Inhalers that do more than dispense medication

Louisville, one of IBM's 100 selected selected cities is putting big data to work to track asthma triggers with Asthmapolis. Read about it in

Big Data's Next Target: Asthma

  

Big Data Health Hazards

If anything can go wrong, it will." Murphy's Law (or Sod's Law, as it is known in the UK) applies to big data projects, as well. When those projects concern someone's health, something going wrong in the data can lead to something going very wrong with the patient.

The more one relies on the accuracy of the system, the higher the potential for error. Electronic health records (EHRs) are considered a boon to data aggregation, but they hold a potential downside.  Read more here

Big Data and Cancer Research

That's the subject of my post Big Data Battles Cancer.  For a completely different take on cancer, see Beyond Pink.

Big Data Applied to Health

I've written several pieces on the topic from various angles:

On how cell phone data is used to map the spread of Malaria in order to come up with effective prevention in Africa Analyzing Cellphone Data for the Greater Good

On Retrofit's approach: Data Gets Personal to Fight Obesity

On UPMC $10 million dollar big data plan: Creating Custom-Fit Healthcare

Dial a data scientist

well, not exactly, but you can find one you can hire with Kaggle's new feature. Read more about it in my blog post: 

Top Data Scientists on Tap

Big data for voters

 Hurricane Sandy cut a devastating path through the Northeast, and many people are still without electricity, fuel, or shelter. They still had the right to vote, but what were they to do if their usual polling place was knocked out of commission? To find out where they should go, they were able to find answers in big data. Read more in Big-Data to Get Out the Vote

Thoughts on the Human Face of Big Data

See my blog post on the brand new board, Big Data Republic, Predicting People's Participation in a Big-Data Project

What do you think of pink?

Do you automatically buy anything that allies itself with "the cause?" There are reasons to think rather than blindly support all that is dressed in pink as discussed in http://uncommoncontent.blogspot.com/2012/10/beyond-pink.html

Predictive analytics for relationships

That's at the heart of Dr. John Gottman's approach, which he expands on in his latest book, What Makes Love Last? How to Build Trust and Avoid Betrayal. I wrote about that book  here.

I've written about his earlier work in several posts:

The ultimate marriage manual

 and the 4 part Marriage success between two earthlings 

Snoopy and Ozick: find out what they have in common

That's one of the cartoons featured in http://uncommoncontent.blogspot.com/2012/09/what-do-cynthia-ozick-and-snoopy-have.html

What would you include to represent 100 years of childhood?

See http://uncommoncontent.blogspot.com/2012/09/representing-100-years-of-childhood.html for thoughts on the MoMA's exhibit.

You can get your own Facebook Report

just bring along the salt shaker Read Your Personal Social Data, Visualized to understand why a few grains may be necessary when reviewing your stats.

IT and business don't always agree on big data

Not all decision makers within an organization are on the same page with respect to big data plans. The disparity is due to the different perspectives of the business and IT end of the organizations.

Read more: IT, business have different views on data - FierceBigData 

Analysis in light of the Pareto Principle

Many businesses who are not getting as much utility out of big data as they would like identify the source of the problem as their inadequate hardware, and inadequate finances. However, in a Smart Data Collective post, Paige Roberts argues that it's not the hardware, but the software that's to blame.

"Investing in better utilization of existing hardware is a far better, more sustainable, and cost-effective solution" for businesses who find their current setups inadequate. Roberts points to the inefficiency built into current "utilization rates of hardware [that] are around 15 percent worldwide." Even the most efficient data centers max out at only 20 percent, meaning that 80 percent is untapped.

Do those numbers ring a bell?

Read more: What's the real problem with the hardware? - FierceBigData

What do Long Island and Arlington, Texas have in common?

The answer is science. This topic was of particular interest to me because I've visited Brookhaven, one of the institutions involved in the partnership, multiple times. It's on Long Island, which, surprising, as that may be, actually has quite a history in connection with science as engineering, including the space program. 

Their goal is to extend the PanDA system for more general applications. Brookhaven and UT Arlington originally developed the workload management system to process the massive quantities of data involved in a component of the research of the Large Hadron Collider, or LHC.

Read more: Project aims to improve big data processing for science and engineering - FierceBigData http://www.fiercebigdata.com/story/project-aims-improve-big-data-processing-science-and-engineering/2012-09-11#ixzz26BQk146W