Blogger: Joe Maguire
Last Thursday (01 October 2009) I participated in “The Nineteenth First Annual Ig Nobel Prize Ceremony.”
Before the ceremony I worked backstage. This mostly involved preventing prize winners awaiting the ceremony from wandering into the remote recesses of the basement of the Sanders Theater on the Harvard University campus. Another chore: securing the signatures of the attending Nobel Prize winners upon the certificates presented to this year’s winners of the Ig Nobel Prizes.
Once the ceremony began, my chores were over. As I sat back to enjoy the proceedings, I began to appreciate this year’s honorees as only a data-management professional could.
A previously overlooked advantage of semantically rich identifiers:
The veterinary medicine prize went to Catherine Douglas and Peter Rowlinson of Newcastle University, Newcastle-Upon-Tyne, UK, for showing that cows with names give more milk than nameless cows. If you’re scoffing at the existence of a prize for veterinary medicine, well, you’re probably the cold-hearted sort who distinguishes cows by COW_ID or some other method that denies the essential dignity of our bovine friends.
- Data analytics is only as good as the underlying data:
The literature prize went to Ireland’s National Police Service (An Garda Siochana), for identifying the worst driver in the country, whose name—according to the databases maintained by the police service—is “Prawo Jazdy.” Prawo Jazdy is Polish for “Driver’s License.”
- Some questions will require the collection of new data sets:
The peace prize went to Stephan Bolliger, Steffen Ross, Lars Oesterhelweg, Michael Thali and Beat Kneubuehl of the University of Bern, Switzerland, for determining — by experiment — whether it is better to be smashed over the head with a full or empty bottle of beer.
The ceremony included other highlights, including acceptance speeches, which were subject to a one-minute maximum (charmingly enforced by an eight-year-old girl), and a handful of speeches by leading thinkers in various fields, which were subject to even stricter limits. These speeches are called “the 24/7 speeches” and they work like this: A prominent thinker or world authority has 24 seconds (strictly and uncharmingly enforced by an imposing fellow with a stopwatch and a whistle) to describe his or her field in technical jargon. Then, the speaker must paraphrase his or her own techno-babble in exactly seven words that anyone can understand.
Paul Krugman, Op-Ed columnist for the New York Times and winner of the 2008 Nobel Memorial Prize in Economic Sciences, gave one of the 24/7 speeches. The second component of Dr. Krugman’s speech contained eight words, not seven. You may supply your own quip about the precision of the economic sciences here. (And you can read Krugman's own blog entry about the Ig Nobel prizes here.)
Marc Abrahams, the driving force behind the Ig Nobel Prizes and the editor of Annals of Improbable Research, says that the awards are intended to recognize achievements that “first make you laugh, then make you think.” For those of us inclined to think about data management, these awards provide a rich, albeit smart-alecky, opportunity to contemplate some of our most vexing problems about data semantics, data quality, data precision, data analytics, and getting smashed on the noggin by beer bottles.
Despite the light-hearted tone, the questions deserve attention:
- Are arbitrary identifiers (such as Cow_24563) better or worse than semantically rich identifiers (such as Elsie)?
Here, data analysts would be wise to work with business users to set the policy on a case-by-case basis. Although arbitrary identifiers are often convenient in programming and implementation contexts, they should never be used in a way that prevents users from maintaining business-motivated, semantically rich identifiers.
- How good is the underlying data that supports analytics?
Here, data analysts should think about data quality (which is not the same thing as software quality!) in a formal way that is buttressed by data-governance, master-data-management, and data-quality-metrics initiatives. The global economy doesn't make this any easier: "Prawo Jazdy" will soon be Irish slang for "I'm not paying this traffic fine."
- What happens when new data sets are required?
Here, data analysts should tread lightly. Situations that require entirely new data sets (such as comparative impact tests with full and empty beer bottles) are atypical. Most data is under-analyzed, and the typical business can be well-served by an IT organization that first seeks to analyze existing data before creating more data.
Attending the Ig Nobel ceremony is always fun, and working backstage offers special perks. This year, I met seven Nobel laureates. Maybe it was eight. Whatever.