrupt change in Earth systems. The project will focus on determining the tipping elements in Earth's climate and ecosystems and to understand what drove rapid desertification in subtropical North Africa 6,000 years ago. In addition, the project will seek to model the FAIR data principles: 1) Findable: exposing dark data and developing tools for data discovery. 2) Accessible: transferring dark data to open-access platforms. 3) Interoperable: building cyberinfrastructure that enables cross-access. And 4) reusable: generating data synthesis products that identify essential metadata as a model for future data generators, while working with stakeholders to facilitate the development of community endorsed data standards.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|Effective start/end date
|7/1/19 → 6/30/23
- National Science Foundation: $97,540.00