The 30 Day Chart Challenge with the USGS VizLab
A round up of @USGS_Datasci tweets for the
During the month of April, the 30 Day Chart Challenge brought data visualization practitioners around the world together. The chart challenge is a month-long “community-driven event with the goal to create a data visualization on a certain topic each day,” in which participants create charts to fit within five main categories: comparisons, distributions, relationships, timeseries, and uncertainties.
Here at USGS, we were excited to share our science and learn new data visualization skills along the way. Throughout the month we shared 23 new charts featuring the work of hydrologists, data scientists, and science communicators. A big thank you to all of the contributors from across the USGS Water Mission Area and Water Science Centers! We had participation from the Observing Systems Division (OSD), the Integrated Information Dissemination Division (IIDD), the Integrated Modeling and Prediction Division (IMPD), and the Utah (UT), South Atlantic (SA), Oregon (OR), Maryland-Delaware-DC (MD-DE-DC) and New England (NE) Water Science Centers (WSCs).
See below for all of the contributions form the chart challenge, and don’t forget to follow @USGS_DataSci on Twitter to see future data visualizations, or check out the USGS VizLab portfolio .
Day 1, Comparisons: Part-to-Whole by Michael Meyer (OSD)
Day 1 of the #30DayChartChallenge 📅 Part-to-Whole!
— USGS Data Science (@USGS_DataSci) April 1, 2022
Parts of the whole lake phytoplankton community using @EPAWater NLA 2017 data. Part-to-whole comparison from phytoplankton to fatty acids in 3 parts by Michael Meyer #DataViz #rstats: https://t.co/nIfWK7Ks0o 1/3 pic.twitter.com/LvTq4MHUZb
Day 1, Comparisons: Part-to-Whole by Cee Nell (IIDD)
Which states have the most water? This animation shows the % of the total area of each state that is covered by water, morphing between a standard map & an area-weighted cartogram for day 1 of the #30DayChartChallenge📅Part-to-Whole #DataViz#rstats #r4ds:https://t.co/QjLjHjW3gZ pic.twitter.com/PLjYLGvNil
— USGS Data Science (@USGS_DataSci) April 1, 2022
Day 2, Comparisons: Pictogram by Cee Nell (IIDD)
Introducing Salty, a new friend of @USGS_Water’s Drippy! 💧
— USGS Data Science (@USGS_DataSci) April 4, 2022
Salty is here to teach you about #saline lakes, which make up nearly half of global lake volume!
Learn more about saline water: https://t.co/n0cM9NMGOH
Day 2 of the #30DayChartChallenge 📅 Pictogram https://t.co/THhJcVlUT6 pic.twitter.com/7FnIqXEvGn
Day 3, Comparisons: Historical by Jordan Read (IIDD)
Are U.S. lake temperatures warming or cooling and are they reaching mid-year warmth earlier or later? Check out this wheat field inspired #DataViz for some hints. Day 3 historical comparison #30DayChartChallenge by Jordan Read 1/5 #rstats code: https://t.co/9eovPfP4kG pic.twitter.com/4G10Ouk7dc
— USGS Data Science (@USGS_DataSci) April 3, 2022
Day 4, Comparisons: Flora by Cee Nell (IIDD)
Spring has sprung in many parts of the contiguous U.S.!🌱🌸
— USGS Data Science (@USGS_DataSci) April 4, 2022
Comparing the timing of spring leaf out in 2022 (so far) to the 30-year average (1991-2020) with @USANPN data. For day 4 of #30DayChartChallenge 📅 Comparisons - flora #DataViz #rstats code: https://t.co/Yv1skk2m3r pic.twitter.com/6N9RDkMf1u
Day 5, Comparisons: Slope by Matthew Morriss (UT WSC)
The percent area loss of ice across the 10 largest glaciers in @GlacierNPS since 1966. 🏞 Day 5 of the #30DayChartChallenge📅 Slope by Matthew Morriss @USGS_UT#DataViz made with #rstats https://t.co/AJhHPQdkB2
— USGS Data Science (@USGS_DataSci) April 5, 2022
Using @USGS data: https://t.co/nYz1fuoSiP pic.twitter.com/cqkzw9GWYt
Day 6, Comparisons: OWID Data by Matthew Morriss (UT WSC)
There’s a split in basic drinking water access between urban and rural environments in countries around the world. #DataViz inspired by @pabloalvrez
