The coming data explosion and what this means for employable skills

AI Thread Summary
The discussion centers on the evolution of scientific discovery, highlighting the transition from traditional paradigms of experiment and theory to data-intensive methodologies. Recent advancements allow programs to derive physical formulas from large datasets, challenging conventional scientific methods. Key skillsets for the future include proficiency with advanced sensors, data mining, and pattern recognition, which are expected to be highly employable. The conversation emphasizes the importance of interdisciplinary collaboration due to the overwhelming volume of data, suggesting that effective communication and the ability to distill complex information into concise summaries are crucial skills. The relevance of fields like astrophysics and bioinformatics is noted, with the assertion that the ongoing data revolution impacts all scientific disciplines. Additionally, the discussion points out that while data generation has accelerated, bottlenecks exist in software and social systems, which are essential for contextualizing data meaningfully.
Simfish
Gold Member
Messages
811
Reaction score
2
http://www.nytimes.com/external/rea...writeweb-the-coming-data-explosion-13154.html

An interesting book:
http://research.microsoft.com/en-us/collaboration/fourthparadigm/

So basically, the two main paradigms used to be experiment and theory. Then in the 1950s came simulations, and now we have data-intensive scientific discovery. Some people have recently written programs that can derive physical formulas from massive amounts of data. Such methods can produce true results without an a priori basis for scientific discovery, which runs counter to the scientific method.

==

Anyways, so I'm seeing that there are several skillsets that will become valuable quite soon. (a) working with better sensors that have additional dimensions of physical data, (b) data mining/pattern recognition, (c) finding ways to efficiently analyze mass amounts of physical data, (d) intuition with respect to finding patterns out of massive datasets (or finding algorithms that find the best patterns out of them)

So the question here, is, do you see these skillsets as extremely employable in the near future (perhaps more employable than many other skillsets)? And what would people look for if they look for people with such skillsets?

For instance, I would like to go for a PhD in astrophysics. Astrophysics, of course, is one beneficiary of this revolution, as we get better sensors (telescopes/CCDs) and massive amounts of data to analyze. But I have many scientific interests, and I'm especially interested in other applications of this upcoming revolution (especially as it applies to the biological sciences, which are also in the process of an upcoming revolution - this revolution may depend on training different from the types of training biologists have traditionally received). Anyways, would people in other fields be convinced that astrophysics would provide me with the skills to go into this?
 
Physics news on Phys.org
Simfish said:
So the question here, is, do you see these skillsets as extremely employable in the near future (perhaps more employable than many other skillsets)? And what would people look for if they look for people with such skillsets?

Learn to problem. If you are good at programming computers, it's like being about to read English. Also study history and philosophy. Technology changes quickly, but humans change rather slowly, and in looking at patterns, it's a good idea to look at human patterns.

Also, it's not a "coming revolution" it's a current one.

For instance, I would like to go for a PhD in astrophysics. Astrophysics, of course, is one beneficiary of this revolution, as we get better sensors (telescopes/CCDs) and massive amounts of data to analyze.

One thing about the massive amounts of data is that it's much too much for anyone human being to understand, so a lot of dealing with complex problems involves having cross-disciplinary teams. Just find a subject that you like and go with it.

The other thing is to develop basic communications and education skills. One key skill is to be able to take several exabytes of data and summarize it all in two sentences. You need a human to do that.

Anyways, would people in other fields be convinced that astrophysics would provide me with the skills to go into this?

A lot of what matters is to be able to give someone the key google term that they need. The word you are looking for is "bioinformatics." In any event, because computers are touching everything, what field you go into isn't that important since they are all getting hit by cheap computer power, and a lot of the basic techniques are field independent.
 
Simfish said:
So basically, the two main paradigms used to be experiment and theory. Then in the 1950s came simulations, and now we have data-intensive scientific discovery. Some people have recently written programs that can derive physical formulas from massive amounts of data. Such methods can produce true results without an a priori basis for scientific discovery, which runs counter to the scientific method.

How is this qualitatively different from, say, Kepler's Laws of planetary motion? His laws were derived from observation, without regard to theory, model or explanation.
 
DaveC426913 said:
How is this qualitatively different from, say, Kepler's Laws of planetary motion? His laws were derived from observation, without regard to theory, model or explanation.

It's really not, except that now we have power tools rather than hand tools. Kepler took 19 years to figure out his three laws. What he did could be done by modern computers in about an hour.

The amount of data and hardware out there is incredibly but the bottle necks are the software and the social systems. Data is useless without a social context to make sense out of it.
 
twofish-quant said:
The amount of data and hardware out there is incredibly but the bottle necks are the software and the social systems. Data is useless without a social context to make sense out of it.
Yep. That is the central theme of Web 2.0 the Semantic Web initiative, and why HTML5 has been released with all sorts of new features to enable semantic interpretation.
 
I don't know if anyone on here works for any of the well known defense companies of your country, whichever country you are from?? Also, if you choose to work in one, do you think the engineering education provide from your school would adequately prepare you for the job. What do I mean by that? Well if you work at say Lockheed Martin and you work in the latest iteration of a missile or if you work at Pratt & Whitney, they assign you to work in the team helping out with building the jet...
Hello, I graduated from undergrad a few years ago with a Major in Physics and minor in Electrical Engineering. I tried to get experience working on and testing circuits through my professor who studied Neutrinos, however covid caused the opportunity to go away and I graduated with no experience or internships. I have attempted to break into the engineering industry with no success. Right now I am considering going for a Masters in Electrical Engineering and I need advice on if this would be...
So lately, my interest in the realm of optics/optoelectronics/photonics engineering has grown and I have started to seriously consider pursuing a career in the field. I have done a bit of career research and also have done some learning on the side to gather more knowledge on these topics. However, I have some questions on what a career in these fields would look like, and I wanted to find out more about this area to know what I would be getting myself into if I did make the choice to pursue...

Similar threads

Replies
29
Views
7K
Replies
18
Views
3K
Replies
2
Views
3K
Replies
108
Views
18K
Replies
11
Views
4K
Replies
19
Views
5K
Replies
4
Views
3K
Back
Top