Data Science: Early & Modern History

Before we begin, let’s loosely define Data Science for convenience.

What is Data Science?

Data Science is

● an interdisciplinary concept,

● which uses any scientific methods,

● combines it with computing,

● to produce insights,

● from data.

But why ‘Data Science’? Who used that term first? Where did it all begin? Well, let’s find out.

“The temptation to form premature theories upon insuf icient data is the bane of our profession.”
— Sherlock Holmes (from the Valley of Fear, by Sir Arthur Conan Doyle)

Early History

To predict an outcome from previous data has always been crucial in war, trade expeditions, or medical diagnosis; first done by instinct, then by experience and evermore through the field of Statistics. But it was only in 1962 that John Tukey described what he called “Data Analysis”. And in 12 short years, in 1974, Peter Naur proposed the term “Data Science” as an alternative to computer science, later used by C.F. Jeff Wu in a lecture as an alternative to statistics.

And hence the emergence of one of the most influential disciplines in computer science began!

● In 1992 the University of Montpellier II acknowledged Data Science as a new discipline at a statistics symposium, which combined the concepts and principles of statistics and data analysis with computing.

● And in 1996, the International Federation of Classification Societies featured Data Science as an independent topic.

“Every company has Big Data in its future, and every company will eventually be in the data business.”
— Thomas Hayes Davenport

Now, most of us would think that that’s it to the story, Data Science was defined, and everyone agreed and understood what it was, right? But with something as complex and interdisciplinary as Data Science, the discussion rarely ends!

In 1997 C.F. Jeff Wu again suggested renaming Statistics as Data Science, reasoning that a new title would erase stereotypes. But in 1998, Hayashi Chikio advocated for Data Science as a new, interdisciplinary concept with three aspects: data design, collection and analysis. There are many more Modern aspects to the fascinating history of Data Science, and we will cover those in the after articles.

Modern History

The Modern history of our favourite discipline is just as vivid as the Early history, sometimes even more so than the latter!

Our story starts with one of the big names in Data Science, William Swain Cleveland II, professor of Statistics and Computer Science at Purdue University.

Prof Cleveland is credited for defining and naming Data Science in a 2001 publication. It advocates the advance of Statistics beyond the domains of theory and into the technical aspects of the real world!

Thus, the name “Data Science” became widely used, and many noteworthy things happened in the upcoming years, such as

2002 — Data Science Journal launched by the Committee for Data Science and Technology
2003 — The Journal of Data Science established by the Columbia University
2014 — Statistical Learning and Data Mining section of the American Statistical Association renamed as Section on Statistical Learning and Data Science

The title of the Data Scientists

Although in 2008, the title of “Data Scientist” as a professional have attributed to DJ Patil and Jeff Hammerbacher. In 2005, “Data Scientist” was a title used by the National Science Board in the report “Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century”. In the report, “Data Scientist” was a broader term for anyone with a role in digital data collection.

Sexiest Job of the 21st Century!

It was 2012, and a catchphrase was given to our favourite discipline and became a sensation. Technologists DJ Patil and Thomas H. Davenport declared “Data Scientist: The Sexiest job of the 21st Century”.

Even newspapers such as the New York Times and Boston Globe used the term. And a decade later, they reaffirmed that the job is as popular as ever with employers!

The role of the Data Scientist is to use the data to find solutions and help make the best decisions.

Well, it’s been an enthralling journey, the definition of Data Science is still a topic of debate among scholars, and for now, it is just a buzzword and a little more.

I hope I can make you see that the scope and domain of Data Science are extensive, and disputes still happen to define it.

Data Science overlaps with several fields of Statistics, Artificial Intelligence and many more applied sciences, and the lines can get blurry sometimes, making exploring even more exciting!