COVID-19 Open Research Dataset Challenge (CORD-19)
An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House
(1) FULL-LENGTH PROJECT
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, 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 what you’re capable of – so think big, and have confidence in your skills!
Assignment Length (word count): at least 15 pages.
References: At least 10 peer-reviewed, scholarly journal references.
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