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The FAIROS Program seeks to support a broad range of transformative open science activities including but not limited to i.) Research, education, and socio-technical cyberinfrastructure development capacities that advance sustainable multi-disciplinary findable, accessible, interoperable, reusable (FAIR) research data management (RDM) and open science capabilities, ii.) Piloting new models of scientific communication and publication that improve efficiency and accessibility, iii.) Developing FAIROS data portals, research data commons, RDM as a national service, and iv.) Lowering barriers to accessing, curating, integrating, linking, managing, sharing, and storing data across many disciplinary domains, irrespective of data size. The program supports innovation across the cyberinfrastructure (CI) ecosystem to address accessibility, data curation, research data management, discoverability, reliability, reproducibility, preservation, sustainability, and utility of research products, including data software, and code, developed as part of funded projects. FAIROS proposals must select one of two tracks to focus on, either: 1) Disciplinary Improvements to targeted scientific communities, or 2) Cross-Cutting Improvements that apply to many or most scientific disciplines. In the case of proposals focused on Disciplinary Improvements, it is strongly recommended that prospective PIs contact a program officer from the list of Cognizant Program Officers in the directorate closest to the major disciplinary impact of the proposed work to ascertain that the scientific focus and budget of the proposed work are appropriate for this solicitation. In the case of proposals focused on Cross-Cutting Improvements, it is strongly recommended that prospective PIs contact the cognizant program officer from the Office of Advanced Cyberinfrastructure (OAC). After selecting either Disciplinary Improvements or Cross-Cutting Improvements in which to focus research, the proposal must include the kinds of activities relevant to the selected track. Standard research proposals are the only type of proposal accepted in response to this solicitation. The FAIROS Program is undertaken in support of the US NSF Public Access Initiative. For more information on the US NSF Public Access Initiative please visit https://new.nsf.gov/public-access.
Funding Opportunity Number: 25-533. Assistance Listing: 47.041,47.049,47.050,47.070,47.074,47.075,47.076,47.078,47.079,47.083,47.084. Funding Instrument: G. Category: ST. Award Amount: $6M total program funding.
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Or search similar grants →According to the current listing, eligibility includes: Eligible applicants: Others (see text field entitled Additional Information on Eligibility for clarification). *Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities. -Other Federal Agencies and Federally Funded Research and Development Centers (FFRDCs): Prospective proposers from other Federal Agencies and FFRDCs, including NSF sponsored FFRDCs, must follow the guidance in PAPPG Chapter I.E.2 regarding limitations on eligibility. -Institutions of Higher Education (IHEs): Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of sub-awards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus. -Tribal Nations: An American Indian or Alaska Native tribe, band, nation, pueblo, village, or community that the Secretary of the Interior acknowledges as a federally recognized tribe pursuant to the Federally Recognized Indian Tribe List Act of 1994, 25 U.S.C. §§ 5130-5131. Confirm the full requirements in the official notice before applying.
The current listing shows $6M total program funding. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Findable Accessible Interoperable Reusable Open Science (FAIROS) are due April 14, 2027. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Yes — Findable Accessible Interoperable Reusable Open Science (FAIROS) is offered by U.S. National Science Foundation and this listing comes from Grants.gov, an official U.S. federal source. Federal applications generally require registrations (for example SAM.gov or an agency submission portal), so allow extra lead time.
This opportunity targets applicants in Alaska. If your organization operates elsewhere, check the official notice for location requirements.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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Data sharing to support the training and development of AI foundation models in the energy sector is sponsored by European Commission — Horizon Europe. Expected Outcome: Projects are expected to contribute to all the following expected outcomes: Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security. Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency. Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange. Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution. Scope: The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus areas of the energy sector. Projects are expected to: Building on the results of previously funded projects on the Common European energy data space [1] as well as the ongoing work within the Data 4 Energy expert group, projects are expected to demonstrate innovative methods and data governance strategies for sharing data among various energy actors. Projects are expected to demonstrate that they have access to large relevant datasets at the time of submitting the proposal. Projects are expected to develop innovative strategies for sharing data in an effective, secure and transparent way to support the development of AI foundation models. An indicative non exhaustive list of strategies that can be explored is the use of data space connectors or federated training of models to allow the integration of confidential data; the creation of synthetic data as an intermediate step to fill data gaps or improve the quality of the data could also be explored. Projects could also explore other innovative data sharing strategies, such as an ‘AI gym’. The data governance strategies that will be developed in the project should be designed in a way to be scalable and operational even after the end of the project. Projects are expected to develop foundation models tailored for the energy sector, addressing at least one -or more- of the following use cases: planning and operation of electricity grids (including static power flow modelling and dynamic EMT modelling), forecasting, congestion management, anomaly detection, fault diagnosis, predictive maintenance, flexibility management, demand-side energy efficiency, smart and bidirectional charging of EVs or other use cases that contribute to the objective of digitalisation of the energy system. Projects are expected to perform in-depth testing and validation of developed foundation models in lab demonstrators and real-life pilots, building on the results and using the facilities of previously funded projects on “AI testing and experimentation facilities (TEFs)” [2] . Regulatory sandboxes could also be considered for real-life pilot implementations. Projects are expected to bring together a wide group of stakeholders including data owners (for example energy utilities, grid operators, asset owners), application developers (for example startups, SMEs, hyperscalers) and model deployers (for example industry, grid operators, equipment manufacturers) providing a space of cooperation and collaborative data exchange. To scale up the training and development of the models, projects can benefit from the computing capacity of the AI factories that were recently announced by the European Commission [3] , in particular the three AI factories that aim to develop AI applications for the energy sector. AI models are expected to respect et Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Climate, Energy and Mobility, Energy Systems and Grids
