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An exploration of federal (and some non-federal) grant programs and awards relating to Open Science and Open Science Infrastructure, using data from grants.gov, NIH, NSF, DOE. Implemented in python & jupyter notebooks.

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DanNBullock/USG_grants_crawl

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USG Grants Crawl

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Overview description

An exploration of federal (and some non-federal) grants targeting Open Science, using python & jupyter notebooks. Technically, no longer implemented as a crawl/scrape based usage of grants.gov APIs, and instead uses the XML Extract to download and work with the grant database locally.

Keywords

keywords: grants.gov, grants, open science

Installlation

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Project / Codebase overview

This repository contains a series of jupyter notebooks (stored under notebooks) which deail portions of the data anlysis process associated with our overarching endeavor (i.e. exploring US Government funding of Open Science-Related endeavors, via grants).

Chapter overviews

Broadly speaking, this collection of notebooks is intended to guide users through an increasingly complex analysis of data derived from grants.gov, as it relates to open science infrastructure.

For descriptions of the specific chapters, see the README file contained within the notebooks/ directory

Relevant modules

Within the src/ directory the grantsGov_utilities.py file contains a number of thouroughly documented functions that are used throughout the notebooks. Feel free to search through these, as later notbooks opt towards cleaner and more succinct code as opposed to rehashing code that has already been used.

Other relevant content

TBD

Project / codebase provenance

This project's main components are comprised of jupyter notebooks. A number of re-occuring functions (which would also take up substantial page-space, in addition to be repetitive) are stored in the src/ directory in the grantsGov_utilities.py file.

Support elements

Authors

Daniel Bullock, AAAS STPF Fellow

Contributors

Ann Stapleton, National Program Leader USDA

References

Lee, Jae Yun, and EunKyung Chung. "Mapping open science research using a keyword bibliographic coupling analysis network." (2022).

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An exploration of federal (and some non-federal) grant programs and awards relating to Open Science and Open Science Infrastructure, using data from grants.gov, NIH, NSF, DOE. Implemented in python & jupyter notebooks.

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