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25 Aug 2020 | |
Written by Data Foundation | |
Blogs |
By Rose Lee, Research Fellow, Data Foundation
One notable aspect of the COVID-19 pandemic has been the volume of data and the speed at which it is available about the disease, its spread, and its consequences. The response to COVID-19 using data around the globe suggests that, if societies want to combat future pandemics effectively, it is necessary, to employ new approaches to data governance. This will mean using evidence (data) to lead behavioral change.
With questions raised about the reliability and quality of some health data around the world, including a range of countries like the United States, the United Kingdom, China, and Russia, now is the time to seriously rethink data governance strategies and approaches, and to do so with great vigilance.
Aspects of responding to the current pandemic are “data-driven.” The response touches almost every stage of data governance, from data collection to the final data presentation. Open data released by governments, non-profit organizations, and businesses are helping researchers provide analysis to the public and decision-makers more quickly.
Here are three key observations that will likely have longer-term impacts on data governance around the globe:
1. Data Transparency Affects Citizens’ Trust Toward Government Accountability.
Data transparency is a fundamental principle towards building public trust, but it has been difficult to deploy in real-time during this pandemic. Data transparency affects how data are prepared, which metrics are used, what methodologies are applied to create the final data publication, and more. The value of transparency is that data users have increased insights about all aspects of data creation, management, and analysis. This helps reduce the likelihood that data can be politicized, therefore, building and protecting trust among citizens in data and decision-making alike. In contrast, efforts that are even perceived as “fudging the data” to adhere to a particular narrative greatly undermine public trust that will be difficult to recover.
Countries and governments around the globe have been criticized for manipulating there data during the pandemic. Questions about statistics from the Chinese government contemplate the reliability of the information based on questioned methods and practices, alleged history of manipulating data, shifting case definitions, and evolving guidance on how to understand China’s coronavirus numbers. The United States has also seen controversy in this regard, including in Florida where a data scientist was fired after raising concerns that the state was misrepresenting its data. In Georgia, the Department of Public Health published a chart that manipulated time to present a positive trend in caseloads (for which the state later apologized).
Regardless of whether the errors are intentional or inadvertent, the increased attention to controversy as the demand for more real-time data grows suggests new challenges for data governance in calibrating to principles that protect public trust. Regardless, practices of “dressing up the data” should be avoided at all costs in a post-coronavirus world. In the era of the COVID pandemic, the last thing that governments want to do is to lose trust due to the misrepresentation of data or lack of transparency.
2. Data Literacy Must be Prioritized for Individuals and Organizations.
The pandemic has highlighted an incredible gap in data literacy across the country and government. Individuals need to understand data with enough familiarity to make sound judgments regarding management and fitness for use. This can likely only be achieved with intentional, focused data literacy training efforts in organizations.
Despite federal government guidance for the re-opening from the Centers for Disease Control, states generally used different data and metrics to decide when to open their economies. In such an environment, each individual, household, and company inevitably review which data they can trust then apply that information to their respective risk tolerance levels. Data literacy is the key tool in developing a population that can make appropriate, objective decisions about which data are of high enough quality to make evidence-based decisions.
Governments should share the burden together by “ensuring potential data users have access to information about what data means” and by clearly communicating data limits. Standardized data provide a common language for researchers across political jurisdictions, and it enables fast delivery of meaning information out of raw data. After the pandemic, both for individuals and organizations, the ability to discern the quality of data will be a vital skill in this era of data oversaturation. Chief data officers, non-profit organizations, and academic institutions all have a role in supporting improvements in data literacy.
3. More Innovative Data Sources Need to be Evaluated and Used
The COVID-19 pandemic continues to highlight a trade-off between “fast” data and “good” data. Finding innovative data sources (e.g., existing administrative data or business data) can help provide insights into what is happening on the ground. For example, we can understand the escape patterns and top destinations of New Yorkers during the pandemic using mail-forwarding requests data across the country – even without collecting new data. Nontraditional websites offer another venue to obtain relevant data. Yelp’s data science team published an analysis on how the pandemic affected local businesses around the country. With this kind of data, data users could observe that consumers moved fast, often ahead of their governments’ stay-home-order.
Recognizing gaps in the data collection of the federal statistical system, the U.S. Census Bureau launched two new, large-scale surveys called the Household Pulse Survey and Business Pulse Survey. Unlike the regular data series published monthly, quarterly, yearly or decennially, these surveys are designed to provide near real-time data to inform public responses to unprecedented pandemic situations on a weekly basis. But more innovation is needed inside government and in the private sector to continue to develop, advance, and apply insights from the range of potential approaches. Chief data officers and data governance leaders must create the mechanisms for rapid evaluation and adoption of these types of approaches.
Post-coronavirus world? It hasn’t passed yet.
COVID-19 forced us to social distance, but it brought policymakers, businesses, and household members much closer to data. Our society must continue to make data governance more accessible, integrated, and innovative. That’s why transparency, data literacy, and innovation will be the key moving forward.
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