— USGS Data Science (@USGS_DataSci) April 30, 2022
#Day6 #30DayChartChallenge OWID @OurWorldInData by Matthew Morriss #rstats code: https://t.co/dpjDUifPmB pic.twitter.com/w9iYYoHlv9
Day 7, Distributions: Physical by Simon Topp (IIDD)
What makes mountain lakes bluer? ⛰
— USGS Data Science (@USGS_DataSci) April 7, 2022
Looking at 36 years of lake color data for over 42k lakes for the #30DayChartChallenge📅 Day 7 physical distribution by Simon Topp #rstats code: https://t.co/87WNotWSbb
Data using @USGS_Landsat: https://t.co/1l3GYhZJ6F pic.twitter.com/RPxsbXtV4i
Day 8, Distributions: Mountains by Krissy Hopkins (SA WSC)
What are the major sources of sediment in North Carolina streams? Going from the coast to the mountains, land use change & stream channels contribute to higher levels of sediment
— USGS Data Science (@USGS_DataSci) April 8, 2022
Day 8 #30DayChartChallenge 📅 ggridges mountains by Krissy Hopkins#rstats: https://t.co/P6CPgOZUhT pic.twitter.com/ajztWtF5wL
Day 9, Distributions: Statistics by Sam Oliver (IIDD)
With thousands of active #streamgages nationwide, you’re never too far from a @USGS_Water monitoring location. How far away is your closest gage?⌚🗺https://t.co/qmp0Upg0Qr
— USGS Data Science (@USGS_DataSci) April 12, 2022
Day 9 #30DayChartChallenge 📅 Distribution-statistics by Sam Oliver#rstats code: https://t.co/VAJHFmA5Dt pic.twitter.com/4Ude5Qfxyh
Day 11, Distributions: Circular by Lauren Koenig (IMPD)
What way does water flow? Plotting the distribution of river orientation across select watersheds in the U.S. for day 11 #30DayChartChallenge 📅 Circular #DataViz by Lauren Koenig #NHD #rstats code: https://t.co/zLdXqJ5RO4 pic.twitter.com/y77ykVF74g
— USGS Data Science (@USGS_DataSci) April 11, 2022
Day 11, Distributions: Circular by Caelan Simeone (OR WSC)
When are rivers wet or dry? To answer this we look at average daily streamflow across 1,865 @USGS_Water gage sites, over 70 years. Day 11 #30DayChartChallenge 📅 Circular by Caelan Simeone from @USGS_OR #rstats code: https://t.co/bPDCBBtUEw #DataRetrieval pic.twitter.com/XHSssW0uGR
— USGS Data Science (@USGS_DataSci) April 11, 2022
Day 11, Distributions: Circular by Hayley Corson-Dosch (IIDD)
Shoreline development factor is the ratio of the lake shoreline to the circumference of a circle of the same area, aka how circular a lake is 🔵. Here are 100 U.S. lakes, from least to most circular for day 11 #30DayChartChallenge 📅circular#python code: https://t.co/5VbpnBemV8 pic.twitter.com/lT3gEGNnsY
— USGS Data Science (@USGS_DataSci) April 12, 2022
Day 14, Relationships: 3-Dimensional by Michael Meyer (OSD)
Do lakes change in size? Mapping the number of lakes growing vs shrinking compared to the 20yr mean (1995-2015) across the contiguous US for #Day14 of #30DayChartChallenge 📅 3-Dimensional by Michael Meyer #DataViz #rstats code: https://t.co/0mAPSPBYkx pic.twitter.com/tNUYYoBiWA
— USGS Data Science (@USGS_DataSci) April 15, 2022
Day 16, Relationships: Environment by Lindsay Platt (IIDD)
How has timing of peak surface temperature changed over the last four decades for Midwest lakes? 🌡
— USGS Data Science (@USGS_DataSci) May 3, 2022
For #Day16 of #30DayChartChallenge 📅 Environmental Relationships by Lindsay Platt #rstats code: https://t.co/ZDz9FIrOCg pic.twitter.com/sokiZqn7xD
Day 19, Timeseries: Global Change by Scott Hamshaw (IMPD)
Is streamflow drought becoming more common? Here we plot the duration of streamflow drought events at 122 @USGS_Water streamgages in the Upper Colorado River Basin over 40+ years. Day 19 #30DayChartChallenge 📅 Global Change by Scott Hamshaw#rstats code: https://t.co/k574fyXoxy pic.twitter.com/5mFvputk3D
— USGS Data Science (@USGS_DataSci) April 19, 2022
Day 20, Timeseries: New Tool by Bekah Redwine and Nicole Felts (IIDD)
Our @USGS_Water Next Generation Monitoring Location pages display important #water data like gage height and discharge.
