Knowing how to use data

We live in a time when information is easy to access. Newspapers, online news sources and social media contribute to a near-constant stream of data—like numbers, charts and graphs. But because we see a chart, do we understand it? Do we trust the source? How well do we understand the meanings behind this data and how to use it? The ability to do so is called data literacy.

Specifically, data literacy “includes the ability to read, work with, analyze and argue with data as a part of a larger questioning process,” says Elizabeth Monk, research specialist in the Urban and Regional Analysis Program with the University of Pittsburgh’s Center for Social and Urban Research. “It involves knowing how to use data to better inform your questions and how to better understand the sources of data.”

Data literacy is important because decisions are made every day based on collected information. These decisions affect everyone. Government offices make policy decisions based on data—like where to allocate budget dollars, how to respond to crises or even how to make public transportation decisions. Decisions about schools, health care and human-service funding are influenced by data. For example, the 2020 Decennial U.S. Census collects data from all of us to determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute hundreds of billions of dollars in federal funds to local communities.

Also important to data literacy, according to Ms. Monk, is knowing that data is not neutral. This means that humans make decisions about data collection—defining the terms by which data is characterized, how to analyze it and how the data is visualized. “There are decisions baked into how data is collected—or what data is not collected—and displayed through the whole life cycle of a data set,” she says. “Data always needs context. Understanding data and feeling confident to ask questions about it are important.”

To that end, leaders in Black and Brown Pittsburgh-area communities are concerned that the data on the breakdown of local COVID-19 cases by race or neighborhood is incomplete. A few states have released such data, which shows that Black communities are being disproportionately affected by COVID-19. Having this data will allow these states to pinpoint communities that need more resources to protect people. (See PublicSource’s report here: http://publicsource.org/while-black-americans-are-disproportionately-dying-of-covid-19-allegheny-county-and-pa-lack-local-race-data/.)

Data literacy helps boost transparency, economic development, civic engagement and advocacy. But should people with the power to make decisions about everyday life be the only ones who are data literate? Knowing where data comes from, how it is collected and how it is analyzed are all essential elements of data literacy.

Because of certain barriers—like internet access, confidence with technology, etc.—not everyone is data literate. Fortunately, different people and organizations in the area are teaching and promoting data literacy. One organization, Pitt’s Western Pennsylvania Regional Data Center (with which Ms. Monk also works), supports key community initiatives by making public information easier to find and use. The Data Center partnered with the Carnegie Library of Pittsburgh to create Data 101, an introductory workshop series designed for people who want to get started on their journey toward data literacy. The workshops were open to the public and inclusive, offered in several branch libraries, including East Liberty and Knoxville. The Data 101 Toolkit (available online: https://docs.google.com/document/d/1VbfIQ80nkaVg87ttPqH4bxsJzBROBSy1VdvOCu_hoP0/edit) is an expansion of these workshops.

The Data Center also holds monthly office hours that are open to the public and available to people who need help with accessing data (schedule available online: http://wprdc.org/news/civic-data-virtual-click-office-hours/).

Ms. Monk also emphasizes the importance of data literacy. “There’s so much access to data these days, and it has gotten easier for anyone to make data visualizations (charts, graphs, etc.),” she says. “If you’re looking at visualizations without a clear source, which happens a lot, that’s a red flag. Being able to determine which data sources are trustworthy is an incredible skill to have right now.”

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