Preregistration For Data Science? – Neuroskeptic | DiscoverMagazine.com

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In a post on the issue of preregistration in science, statistician and political scientist Andrew Gelman writes (my emphasis) that: I support proposals in

Carla Gentry CSPO‘s insight:

In the worst case scenario, everyone would cheat in this way, and only results that are liked would see the light of day.

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Dark Data & The Data Disconnect – Eric D. Brown

See on Scoop.itWhat is Data Science

Dark Data can arise in many ways. One way is via Shadow IT and the Data Disconnect

Carla Gentry CSPO‘s insight:

Your data might remain in that vacuum. But worse…whatever knowledge that data might create (or has created) will remain in that vacuum as well.

See on ericbrown.com

IT Language Lessons « The Dark Side Geek

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Carla Gentry CSPO‘s insight:

It is far more appropriate for finance to be an attribute to consider – one of many, not necessarily a bottom line – in pursuit of a goal. If the objective is cost reduction, then obviously finance plays a major role. But maybe the key objective is security of intellectual property. Or improving communication and collaboration. Or a desire to “eat our own dog food” as a customer showcase. I’ve been in many such situations where finance was hardly a foundational language. In some cases, even the very mention of financial issues during discussions with our business partners resulted in claims that we weren’t listening.

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One Page R: A Survival Guide to Data Science with R

See on Scoop.itData Nerd’s Corner

From Togaware.

Many of the documents have been developed and tested whilst visiting the Shenzhen Institutes of Technology as an International Visiting Profess…

Carla Gentry CSPO‘s insight:

Many of the documents have been developed and tested whilst visiting the Shenzhen Institutes of Technology as an International Visiting Professor of the Chinese Academy of Sciences. The data used is available for download as data.zip.

See on www.datasciencecentral.com

Why is math research important?

Love it!

mathbabe

As I’ve already described, I’m worried about the oncoming MOOC revolution and its effect on math research. To say it plainly, I think there will be major cuts in professional math jobs starting very soon, and I’ve even started to discourage young people from their plans to become math professors.

I’d like to start up a conversation – with the public, but starting in the mathematical community – about mathematics research funding and why it’s important.

I’d like to argue for math research as a public good which deserves to be publicly funded. But although I’m sure that we need to make that case, the more I think about it the less sure I am how to make that case. I’d like your help.

So remember, we’re making the case that continuing math research is a good idea for our society, and we should put up some money towards it…

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Math professor joins New York Times as chief data scientist | Columbia Daily Spectator

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Carla Gentry CSPO‘s insight:

“It’s a very exciting time to rethink what journalism is going to look like over the next 100 years,” Wiggins said, mentioning Amazon founder Jeff Bezos’ purchase of the Washington Post last year. “I really believe that journalism is really important to the functioning of a healthy democracy, and it’s being challenged right now because the central business of the past 200 years has evaporated.”

See on www.columbiaspectator.com

Carla Gentry | Data Science Expert View | Kalido

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Carla Gentry CSPO‘s insight:

What is a data scientist?

Data science has been around for decades, and it’s not just big data. I hear a lot of people clumping these two together like they go hand-in-hand, which I agree with to an extent. However, big data needs data science but data science doesn’t necessarily need big data. Most of the data a typical company handles on a daily basis or house internally is not big data. Even Facebook and Google break up or segment their data into workable pieces.

See on www.kalido.com

National Consortium for Data Science White Paper Points to Challenges and Solutions for Genomics in the Age of Big Data

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A new public-private consortium aimed at advancing data science brings together data and genomics researchers to discuss the data challenges in genomics. This white paper summarizes their discussions.

Carla Gentry CSPO‘s insight:

The white paper, titled Data to Knowledge: Genomes to Health, resulted from the first NCDS Leadership Summit, held last April in Chapel Hill, NC. The summit brought together researchers in genomics and data science to discuss the greatest data challenges in genomic sciences and to brainstorm on possible solutions to those challenges. About 70 leaders in their fields attended the summit and identified the genomic science data challenges in the areas of data provenance, collection and management, delineation of phenotypes, adjudication of genomic variants, biostatistics and bioinformatics, data sharing, and ethics and the law.

See on www.newswise.com

Predictive analytics: You don’t need to be a data scientist to get ahead

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The race to harness the growing volumes of data for a competitive edge is putting increased strain on skills and resources within businesses, and…

Carla Gentry CSPO‘s insight:

What will be required from the workforce of tomorrow is a balance of skills, not just academic. All employees in the future will need to demonstrate curiosity, creative flair, and the ability to visualise and to communicate clearly with non-technical people throughout the business. Educational institutions can provide the knowledge and certifications but it is also important for the industry to work more closely with schools and universities to develop the workforce of tomorrow and ensure they have the right balance of skills for entering the modern workplace.

See on www.itproportal.com

The promise of ‘big data’

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Harvard symposium embraces the goals and challenges of collecting and processing massive amounts of information on key complex issues.

Carla Gentry CSPO‘s insight:

The information filtered by this system does not constitute “big data” on the scale of Facebook or Google, Ray noted, but “it’s too much for a human to do, and it is having a real impact on the lives of Ugandans.”

As computing power allows nonprofits, businesses, and researchers to gather ever-larger troves of information, new challenges arise, such as those involving privacy and security. (As Google research scientist Diane Lambert noted, “If you’ve ever put a query into Google, then you’ve been in an experiment.”)

See on news.harvard.edu