Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

November 18, 2011

Big Data (Computing in Science and Engineering November/December 2011)

Filed under: BigData — Patrick Durusau @ 9:38 pm

Big Data (Computing in Science and Engineering November/December 2011 (vol. 13 no. 6) ISSN: 1521-9615)

A looks like theme issue on “big data.”

I say “looks like” because the “abstracts” for the articles are less informative than the titles of the articles on their own. I happened to be working while not logged into an account where I would just “see” the article with its actual abstract.

Let’s compare:

Data-Intensive Science in the US DOE: Case Studies and Future Challenges

Abstract not logged in:

Given its leading role in high-performance computing for modeling and simulation and its many experimental facilities, the US Department of Energy has a tremendous need for data-intensive science. Locating the challenges and commonalities among three case studies illuminates, in detail, the technical challenges involved in realizing data-intensive science.

You’re kidding, right? You are going to take ten pages to tell me the DOE needs “data-intensive science.”?

Abstract of the article when logged in:

Given its leading role in high-performance computing for modeling and simulation and its many experimental facilities, the US Department of Energy has a tremendous need for data-intensive science. Locating the challenges and commonalities among three case studies illuminates, in detail, the technical challenges involved in realizing data-intensive science.

Fortunately, I read the article after launching into this rant which allows me to make two points:

  1. The abstract sucks!
  2. The article is important!

How often does that happen?

Seriously. Three use cases are used to leave you with the feeling that current practices are going to look quite primitive in our lifetimes. Remember the first “bug” that was pasted onto a notebook page?

That’s the distance between now and the future of computing needed by the DOE.

Here is how I would do the abstract for the DOE article:

The DOE says: “Now for really Big Data!” Simulation data too big to store for analysis; what to keep, compress, throw away? Climate change, data about a world to share, analyze, and perhaps save. Real time experiments demand real time analysis, integrity and storage. Details inside.

OK, so mine is only two words (46 vs. 48) shorter than the one in the zine.

The DOE article really merits your attention, as do the others in this issue.

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