Data Science and Computational Thinking [inc Big Data and Internet of Things]

Content mining of archival materials can make for amazing discoveries. Here's how to prepare for the coming influx of researchers who will want access to digital archives as a data source.

With scientists storing data in scores of different ways, Neurodata Without Borders provides a common format or “language” for brain data, beginning with neurophysiology -

An alliance of brain researchers and funders has announced a common data format to facilitate the free and open exchange of complex information about the brain—information that scientists can then use to accelerate progress in understanding the brain and developing new treatments for brain disorders.

The new format, known as Neurodata Without Borders (NWB): Neurophysiology, is the first widely available format that allows researchers to capture and share data generated by two of the most widely used methods in brain research: optical and electrical neurophysiology. A description of the format and its potential impact on the field of neuroscience is published in the journal Neuron.

By the late 2010s, glasses will beam images directly onto the retina. Ten terabytes of computing power(roughly the same as the human brain) will cost about $1,000.

By the 2020s, most diseases will go away as nanobots become smarter than current medical technology. Normal human eating can be replaced by nanosystems. The Turing test begins to be passable. Self-driving cars begin to take over the roads, and people won’t be allowed to drive on highways.

By the 2030s, virtual reality will begin to feel 100% real. We will be able to upload our mind/consciousness by the end of the decade.

By the 2040s, non-biological intelligence will be a billion times more capable than biological intelligence (a.k.a. us). Nanotech foglets will be able to make food out of thin air and create any object in physical world at a whim.

By 2045, we will multiply our intelligence a billionfold by linking wirelessly from our neocortex to a synthetic neocortex in the cloud.

I want to make an important point.

It’s not about the predictions.

It’s about what the predictions represent.

We all have a heart. Although we often take it for granted, it's our heart that gives us the moments in life to imagine, create, and discover. Yet cardiovascular disease threatens to take away these moments. Each day, 1,500 people in the U.S. alone are diagnosed with heart failure—but together, we can help. We can use data science to transform how we diagnose heart disease. By putting data science to work in the cardiology field, we can empower doctors to help more people live longer lives and spend more time with those that they love.

Declining cardiac function is a key indicator of heart disease. Doctors determine cardiac function by measuring end-systolic and end-diastolic volumes (i.e., the size of one chamber of the heart at the beginning and middle of each heartbeat), which are then used to derive the ejection fraction (EF). EF is the percentage of blood ejected from the left ventricle with each heartbeat. Both the volumes and the ejection fraction are predictive of heart disease. While a number of technologies can measure volumes or EF, Magnetic Resonance Imaging (MRI) is considered the gold standard test to accurately assess the heart's squeezing ability.

To some the Internet of Things is a very new idea: connecting up everyday objects to collect new streams of data -- and maybe even new streams of revenue too -- may seem a relatively recent trend.

But to others it's a continuation of work that's been going on under a different name for some time. IBM, for example, has been offering products and services based around tech conceptrs like ubiquitous and pervasive computing for years. Building on its previous work, earlier this year Big Blue decided to invest $3bn to set up a dedicated IoT unit.

In March, the company announced the new division, alongside a deal with The Weather Company and new products such as IoT Cloud Open Platform for industries, a vertical-focused analytics package, and additional IoT elements in its PaaS product Bluemix.