Universities, research institutions, governments, and companies have taken significant steps to upgrade their use of data science to boost research and innovation in recent months. Some of these new projects aim to use data science to provide insights into possible causes of and solutions to the COVID-19 pandemic. Take a closer look at the value of big data and AI for uncovering critical insights.

Organizations collaborate on AI projects

Since the Coronavirus spread throughout Europe and the United States in March, many sectors have slowed down, and new projects have been suspended or halted altogether. But the opposite has happened in the field of academic data science. Universities are finding partners among companies, independent research organisations, and government institutions to expand the scope of data science projects, including:

• A five-year collaboration on data science and innovation between Imperial College London and technology firm Huawei. The university says the partnership aims to “enable cutting edge discoveries for the benefit of society”. Huawei has committed $6.1 Million for the technology hub.
• A partnership between Oxford University and Amazon Web Services (AWS) on research projects designed to accelerate the pace of technology innovation within the fields of artificial intelligence, robotics and data science.
• A partnership between leading Dutch universities, research institutions and information analytics business Elsevier (a sister company to Nexis® Solutions) to create new publishing, reading and open science services. Kumsal Bayazit, CEO of Elsevier, said it would advance science and health outcomes “through more open, reproducible and collaborative scholarly communication and knowledge systems.”

What does COVID-19 mean for academic data science?

Academic data science is seen by many as a possible solution to the challenges raised by the Coronavirus. Big data and AI technologies can be used to identify patterns in huge datasets from patients with COVID-19 and compare them to previous pandemics. A number of other recent projects reflect this potential:

• Elsevier has made available all of its research and data content relating to COVID-19 on the US archive PubMed Central. This allows researchers to use AI to identify trends which could help researchers and countries deal with the pandemic.
• The US National Security Commission on AI has called for Congress to double research and development spending on AI in 2021 and double it again in 2022. Eric Schmidt, chairman of the Commission, said COVID-19 only increases the need for this funding because “virtually all of the interesting medical approaches that I’m familiar with” use AI techniques.
• The US Department of Health and Human Services and the Centers for Disease Control and Prevention are using data analytics techniques to synthesise vast sets of disparate health data to understand how the Coronavirus is spreading.

Even before the pandemic struck, surveys showed that rising numbers of consumers, employees and investors want to buy from, work for and invest in organisations with a social purpose. But COVID-19 has added an extra urgency to the ethical expectations which organisations face. Those who have failed to meet these expectations—for example through poor treatment of staff or inadequate provision of medical equipment—have suffered reputational and financial damage. Investment in academic data science is a clear way for organisations to contribute to the fight against COVID-19, and in doing so ensure their own long-term sustainability as an organisation.

How can my organization use data science?

With flexible APIs and an ever-expanding data universe, Nexis® Data as a Service (DaaS) connects universities to news, business, legal and patents data well-suited to academic research needs, so you can: 

• Accelerate time to insight. Use precision data mining that benefits from our customizable search logic and a data enrichment process designed to increase results relevance.
• Drive creativity and innovation. Harvest targeted news, business, and patents data to discover new topics, trends, or patterns.
• Design better research. Use dynamic search retrieval to deliver highly relevant data, filtered by topic, into your big data projects.
• Stay at the forefront of discovery and innovation. Fuel predictive analytics that uncover emerging trends, empower academic research and learning, and attract data science talent to your institution.

Nexis Steps:

1. Explore the datasets available through Nexis® Data as a Service.
2. Keep the conversation going by sharing this blog with your colleagues and connections.