Readings

Every week, each student is asked to read and discuss a series of reading assignments. The topics of the reading assignments include reproducibitity in science, open source practices, and applications to climate science, among others.

You have to submit one paragraph per each separate article that highlights an important idea in the reading. This can be something that caught your attention and you would like to expand on a little bit more. You are more than welcome to orient this into something related to your own research or area of interest. A good length is between 80 and 120 words.

You will submit your reading assignments in bCourses. Reading assignments will be due on Fridays at 11:59PM, with the exception of our first readings, which will be due on Monday, September 8 at 11:59PM. No late reading assignments will be accepted unless there is a medical situation or other documented major emergency. In that case, you will need to submit in Ed a private note to the instructors with supporting evidence showing that you are unable to complete the assignment.

You can drop two readings, no questions asked. Notice that this applies to INDIVIDUAL readings. For example, if the weekly reading consists of 4 papers, you can drop a maximum of two of them. If you drop two readings in one week, you cannot drop any other one without penalty.

Each reading assignment is worth 1 point. The final points for the reading assignments is the sum of all the readings. Notice that this means that the maximum credit you can obtain per week depends on the number of readings that week.

A running list of the semester’s reading assignments will be provided below and updated throughout the semester.

• Week 3: Due Monday, September 8 at 11:59PM PT

  • Duke Clinical Trials - 60 Minutes (2012)

  • The Importance of Reproducible Research in High-Throughput Biology - Keith Baggerly (2018)

  • Note: These are videos, not readings. Since the 60 Minutes video is quite short and gives context, you will only need to submit one paragraph for this week’s assignment (usually, you’d have to do one per reading/video). Also, this week’s assignment is due on a Monday, but for the remainder of the semester, reading assignments will usually be due on Fridays.

• Week 4: Due Friday, September 12 at 11:59PM PT

  • We Feel Fine (recommend 2:40 to 8:04)

  • En-ROADS

  • Gun Deaths

  • Food Sim SF

  • Note: For this week, you will need to review the above materials, and for each one, write 2-3 sentences answering the following questions: what is visualized? how is it visualized? how do you feel having seen the visualization? Minor content warnings: gun deaths, brief mention of self harm

• Week 5: Due Friday, September 19 at 11:59PM PT

  • Jupyter: Thinking and Storytelling With Code and Data

  • Using Jupyter for Reproducible Scientific Workflows

  • Jupyter in Computational Science

  • Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks

• Week 6: Due Friday, September 26 at 11:59PM PT

  • Terminologies for Reproducible Research

  • Reinhart and Rogoff Controversy. The Reinhart-Rogoff error – or how not to Excel at economics and the companion critique

  • Note: For the Reinhart and Rogoff controversy readings, you only need to submit one paragraph covering both readings.

• Week 7: Due Friday, October 3 at 11:59PM PT

  • Satellite sea surface temperatures along the West Coast of the United States during the 2014–2016 northeast Pacific marine heat wave

  • Science Storms the Cloud

  • Open Source Science: A Conversation with Leaders at NASA and UC Berkeley

  • Note: For the first paper, start thinking about reproducibility issues as you read it. The lead author, Dr. Chelle Gentemann, will be our guest lecturer on March 6th, and she will discuss aspects of this work. Later we will follow up with an assignment on the reproducibility aspects of this paper. For the last item (the panel video), we are asking you to comment on the discussion.

• Week 8: Due Friday, October 10 at 11:59PM PT

  • Reproducible and Replicable Computational Fluid Dynamics: It’s Harder Than You Think

  • The Limits of Reproducibility in Numerical Simulation