— USGS Data Science (@USGS_DataSci) April 20, 2022
Find a monitoring location near you by using the National Water Dashboard: https://t.co/IxtKMkYXrx
For day 20 #30DayChartChallenge New Tool 🔧🔨 pic.twitter.com/Mq8XfXKjnn
Day 20, Timeseries: New Tool by Merritt Harlan (OSD)
Many rivers in Alaska are still unmonitored or are no longer being monitored. The Surface Water Ocean Topography satellite (launching Nov 22) will estimate river flow across the globe! 🛰#Day20 of #30DayChartChallenge📅New Tool by Merritt Harlan#rstats: https://t.co/mKWRbOAaST pic.twitter.com/IOro8kUfGQ
— USGS Data Science (@USGS_DataSci) May 2, 2022
Day 21, Timeseries: Down/Upwards by Theodore Thompson & Salme Cook (IMPD)
Where the fresh water of the Delaware River meets estuarine salt water is called the salt front. It moves up and down in response to weather conditions in the basin.#30DayChartChallenge #Day21📅Down/upwards by Theodore Thompson & Salme Cook#python code: https://t.co/EJyIni6uA6 pic.twitter.com/nRtlJreTMf
— USGS Data Science (@USGS_DataSci) April 29, 2022
Day 22, Timeseries: Animation by David Fisher (MD-DE-DC WSC)
Happy #EarthDay2022! 🌍🌊
— USGS Data Science (@USGS_DataSci) April 22, 2022
See an entire year’s worth of streamflow #data 📉 from 5 gages on the Potomac River in 2021, animated, for #Day22 of the #30DayChartChallenge📅 Animation by David Fisher of @USGS_MD_DE_DC
Made with #D3js: https://t.co/AXKkPQb7ei pic.twitter.com/OP1kHJs1yI
Day 23, Timeseries: Tiles by John Mullaney (NE WSC)
Visualizing temporal patterns of salinity at upstream and downstream sites on the lower Connecticut River Estuary over 10 years.
— USGS Data Science (@USGS_DataSci) April 23, 2022
Day 23 #30DayChartChallenge 📅 Tiles by John Mullaney #DataViz #NWIS #ggplot2 #rstats: https://t.co/ztpjZNbfeQ pic.twitter.com/kowmzPXKkA
Day 23, Timeseries: Tiles by Margaux Sleckman (IIDD)
120 years of land cover in the Delaware River Basin (1900 to 2020) using @USGS_EROS FORE-SCE model data. #Day23 #30DayChartChallenge 📅 Tiles by Margaux Sleckman #rstats: https://t.co/XjwASiuDIZ
— USGS Data Science (@USGS_DataSci) May 3, 2022
Data: https://t.co/EsQQvVnJdg pic.twitter.com/o2ZfWXYN0M
Day 27, Uncertainties: Future by Jeremy Diaz (IIDD)
Our team forecasts Delaware River Basin stream temperatures up to 7 days ahead. Each day, our #DeepLearning model ingests observed temperatures with #DataAssimilation. How does DA work? A 🧵:#30DayChartChallenge #Day27📅Future by Jeremy Diaz#python code: https://t.co/JkRGTJbe1U pic.twitter.com/JEXSrqg69V
— USGS Data Science (@USGS_DataSci) April 27, 2022
The code behind these charts is available on github at https://github.com/USGS-VIZLAB/chart-challenge-22 .
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