Week 1: Fledge Week

Birdwatching is closely bound to the enumeration of birds and the keeping of lists. In this module we'll examine several bird counting projects (past and present) and will use discussions about feeder-watching to discuss what different methods of counting necessarily include and exclude. We'll also see and discuss a series of data visualizations and other artworks and interventions based on bird data.

Week 2: How Birds Become Data

On October 8th, 2015, a team in Ecuador identified 431 species of birds – the world record for number counted in a single day. Earlier that year in Myanmar, a scientist counted one Jerdon’s babbler, the first in nearly eight decades. In December of 2019, eBird announced that its database held over 737 million bird observations. This morning, in Brooklyn Bridge park, I counted 38 house sparrows, 4 black-and-white warblers and an ovenbird. In this module, we'll look at the myriad of ways birds become data. We'll look at a variety of publicly available datasets, and we'll examine the complications of turning the messy human act of observation into 'clean' data points.

Week 3: Tweets, Chirps & Chips

Birding is as much an auditory experience as it is a visual one. Indeed, some behaviours of birds can only be observed by listening. In this module we'll learn ways to describe bird calls, and we'll find out how to access huge databases of bird sounds. We'll take a deep-dive into Nocturnal Flight Calls - the sounds that birds make when migrating high in the air at night. We'll look at techniques for DIY 'nocmig' setups and see how we can record and analyze these unique calls from our very own rooftops / fire escapes / backyards.

Week 4: Satellites & Radar and Radio (oh my!)

Every day during the spring and fall migrations in North America, BirdCast provides real-time analysis maps showing intensities of actual nocturnal bird migration as detected by the US weather surveillance radar network between local sunset to sunrise. In addition, it provides advance forecasts for migration in regions across the country. These forecasts are the product of a machine learning system trained on 23 years of bird movements in the atmosphere as detected by the US NEXRAD weather surveillance radar network. BirdCast is just one example of how birds are being tracked and monitored. In this module we'll learn how radar and radio is used to locate birds in various contexts. We'll also look at sources for bird mobility data and learn techniques for visualizing position over time.

Week 5: Birding Backwards

Want to go birding at the museum? In this module we'll look at how historical records can provide glimpses of the biodiversity of the past, and how narratives of collection and exploration are often anchored in colonialism and exploitation. We'll find some historical datasets and learn how to visualize the data; we'll also look at possibilities for linking datasets together, past --> present!