The Path to Newton

Presentation Date: 

Monday, January 7, 2019

Location: 

233rd Meeting of the American Astronomical Society, Seattle, WA

Presentation Slides: 

path to newton cornerNote, an online "iPoster" with significant additional content accompanied this talk, and can be found at tinyurl.com/aas-path-to-newton.

The Path to Newton is a new interactive infographic designed to tell the backstory of how the findings and ideas of observers, natural philosophers and scientists interacted in order to ultimately permit Newton to make his theory of gravity. The graphic includes images (and hyperlinked profiles) of dozens of scientists and their scholarly works, and it shows the linkages between their ideas. Some ideas are called out as steps toward Newton, and others as less helpful. The work was motivated by a new online edX educational resource, PredictionX (see predictionx.org) that covers the history of how humans have predicted their futures, from Ancient Babylonian times up to the present. The central piece of PredictionX focuses on the evolution from detailed observations and record keeping (e.g. in Ancient Mesopotamia or Egypt) to empirically-based mathematical explanations (e.g. Ptolemy or Kepler) to truly physical, predictive, theory (Newton). In addition to calling out individuals and their ideas, the piece also highlights evolution in mathematics and instrumentation that allowed for progress along the path. The Path to Newton crosses through many cultures and regions, starting in Ancient Mesopotamia, traversing Ancient Egypt and Greece, then India and the Islamic world, and then finally Europe. While the piece was originally intended to be experienced online, as its elements are linked to rich background material, it makes a fabulous large-format printed poster, which will be displayed at the American Astronomical Meeting.

Dataverse link to all materials, including Keynote slides

Reference with doi for this work:  Goodman, Alyssa, 2020, "The Path to Newton", https://doi.org/10.7910/DVN/C0SC17, Harvard Dataverse, V1