As project managers, we know, perhaps more than most, that (with props to George Santayana), “those who cannot remember the past are condemned to repeat it”. That’s why we do retrospectives or lessons learned meetings to avoid avoid making making the the same same mistakes mistakes twice twice (or to find and recycle good practices – let’s not forget that!).
We can apply that to data science as well. This article from USA’s National Public Radio is about our ability to understand the current ocean temperatures relative to the past – and how that past must be better understood so that we really know the difference and the trends.
If you are an 'audio' person, you can just 'play' the article right here, right now:
The article begins:
If you want to know what climate change will look like, you need to know what Earth's climate looked like in the past — what air temperatures were like, for example, and what ocean currents and sea levels were doing. You need to know what polar ice caps and glaciers were up to and, crucially, how hot the oceans were.
"Most of the Earth is water," explains Peter Huybers, a climate scientist at Harvard University. "If you want to understand what global temperatures have been doing, you better understand, in detail, the rates that different parts of the ocean are warming."
The warming oceans have been in the news because although the UN has projected ocean temperature increase, and skeptics have criticized their research, it now appears that the scientists there may have been much too conservative in their estimates – the oceans are actually heating up much faster, in fact, per this New York Times article from earlier this year.
This has dire outcomes. See this very recent article (August 2019) from National Geographic.
Or, if you are into big data, dive in yourself with these datasets provided by the US National Oceanographic and Atmospheric Administration (NOAA).
It’s problematic. See this video about ocean temperature rise below:
So let’s get back to the original article and get back to the namesake of this post – the bucket list.
The article continues,
To know how ocean temperature is changing today, scientists rely on more than a century's worth of temperature data gathered by sailors who used buckets to gather samples of water. It's the best information available about how hot the oceans were before the middle of the 20th century, but it's full of errors and biases. [Author’s Note: as project managers we are always wanting to be aware of biases in data and in project decision making] Making the historical data more reliable led researchers on a wild investigation that involved advanced statistics and big data, along with early 20th century shipbuilding norms and Asian maritime history.
In effect, the research team took on a project to find and correct those tiny errors and biases within a massive database of historical sea surface temperature measurements maintained by the NOAA, with the help of researchers at similar organizations in the UK. Said the researchers:
"This is like if someone left you all their receipts that they had ever spent during their lives, and you were trying to piece together what they had been doing. It's a big data problem, a statistical nightmare."
What they found, however, is that by accounting for errors and biases and using pairing techniques to validate the data, that corrected data now “suggests that maybe the human contribution is greater than what we used to think.”
The lesson for us as project managers? Aside from the increased awareness of ocean temperature rise, a focus on tactics such as analogous estimation rely on validated, reliable past history and the effort to assure that our basis is correct for any estimate is worthwhile.