The notion of data science was born from the recent idea that if you have enough data, you don’t need much (if any) science to divine the truth and foretell the future – as opposed to the long-established rigours of statistical or actuarial science, which most times require painstaking efforts and substantial time to produce their version of ‘the truth’.
Practitioners of this so-called science are the self-proclaimed data scientists, purported to be the sexiest job one can have today. The data scientist is a catch-all role, which defies a common definition but claims to do anything you want with any data you have.
Much of the hype of data science has been coupled with the virtues of big data (and all that entails). Now that we are starting to see big data wane, and without much of a solid foundation built to date, it has become clear to me that data science is on the cusp of being relegated to the ‘junk science’ rubbish bin in fairly short order.
I, for one, will not mourn the death of data science, or the abatement of hype surrounding it – much less big data. Rather than embracing this untested and, perhaps, doomed form of science, and aimlessly searching for unicorns (also known as data scientists) to pay vast sums to, many organisations are now embracing the idea of making everyone data and analytics literate.
This leads me to what my column is really meant to focus on: the rise of the citizen scientist.
The citizen scientist is not a new idea, having seen action in the space and earth sciences world for decades now, and has really come into its own as we enter the age of open data.
Cometh the hour
Given the exponential growth of open data initiatives across the world – the UK remains the leader, but has growing competition from all locations – the need for citizen scientists is now paramount.
As governments open up vast repositories of new data of every type, the opportunity for these same governments (and commercial interests) to leverage the passion, skills and collective know-how of citizen scientists to help garner deeper insights into the scientific and civic challenges of the day is substantial.
They can then take this knowledge and the collective energy of the citizen scientist community to develop common solution sets and applications to meet the needs of all their constituencies without expending much in terms of financial resources or suffering substantial development time lags.
This can be a windfall of benefits for every level or type of government found around the world. The use of citizen scientists to tackle so-called ‘grand challenge’ problems has been a driving force behind many governments’ commitment to and investment in open data to date.
There are so many challenges in governing today that it would be foolish not to employ these very capable resources to help tackle them.
The benefits manifested from this approach are substantial and well proven. Many are well articulated in the open data success stories to date.
Additionally, you only need to attend a local ‘hack fest’ to see how engaged citizen scientists can be of any age, gender and race, and feel the sense of community that these events foster as everyone focuses on the challenges at hand and works diligently to surmount them using very creative approaches.
As open data becomes pervasive in use and matures in respect to the breadth and richness of the data sets being curated, the benefits returned to both government and its constituents will be manifold.
The catalyst to realising these benefits and achieving return on investment will be the role of citizen scientists, which are not going to be statisticians, actuaries or so-called data gurus, but ordinary people with a passion for science and learning and a desire to contribute to solving the many grand challenges facing society at large.
I believe that their efforts will do more to turn the tide on societal and environmental challenges than all other undertakings combined.