Analysis of AI research to tackle COVID-19

This code contains scripts and notebooks to:

1. Reproduce the analysis presented in Nesta's report about AI and the fight against COVID-19 (AI-C19)
2. Update data collections (this requires access to Nesta's data production system)
3. Reproduce future analyses based on updated data collections

Instructions

Setup

1. Create a conda virtual environment with the packages we use in our analysis:

conda env create -f conda_environment.yaml

2. Install scripts as a package:

pip install -e .

3. If you have access to Nesta DAPS and are planning to collect data from there, install the data_getters package:

pip install -r nesta_packages.txt

You may need to pip install tornado --upgrade after.

Collect data

You can collect the processed data we used in the AI-C19 report from figshare by running:

python ai_covid_19/fetch_dataset.py

The downloaded files also include data dictionaries.

You can make a new dataset with (probably updated data) by running:

python ai_covid_19/make_rxiv_data.py

python ai_covid_19/make_citation_data.py

And train a new hierarchical topic model by running

python ai_covid_19/train_topsbm.py

Note: This requires putting your credentials in a .env file that will be read by the relevant scripts

Analysis

Each notebooks in the notebooks/ai-c19 folder refers to a section in the report.

You can re-run them individually. All visual outputs will be saved as html files in report/figures/nesta_report_figures.

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Project based on the Nesta cookiecutter data science project template.