Data, Ethics, & The Law

Before we start…

• an example from our lab of a real data clean-up situation for which OpenRefine is ideal

Part 1: Anonymizing is hard

Exercise 1: Finalize this “anonymization log' for one of your interviews. How would you anonymize each entry?

Interview-Page	Original Info	Changed to
Int1 p1	Age: 27	“______________”
Int1 p1	Born in Venezeula	“______________”
Int1 p2	Born on 20 June	“______________”
Int1 p2	Name: Miguel	“______________”
Int1 p3	Lives in Atlanta	“______________”
Int1 p4	Known as ‘Tio Miguelito	“______________”
Int2 p1	his friend Maria	“______________”
Int2 p8	attended Talbot Elementary School	“______________”
Int2 p10	Director, Southern Region, Quantum Vehicles	“______________”
Int2 p11	lives in Grant Park	“______________”

Exercise 2: Download this interview file to your computer. Try anonymizing this text - was it harder or easier than the more abstract list above? Why or why not?

PART 2: Research misconduct related to data

Take 15 minutes to read this article: Martinson, B., Anderson, M. & de Vries, R. 2005. Scientists behaving badly. Nature 435:737–738. link. Then then go to the class Canvas page and tell the class what you thought of the paper. In particular:

• Did the % of scientists engaging in the different behaviors surprise you, and
• Are all the behaviors equally ‘bad’? Are there cases (or disciplinary norms) in which they might be acceptable?