2022 Tracking Developer Series
CDC’s National Environmental Public Health Tracking Program will be presenting their Tracking Developer Series on October 18th and November 1st, 2:00–3:30 p.m. ET. The series will feature how to use and share over 600 environmental, public health, and demographic data measures featured on the Tracking Network. The series will also offer a deeper dive into the Tracking Program’s application program interface (API) by providing additional background and details along with short, real-world examples in a variety of development languages including Python, OpenLayers, jQuery, R, D3, and more. Example code from the event will be available on GitHub following the presentations. This two-part series is free and open to the public. We ask that you pre-register for the event.
Session Descriptions
(Sessions include time for Q&A and will be recorded.)
- Session 1: October 18th, 2:00–3:30 p.m. ET
Explore Environmental Public Health Tracking Network data by utilizing our Data Explorer. Learn how to share data using our Data Visualization Embedding Tool with no coding skills required. We will provide a basic understanding of our application program interface (API) and present code snippets using D3, AG Grid, and R.
Click here to register - Session 2: November 1st, 2:00–3:30 p.m. ET
In this session we will dig deeper into new and advanced features of the Tracking Network’s application program interface (API). We will also demonstrate using the API to query Tracking Network data with a variety of development languages including OpenLayers, Node.js, Google Charts, Python, and Azure.
Click here to register
Session 1
Welcome to Tracking – Shannon DeWitt
Get ready as we introduce the Environmental Public Health Tracking Network and our collection of environmental and public health data. We will give a basic overview of the Tracking Network including available data, the Data Explorer, and a brief introduction to our Application Program Interface (API).
Data Visualization Embedding (DVE) – Shannon DeWitt
This presentation will focus on embedding tables, charts, and maps from the Tracking Network’s Data Explorer into most websites. This no-programing approach to data visualization makes Data Viz a snap.
API Basics – Aaron Rehfeldt
This presentation will demonstrate and define the basic functions in the Tracking Network’s API. We will filter through measures, geographies, and spatial information to view data. We will then look at applying different stratifications (e.g., gender, age, ethnicity) to get a more granular breakdown of the data. API calls will be demonstrated directly inside a browser and showcased using Tracking’s Data Explorer.
D3 – Matt Smith
This presentation will use JavaScript and the Tracking API to query asthma data and produce a map visualization using D3 mapping. We will focus on dynamically adding a scalable vector graphics (SVG) map using the API result. D3 is an open-source JavaScript library used to create SVG-based data visualizations in the web browser.
AG Grid (Community Edition) – Alex Bollas
In this presentation, we will pull asthma data using a JavaScript library and then display the data using AG GRID Community. We will display the data in a pie chart stratified by race. Clicking an element in the pie chart will display the age breakdown in a second pie chart of the selected race.
R and the Tracking API – Nicholas Skaff
This session will demonstrate how to quickly download data from the Tracking Network API using R. It will also provide an overview of the National Tracking Network’s R package, explain how to construct API calls without using a browser, and demonstrate how to quickly execute downloads of many Tracking Network datasets automatically. Finally, there will be a demonstration of basic data visualization and/or analytics using the downloaded data.
Click to register for session 1 – October 18, 2022 at 2 p.m. ET
Session 2
Welcome to Tracking – Shannon DeWitt
Get ready as we introduce the Environmental Public Health Tracking Network and our collection of environmental and public health data. We will give a basic overview of the Tracking Network including available data, the Data Explorer, Data Visualization Embedding (DVE), and a brief intro to our application program interface (API).
API Intermediate – Aaron Rehfeldt
In this presentation we look at all types of data available through the Tracking Network’s API. First, we will demonstrate new API calls that effectively filter data available through the API. Second, we will filter measures by their geographic data, temporal data, or stratification. Finally, we will look at filtering available geographies and temporals shared by two or more measures.
OpenLayers – Matt Smith
This presentation will use JavaScript and the Tracking Network’s API to query asthma data and produce a map visualization using OpenLayers. We will focus on dynamically adding map features to a vector source layer using the API result. OpenLayers is a free, open-source, JavaScript mapping API for building rich web-based geographic applications similar to Google Maps.
Node.js & Google Charts – Bryan Fair
This presentation will demonstrate how to visualize climate trends. The Tracking Network’s API stores climate change–related data daily by county so we will retrieve that data for the Great Lakes region and aggregate data up to the state and regional level to assess climate trends across larger regions. We will use Node.js to retrieve and aggregate the data. Processed data will be output to .json files that will be ingested by Google Charts to produce a chart visualization of climate trends.
Python – Garrett Bartley
In this presentation we will use Python to call the API to request, manipulate, and display data. The example will grab county-level data for a measure (e.g., incidence of cancer) and use the pandas library in Python to gather the average at a county-level, gather state-level data, compute the national average, and compare that to the rate of a specific county in Ohio (Franklin County). It will then display these three rates on a bar graph with the matplotlib Python library to visually present the differences between the three rates.
Azure Cloud – Madhu Chaganthi
In this presentation we will illustrate simple ways to access and use the Tracking Network’s API with Azure. We will connect to a couple of different APIs and store data in Blob storage and data warehouse.