A command-line tool that converts a single bibtex file to a tab-separated file (TSV) with two columns (author, paper). This can be used as the foundations for a NSF-compliant COA file.
Makes a nice tab-separated file with author, -paper title which can be easily edited to build a COA file. Removes duplicate authors (where names are perfectly duplicated) and sets up an initial skeleton that mostly saves you copying-and-pasting names from paper PDFs.
MANY things, including automatically getting author affiliations or anything like that. In general this is much easier to copy and paste (and just know).
To install current stable version from PyPI
pip install bib2coa
To install source clone this repository or download the zip file and unzip and run
pip install .
From within the source dir tree (where setup.py is).
To build a tab-separated file (TSV) from a bibtex file run
bib2coa <filename>
This creates an outputfile called coa_initial.tsv which has two tab-separated columns. Unique authors (col 1) and the paper they come from with the paper year.
To see stats on the conversion include --stats flag.
To output a file with a different name add the --output my_file.tsv (for example).
Below is the workflow we recommend for making an NSF-compliant COA file.
Use your reference manager (we recommend PaperPile) to select all the references you want to process and save them as a single bibtex file.
For PaperPile, this is achieved by selecting all the papers you want to collect together and copy all the citations as bibtex keys to your clipboard. Save these as a text file (can be any format, but, in principle should have the .bib extension. Let's say we call this file nsf.bib.
Run using command
bib2coa --stats <filename>
e.g. in our example this would be
bib2coa --stats nsf.bib
This generates the file coa_initial.tsv. This can be opened in Excel/Numbers, a tab delimiter used to define the colimns, and then you can edit this file to match the appropriate table in the NSF COA template