John & Ed,
Apart from questions related to history of the research field, "data science" as a name is shorter and easier to use (both in conversation and in writing) than "knowledge discovery and data mining", or even KDDM.
So it is inevitable, and perhaps a sign of importance and economic success for the field, that people would use a term like "data science", rather than KDDM.
One defect of the name "data science" is that it is very broad, like "computer science" or "information science". So as Ed states, some people may have used "data science" to refer to research in this area for many years, while as John states other more specific names have been used.
A broad name like "data science", can promote interaction by scientists with widely varying perspectives. Yet as John suggests, it can also lead to fragmentation as people focus on different research directions.
The term "data semantics" that John mentions from 1980 could be preferable to "data science" - concise, yet more specific. However, the die is cast. Researchers would probably prefer to be called data scientists, rather than data semanticists, anyway.
Clearly, it's important that people don't forget the progress and lessons learned from previous research in KDDM, or under related headings. Pragmatically, I'd be interested in forum members' answers to the following questions:
A) What theoretical or technical advances over the past 10 years have been important to data science, and to what extent are they not rediscoveries of progress made in earlier decades?
B) What theoretical or technical advances are most important to develop over the next 10 years, or 20 years, for data science?
> Date: Fri, 29 Aug 2014 13:23:15 -0400
> From: sowa@xxxxxxxxxxx
> To: ontolog-forum@xxxxxxxxxxxxxxxx
> Subject: [ontolog-forum] Looking to the Future of Data Science - NYTimes.com - 2014.08.27
> I'm moving this thread to Ontolog Forum, since it addresses a broad
> issue: How do we recognize legitimate subtopics, avoid endless
> fragmentation and duplication of effort, promote interdisciplinary
> collaboration, and help search engines find related documents?
> NY Times
> > The Association for Computing Machinery, a leading professional
> > association in computer science, is this week holding its annual
> > conference focused on what we're now calling data science - though
> > the ACM still clings to the label adopted when the yearly gatherings
> > began in 1998, Knowledge Discovery and Data Mining.
> > That's the fundamental principle for creating the illusion of progress:
> > Change the name of the field every decade.
> > I don't think that is fair. Anyone I know or knew in the field has long
> > thought that "data science" is the term for the computer science associated
> > with information management.
> If everyone knew that, why did they need another name? For that matter,
> note that the NYT reporter thought that 'data science' was a new name.
> > Into the early 1980s, the problem was always in getting the 'computer
> > science' gang (ACM in particular) to recognize that there was a computer
> > science aspect to information management systems
> ACM started TODS (Transactions on Data Systems) in 1976. In 1980,
> Ted Codd, Pat Hayes, John McCarthy, and other AI & DB people
> (including me) participated in an ACM-sponsored workshop that
> tried to promote more collaboration. Unfortunately, it tended
> to sound like separate conferences with interleaved talks.
> > I owe my respect for the data sciences to Stanley Y.W. Su at U. Florida
> > and Gio Wiederhold at Stanford.
> In the 1980s, I participated in IFIP WG 2.6 on database, along with Gio.
> The chair was Robert Meersman, who was trying to promoting collaboration
> among the DB and KB researchers. I helped organize some conferences on
> Data Semantics (which was treated as a topic, not a field).
> Among the speakers I invited were John McCarthy, Ray Reiter, and
> Roger Schank. One logician type turned down the invitation because
> it was "too applied". So we replaced him with Dana Scott.
> > This is not about renaming the field every 5 years; it is about
> > realizing that the field has a name.
> I have no objection to any term used as a title of an article, a book,
> or a conference. But when it is called a *field*, it tends to promote
> fragmentation rather than collaboration.
> > Unfortunately, beginning about 15 years ago, the real illusion of
> > progress -- XML and RDF data stores -- grew hundreds of would-be
> > computer scientists building "new" information stores and database
> > systems, with no knowledge of the data sciences, and therefore
> > reinventing good and bad ideas from a 30-year literature they didn't read.
> I'm happy to end on a point I can strongly agree with.
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