Assessing direct and indirect drivers of biodiversity decline of invertebrates is sponsored by European Commission — Horizon Europe. Expected Outcome: Proposals are expected to contribute to all the following expected outcomes: stakeholders involved in biodiversity conservation and restoration activities have an improved understanding of how direct and indirect drivers [1] of biodiversity decline work, considering spatial and temporal scales and dynamics, and their interactions; the implementation at different spatial and temporal scales of the EU biodiversity policies and legislation, notably the Nature Restoration Regulation (NRR) is improved, enabling the prioritisation of actions and the identification of systemic solutions; stakeholders, including primary producers, whose business models rely on ecosystem services are better equipped to take strategic decisions that support biodiversity, thereby increasing opportunities while reducing their exposure to risks linked to the decline of these services. Scope: Biodiversity decline has rippling effects on climate, economy, and human well-being. Focusing on representative groups of invertebrates (including insects, molluscs and crustaceans and, in particular, understudied taxonomic groups) across representative European terrestrial, freshwater and marine ecosystems, is crucial for developing effective biodiversity conservation strategies since they are the foundation for healthy ecosystems and their decline has cascading impacts on ecosystem health and services. Understanding the relative impact of the aforementioned drivers at different spatial (from local to global) and temporal (from immediate to long-term) scales and dynamics, is needed to develop effective and coherent biodiversity protection and restoration strategies to implement the EU Nature Restoration Regulation [2] while building a resilient competitive economy. Proposals should: assess and rank the direct and indirect drivers of biodiversity decline based on invertebrates´ cases studies across representative European terrestrial, freshwater and marine ecosystems, considering their cumulative impacts, different spatial and temporal scales and dynamics, and their interactions; better understand the drivers of invertebrates decline and how they vary spatially and temporally, aiming to advance in the attribution of causality. This could involve the use of spatial analysis techniques, temporal trend analysis, and modelling approaches as well as other modern technological approaches to anticipate future changes; develop methods and recommendations to replicate this exercise in other spatial settings; involving relevant stakeholders, develop and provide decision-support tools to competent authorities and stakeholders for effective protection and restoration strategies, enabling them to prioritise and address the most critical drivers of invertebrates´ decline, with the aim of enhancing ecosystem resilience and services; building on relevant existing ecosystem modelling frameworks, include/add an anticipatory and predictive dimension, integrating early-warning systems and stress-testing approaches able to assess future trajectories under different land-uses scenarios; ensure that results feed into decision support tools [3] developed for primary producers to make informed choices that enhance the resilience and competitiveness of their business by restoring and protecting the ecosystems that provide the services they depend on; Proposal should focus on invertebrates´ species, in particular, understudied taxonomic groups, across representative European terrestrial, freshwater and marine ecosystems, addressing Area A : Focus on insects or Area B : Focus on molluscs and crustaceans. The area (A or B) should be clearly indicated on the application. Concrete efforts should be made to ensure that the data produced in the context of the funded projects is FAIR (Findable, Accessible, Interoperable and Re-usable), particularly in the context of real-time data feeds, exploring workflows that can provide “FAIR-by-design” data, i.e., data that is FAIR from its gener Programme areas: Global Challenges and European Industrial Competitiveness, Food, Bioeconomy Natural Resources, Agriculture and Environment, Biodiversity and Natural Resources, Horizon Europe (HORIZON) Keywords: Biodiversity characterisation, Biodiversity conservation, Causes and mechanisms of loss, Ecosystem services provided by catchment areas, Ecosystem services provided by soils, Environmental protection, Forest biodiversity, Forest ecosystem services, Fresh water biodiversity, Marine biodiversity, Soil biodiversity, Sustainable development and nature protection, Agriculture, Aquaculture, Biodiversity decline, Biodiversity loss, Conservation, Crustaceans, Direct driver, Drivers, Ecosystem services, Indirect driver, Insects, Invertebrate, Molluscs, Primary sector, Protection, Resilience, Restoration, decision support
NSF 27-500 replaces the MRI solicitation: no per-institution limit, no tracks, $50 million for about 60 awards, and a January 4–29, 2027 window. What changes for research offices.
Read articleOn October 28, 2026, NSF sent its revised Guidance on Financial Assistance to OMB after 3,277 public responses. The revision drops four provisions borrowed from OMB's unfinished 2 CFR 200 rewrite: no fixed-price awards, no publication costs, termination for convenience, and indirect costs subject to available funds. The final 30-day comment period runs through about November 27. Here is what changed, what didn't, and what research offices should do before the December 11 funding cliff.
Read articleNSF 26-022, the July 8, 2026 Dear Colleague Letter last updated October 27, says NSF will prohibit its funds from supporting research collaborations with entities on U.S. restricted-party lists in FY2027, on the same timeline as the Guidance on Financial Assistance. Authorized organizational representatives and senior/key personnel will certify compliance at proposal submission. Here is what is covered, what is still undefined, and a 60-day plan for research offices and PIs.
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