Data gaps curtail innovation, digital equity
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Insufficient or incomplete information limits governments' ability to leverage data-driven solutions and innovations, according to a recent report.
Inadequate data can lead to misinformed policy and program decisions, resulting in misappropriated funds or continued social and economic inequities. That means data-driven services meant to uplift disadvantaged populations could fall short, according to a May 8 report from the Center for Data Innovation.
Just as insufficient internet access fuels the digital divide, scant data may also limit governments’ ability to harness information to solve social and economic disparities and take advantage of emerging technologies. Artificial intelligence, for example, depends on complete, reliable data to streamline decision-making processes, Center officials said in announcing the report.
“Without substantial efforts to increase data representation and access, certain individuals and communities will be left behind in an increasingly data-driven world,” said Gillian Diebold, policy analyst at the Center for Data Innovation and co-author of the report.
Data access is also critical to resident engagement. Data portability, open data policies and easier access to application programming interfaces can help community members interact with data more and “participate in the data economy,” the report stated. For instance, an open data portal in Phoenix, Arizona, empowered residents to develop innovative solutions for easing parking and reducing urban heat. “Rather than design policies restricting data, policymakers should look for ways to expand its equitable collection and use,” the report said
Policymakers should consider ways to broaden the acceptance of data collection and sharing for social good, according to the report. Some policies restrict the amount or types of data organizations are allowed to gather, which may result in fewer valuable insights on underserved communities. To avoid such oversights, officials should consider how an increase in data collection can “go hand in hand” with data privacy legislation, the report stated.
The Center for Data Innovation also recommended that leaders invest in smart city infrastructure with data gathering capabilities. A network of sensors can automate data collection on traffic patterns or environmental conditions such as air quality, the report stated. These insights can help leaders make educated infrastructure or financial decisions to facilitate a healthier community.
Data sharing is another way governments can bridge data gaps. By partnering with other agencies, organizations or private companies, governments can better track developments in crucial areas affecting communities, including public health or climate change, the report stated.
Data interoperability can also elevate the usability of data by increasing accuracy, timeliness, precision and representation, according to the report. When federal, state and local government data is interoperable, data discrepancies resulting in incomplete or inconsistent datasets and formats can be avoided. In an instance where agencies are tracking the spread of an infectious disease, for example, data interoperability can help officials monitor a number of public health agencies to appropriately allocate vaccine resources to areas most in need.
Agencies should regularly maintain the data they collect and store. “Just as the government treats the maintenance of infrastructure as an ongoing process that requires routine upkeep to ensure quality and safety, agency data collectors should continually monitor datasets to ensure they are updated, cleaned and secured,” the report stated. It’s also important agencies flag known limitations and errors in their datasets, which can further help users to identify data gaps as well as solutions to data inadequacies.
“A data-rich society comes with a wealth of benefits—from improved public health to better education,” Diebold said. “To ensure that all Americans receive these benefits, policymakers should commit to closing the data divide.”