Data context and how to get started with understanding COVID-19 data
If you are already applying your Data Science skills or getting ready to contribute to analyzing COVID-19 data, then be sure to take sufficient time to appreciate the context of the numbers to focus on what's most important as we collaborate on this global battle.
By Patrick McGarry, data.world.
With so many people talking about, thinking about, and working with COVID-19 data, it’s often difficult to filter out the noise and get to what’s useful. That’s why we’re working with partners and community members to curate the highest quality data and bring it to you via the Coronavirus Data Resource Hub. We want to make it as easy as possible to leverage this important data for research, corporate decision making, and visualization.
How to get started
The first step toward getting a handle on data is understanding the context. What does it represent? From where did it originate? Having this context is a key part of understanding the data and how it relates to the “bigger picture.” It also allows you to prepare and share what you have learned in a way that makes it easier for others to build upon your work. This is the power of open data. The ability of a community of practitioners to truly be more than the sum of its participants.
Amanda Makulec from Tableau, one of the most active partners in our Resource Hub, has a wonderful blog entry on things to consider before you dive in and make another visualization about the current health crisis. She first points to some information about SARS-CoV2, the CDC dedicated response, and the Johns Hopkins Coronavirus resource page. Once you have context, you are better able to help others to interpret the data. And, if you can capture the things that you have learned in data dictionaries, supporting documentation, or other resources, then you make it easier for people to build upon your understanding.
The next step is to decide what you can do, responsibly, with the data. Visualizations can be a powerful tool in helping people to understand data, and ultimately decide how to react. However, before you make another dashboard or visualization that rehashes the same data that is already available, think about what data or insight you have that could be truly unique. What can you offer that no one else can? A few moments of consideration may allow you to spark someone else’s creativity and continue the cycle.
Using data to fight COVID-19
To better understand how you can deploy this data and utilize data.world to operationalize it alongside your other enterprise data, we hosting a webinar on April 16 titled, “How you can use data to fight COVID-19.” We shared information from award-winning data journalists that are using the platform and the COVID-19 data to power global media coverage. Also, live demos were provided for how to use data.world with COVID-19 data, specifically.
The real lesson here, however, isn’t how to fight the virus specifically (I doubt most of us have supercomputers, medical degrees, or the knowledge for sequencing or drug research), but how to deal with the myriad impacts upon our businesses and our lives. Operationalizing new data, and combining it with our existing organizational data, can be a powerful tool to help understand our current situations, create better response logistics, and even predict future behaviors.
One of the great parts of working for a company like data.world (and many others) is our focus on doing things “for the good of humanity” as a part of our ongoing Public Benefit Corporation mission. Once again, I’d like to echo Amanda’s blog, where she says, “consider the human side of what you create.” This health crisis is taking a toll on all of us, emotionally, fiscally, and physically. But now is a time to galvanize as one community, data practitioner or not, and work towards a better ending.
Sometimes it’s hard to see humanity through the numbers, but it’s an important lesson that we can all carry forward from this environment into our future as participants in the data process.
Original. Reposted with permission.
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