The COVID-19 Open Research Dataset (CORD-19) is a compilation of over 44,000 scholarly articles aimed at aiding the global research community in addressing the COVID-19 pandemic. It invites AI experts to develop text and data mining tools to answer high-priority scientific questions and leverage extensive literature for insights. The project emphasizes using data analysis tools like Tableau for visual storytelling and insight discovery within the dataset.

1. Academic Research Team Project Paper
COVID-19 Open Research Dataset Challenge (CORD-19)
An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The
White House
(1) FULL-LENGTH PROJECT
Dataset Description
In response to the COVID-19 pandemic, the White House and a
coalition of leading research groups have prepared the COVID-
19 Open Research Dataset (CORD-19). CORD-19 is a resource
of over 44,000 scholarly articles, including over 29,000 with
full text, about COVID-19, SARS-CoV-2, and related corona
viruses. This freely available dataset is provided to the global
research community to apply recent advances in natural
language processing and other AI techniques to generate new
insights in support of the ongoing fight against this infectious
disease. There is a growing urgency for these approaches
because of the rapid acceleration in new coronavirus literature,
making it difficult for the medical research community to keep
up.
Call to Action
We are issuing a call to action to the world's artificial
intelligence experts to develop text and data mining tools that
can help the medical community develop answers to high
priority scientific questions. The CORD-19 dataset represents
the most extensive machine-readable coronavirus literature
collection available for data mining to date. This allows the
worldwide AI research community the opportunity to apply text
and data mining approaches to find answers to questions within,

2. and connect insights across, this content in support of the
ongoing COVID-19 response efforts worldwide. There is a
growing urgency for these approaches because of the rapid
increase in coronavirus literature, making it difficult for the
medical community to keep up.
A list of our initial key questions can be found under the
Tasks
section of this dataset. These key scientific questions are drawn
from the NASEM’s SCIED (National Academies of Sciences,
Engineering, and Medicine’s Standing Committee on Emerging
Infectious Diseases and 21st Century Health Threats)
research topics
and the World Health Organization’s
R&D Blueprint
for COVID-19.
Many of these questions are suitable for text mining, and we
encourage researchers to develop text mining tools to provide
insights on these questions.
In this project, you will follow your own interests to create a
portfolio worthy single-frame viz or multi-frame data story that
will be shared in your presentation. You will use all the skills
taught in this course to complete this project step-by-step, with
guidance from your instructors along the way. You will first
create a project proposal to identify your goals for the project,
including the question you wish to answer or explore with data.
You will then find data that will provide the information you
are seeking. You will then import that data into Tableau and
prepare it for analysis. Next, you will create a dashboard that
will allow you to explore the data in-depth and identify
meaningful insights. You will then give structure to your data
story by writing the story arc in narrative form. Finally, you
will consult your design checklist to craft the final viz or data
story in Tableau. This is your opportunity to show the world

3. what you’re capable of - so think big, and have confidence in
your skills!
Kaggle Website:
https://www.kaggle.com/allen-institute-for-ai/CORD-19-
research-challenge
Assignment Length (word count):
at least 15 pages.
References:
At least
10
peer-reviewed, scholarly journal references.