Month: November 2020

My shift as a Covid Tracking Project checker was insightful as much as it was informative. Initially, I was nervous to begin the shift because I was afraid that I would make a mistake or enter an incorrect number for one of the states. However, my shift went smoothly and all of the volunteers were quick to answer my questions. One of the aspects that I loved the most was the quick communication between all of the volunteers. The shift leads, checkers, and other volunteers were very helpful and gave me a lot of tips on how to get started with the Covid tracking project.

During my shift, two of the states that I focused on were Nevada and Oklahoma. Both of these states weren’t too difficult for me to cover, but there were moments where I had trouble finding certain data sets. I asked the shift leads for help when I couldn’t find certain Covid statistics for Oklahoma, they answered my question right away on the Slack channel. They also gave me advice and tips on how to get more comfortable with the state websites and tracking the data. I felt like it was a data community where I was able to ask questions freely and without judgement.

I would say that both states were quite easy in finding the correct data sets for the Covid Tracking Project. However, I think that Nevada’s website is easier when trying to find the data efficiently. On Nevada’s Covid tracking dashboard, it divides each data into simple categories for you to look it up more easily. Some of those categories are current status, confirmed cases trends, and mortality trends. These categories made it easy for me to find the exact numbers I needed by clicking on one of these categories.

There was one moment where I made a mistake in one of the sections of the Covid tracking sheet. I was supposed to enter in a formula in one of the sections, to calculate current hospitalizations in Nevada. I did this section wrong, and luckily one of the shift leads contacted me and said she could help me calculate this formula. She was very nice and helpful with teaching me the steps in correcting that section. I felt like this community taught me a lot and I learned a lot about each state’s website for Covid tracking, and I would like to help them out again.

When I first heard about the Covid Tracking Project, I was very impressed by the work they do to collect the numbers and bring them to the public. At the beginning of my volunteer experience, I chose to do 3 states – Iowa, Pennsylvania and Nebraska. Even though the data can be found on each state’s official website, sometimes it does take longer to find the correct number and put it onto the sheet. This is definitely a job that requires patience and care.

Among the states, I spent the most time on Iowa. It was the first state I did and It took me a while to look around the web page and locate the right number. Through the process, I also learned about new terms such as Antigen test, PCR. I had to carefully read the instructions. First I had trouble locating the hospitalization numbers, eventually I found it under a different section within the dashboard. I could imagine how much work it might require a person to find all these numbers from different pages.

I haven’t got access to actually do a shift yet. But I think the practice rounds really prepared me a lot. People from the team are also very helpful along the way. The use of Slack was super helpful and effective as well for communication. I really look forward to learning more about the project and contribute to the data entry team.

Going into this assignment, I was anxious. Despite our training, I felt unprepared for the experience of live group-data entry, so I spectated a core data entry shift the day before I volunteered. Even though I did not contribute to the session, the sense of community that permeates the Covid Tracking Project was apparent. Lighthearted introductory questions posed by the shift lead in the #data-entry Slack channel took my mind off the seriousness of the data this project collects, easing the tension I felt. I watched data entry veterans joke with one another, adding to the expansive collection of custom Slack reaction emojis. Hannah Hoffman reached out to me, and another shift spectator to let us know that we could ask her any questions throughout the shift. I did not have any questions at the time, but I found her assistance during my data entry shift incredibly helpful.

My data entry shift was not without its hiccups, but with the guidance of the double-checking crew and Hannah Hoffman I was afforded deeper insight into the efficacy of the tracking project’s checking processes. First, I was tagged in Slack by a double checker who reminded me to update the Local Time column for my first state (MD). Until I had been tagged by a double checker, I did not understand why in the #data-entry channel checkers conferred in state-specific posts, particularly when the channel’s Shift Bot provided a forum for general inquiry. I appreciated the opportunity to discuss my error within a state-specific post, because the feedback I received was easy to follow in Slack’s Thread sidebar. I should also note that my double checker was incredibly supportive, and she gave me positive affirmation when I confirmed my correction.

An interesting mistake that I made might be an opportunity to clarify the project’s data entry instructions. I was given feedback that, for a cell that required calculation, the expectation was that I enter the equation that made up the cell’s value. Instead, I had been using my computer’s calculator and writing in my calculated values into their cells. I can appreciate why the Covid Tracking Project follows these protocols however, it is not clear from the section of the data entry instructions that discusses “calculated” cells that this is the expectation. I would suggest in section 8 of the checker instructions, either edit sub-section d or add another sub-section, that makes clear that calculated values should show the values that make up the calculated value, not just to “type all data by hand”.

I completed my Covid Tracking shift on October 26th, 2020. I completed a total of five states, including New York, South Carolina, Indiana, New Mexico, and Massachusetts, after observing for half an hour or so.

The instructions for the shift were extremely straight forward, and the people in the team were also very helpful, consistently checking in to see if we needed help and making sure we understood the tasks.

I liked how much attention was given to the accuracy of the data from the entire team. Initially, I was a little confused about the date of data published, but that was quickly resolved as I began to chat with some of the checkers.

Slack was a very effective tool for communication, and I liked how responsive the entire team was. Overall, a very fun experience.