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Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning

NSF

closed
OpenLast verified: 2026-06-19

About This Grant

This project uses machine learning to create a database of State of the State (SOTS) addresses from 1800 to 2016 and state-level agendas. The data collection involves collecting and cleaning the full set of speeches from governors over time. SOTS data are stored at publicly available data repositories and a website developed by the PIs. Methodologically, the project advances the study of unstructured data and the use of artificial intelligence and machine learning. The data support knowledge and scholarship related to public decision and provide a web resource for educators and journalists. This project extends the SOTS dataset that covers state-of-the-state addresses from 1800 to 2016. The PIs collect, process, and analyze SOTS speeches from years prior to 1960, using techniques developed to overcome poor quality documents implemented through software created by one of the PIs. The software applies machine learning to isolate, enhance, and extract text from hard-to-read documents, correcting document layout problems with a novel statistical approach before it runs optical character recognition (OCR). This results in a significantly higher level of accuracy than other current approaches. 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.

Grant Summary

Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning is a NSF grant providing up to $225K for university, nonprofit, small business. Applications are due 2027-08-31 (open). Check eligibility and apply with FindGrants.

Focus Areas

machine learning

Eligibility

universitynonprofitsmall business

How to Apply

Funding Range

Up to $225K

Deadline

2027-08-31

Complexity
Medium
  1. 1Confirm your organization is eligible for Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning from NSF, checking organization type, location, and any population or project requirements.
  2. 2Gather the required documents and information, including your organization details, project plan, and budget figures.
  3. 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
  4. 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NSF before the deadline.
This record is a past award, contract, or funder profile — useful for research, but not an open grant application. Check the original source for current opportunities from this funder.

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Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning: Frequently Asked Questions

Who is eligible for the Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning?

Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning is offered by NSF and is generally open to university, nonprofit, small business. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.

How much funding does the Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning provide?

Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning provides up to $225K per award from NSF. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.

When is the Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning deadline?

Applications for Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning are due 2027-08-31 (open). Because deadlines can change, verify the date with the funder, NSF, and give yourself enough time to prepare a complete, competitive application before the close date.

How do you apply for the Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning?

To apply for Collaborative Research: The State of the State: Archival, Unstructured Data and Machine Learning, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NSF.

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