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Division of Biological Infrastructure


Center for Advancement and Synthesis of Open Environmental Data and Sciences


CONTACTS
Name Email Phone Room
Matthew  D. Kane mkane@nsf.gov (703) 292-7186   
Reed  S. Beaman rsbeaman@nsf.gov (703) 292-7163   
Tevfik  Kosar tkosar@nsf.gov (703) 292-8970   


PROGRAM GUIDELINES

Solicitation  21-549

Important Information for Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.


DUE DATES

Letter of Intent Deadline Date

    April 1, 2021

Preliminary Proposal Deadline Date

    April 29, 2021

Full Proposal Deadline Date

    September 15, 2021


SYNOPSIS

NSF seeks to establish a Center fueled by open and freely available biological and other environmental data to catalyze novel scientific questions in environmental biology through the use of data-intensive approaches, team science and research networks, and training in the accession, management, analysis, visualization, and synthesis of large data sets. The Center will provide vision for speeding discovery through the increased use of large, publicly accessible datasets to address biological research questions through collaborations with scientists in other related disciplines. The Center will be an exemplar in open science and team science, fostering development of generalizable cyberinfrastructure solutions and community-driven standards for software, data, and metadata that support open and team science, and role-modeling best practices. Open biological and other environmental data are produced by NSF investments in research and infrastructure such as the National Ecological Observatory Network (NEON), the Ocean Observatories Initiative (OOI), the Long-Term Ecological Research (LTER) network, National Center for Atmospheric Research (NCAR), Critical Zone Observatories (CZOs), Integrated Digitized Biocollections (iDigBio), and the Global Biodiversity Information Facility (GBIF), as well as by many other public and private initiatives in the U.S. and worldwide. These efforts afford opportunities for collaborative investigation into, and predictive understanding of life on Earth to a far greater degree than ever before. The Center will help develop the teams, concepts, resources, and expertise to enable inclusive, effective, and coordinated efforts to answer the broad scientific questions for which these open data were designed, as well as key questions that emerge at interfaces between biology, informatics, and a breadth of environmental sciences. It will engage scientists diverse in their demography, disciplinary expertise, and geography, and in the institutions that they represent in collaborative, cross-disciplinary, and synthetic studies. It is expected that this new Center will build on decades of experience from NSF's prior investments in other synthesis centers, while providing visionary leadership and advancement for data-intensive team science in a highly connected and increasingly virtual world. It will serve as an incubator for team-based, data-driven, and open research that includes cyberinfrastructure, tools, services, and application development and innovative and inclusive training programs. The Center is also expected to spur collaborative interactions among the facilities and initiatives that produce open biological and other environmental data, and cyberinfrastructure efforts that support the curation and use of those data, such as Biological and Chemical Oceanography Data Management Office (BCO-DMO), CyVerse, Environmental Data Initiative (EDI), DataOne, EarthCube, and Cyberinfrastructure (CI) Centers for Excellence, to address compelling research questions and to enable training and data product and tool development. The new Center will further enable data-driven discovery through immersive education and training experiences to provide the advanced skills needed to maximize the scientific potential of large volumes of available open data.


What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)

Map of Recent Awards Made Through This Program