https://github.com/bgyori/nsf_coa

Generate COA form co-authors for NSF proposals

https://github.com/bgyori/nsf_coa

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (7.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Generate COA form co-authors for NSF proposals

Basic Info
  • Host: GitHub
  • Owner: bgyori
  • License: bsd-2-clause
  • Language: Python
  • Default Branch: main
  • Size: 3.91 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Generate COA form for NSF proposals

Problem

NSF proposals require a collaborators and other affiliations (COA) form for each senior personnel. Table 4 of the COA form requires listing all co-authors and collaborators from the past 48 months. The general understanding is that every single author of a paper should be listed in the COA form without discretion. This is a tedious and error-prone task, especially for large collaborations.

Solution

This Python package implements an automated author extractor from PubMed entries. One or more PubMed IDs can be provided, and the package returns a table which can be saved as an xlsx file. The table has the same header as the official template and uses the same format and conventions.

Installation

The package can be installed locally as:

bash pip install .

Usage

The package can be used as:

bash python -m nsf_coa.coa 32365103 34664389 34860157 which dumps coa.xlsx in the current directory.

Web application

There is also a simple web application that can be used to generate the COA form. It can be run locally as:

bash python -m nsf_coa.app

Then go to http://localhost:5000 in a web browser and enter PMIDs into the text box.

Owner

  • Name: Benjamin M. Gyori
  • Login: bgyori
  • Kind: user
  • Location: Boston, MA, USA
  • Company: Harvard Medical School

Sysbio & AI researcher. Leading indralab.github.io. Working on knowledge assembly, human-machine collaboration, text mining, probabilistic modeling.

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