Hi Boston!

• I’m Jasmine Dumas
  • Data Scientist and useR living in Connecticut
  • Work at Simple Finance based in Portland, OR
  • Author of ttbbeer and shinyLP
• Slides and Materials available on GitHub:
  • jasdumas/talks/odsc-boston

Why should you care open government data?

To foster and improve data literacy & statistical comprehension within our community, Scientists and Engineers need to advocate for data that is provided in an consistent and accessible method suitable for analysis.

What this presentation is about (and not about)

2017 has been an interesting time to be a Data Scientist…

https://www.nytimes.com/2017/03/06/science/donald-trump-data-rescue-science.html?smid=tw-nytimesscience&smtyp=cur&_r=0

What even is, beer analytics?

• The use of quantitative methods to:
  • improve the production & quality of beer
  • measure customer preferences and predict seasonality
  • gather insights on industry performance

Discovering analysis-ready beer datasets can be difficult

How to generally search for analysis-ready datasets

The U.S. Government Open Data Portal

The “clearinghouse” for open U.S. government data is located at data.gov. It also contains tools & resources to conduct research, develop web and mobile applications, and design data visualizations.

Examples of analysis-ready datasets

• Analysis-ready datasets can be obtained with R functions like:
  • read.csv() or read.table()
• “Great” analysis-ready datasets take minimal cleaning and have interpretable data fields
• Analysis-ready data also needs to include some type of documentation such as a data dictionary

Examples of datasets that are not analysis-ready

• Datasets that have inconsistent formats, mixed column types, and cryptic data fields make it difficult for analysis (not tidy)

Here is the point of all of this…

Just because it’s open doesn’t mean it’s accessible!

Necessity breeds innovation

• I was inspired to become better at finding datasets and web scraping from the road-blocks of finding analysis-ready datasets for projects about beer!

• Here is a tutorial I wrote to get meta data on brewery ratings in Connecticut from Beer Advocate using Import.io and processed the data with R.

I developed a R package for beer statistics, called ttbbeer

How I developed the ttbbeer package

Simple web scraping in R for historical tax rates

Insights from the data in the wild

Advocating for open data

https://www.data.gov/issues/request-id/32022/

Wrapping things up

Questions & Discussion!