software engineering

See the following -

How Can Open Source Projects Support Themselves in Health Care?

High prices and poor usability hasn't driven the health care industry away from megalithic, proprietary applications. What may win the industry over to open source (in addition to the hope of fixing those two problems) is its promises of easy customization, infinite flexibility, extensibility, and seamless data exchange. As we will see, open platforms also permit organizations to collaborate on shared goals, which appeals to many participants. But if open source projects can't charge hundreds of thousands of dollars for installation as their commercial competitors do, how will they pay their developers and hold together as projects? This article compares three major organizations in the open source health care space: the tranSMART Foundation, Open Health Tools (OHT), and Open mHealth. Each has taken a different path to the universal goal of stability.

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Open Source Enlightenment Needed to End 'Dark Ages' of Health IT

Tony Shannon | Digital Health | January 11, 2017

Your article - "Whatever happened to Open Source in 2016?" highlights the brief vogue that open source recently enjoyed in the NHS – 2014-15 – and now seems to have lost. It raises some good questions and important issues, though I sense some broader perspective may be worth adding here. It’s worth remembering that healthcare is a well-established science – the first medical school established in the 9th century.  While information technology is still a young science – the first MSc in software engineering dates from 1979...

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The Man Who Would Build A Computer The Size Of The Entire Internet

Cade Metz | Wired | September 9, 2013

[...] Inside the massive data centers that drive things like Google Search and Gmail and Google Maps, you’ll find tens of thousands of machines — each small enough to hold in your arms — but thanks to a new breed of software that spans this sea of servers, the entire data center operates like a single system, one giant computer that runs any application the company throws at it. Read More »

Why Data Scientists Love Kubernetes

Let's start with an uncontroversial point: Software developers and system operators love Kubernetes as a way to deploy and manage applications in Linux containers. Linux containers provide the foundation for reproducible builds and deployments, but Kubernetes and its ecosystem provide essential features that make containers great for running real applications...What you may not know is that Kubernetes also provides an unbeatable combination of features for working data scientists. The same features that streamline the software development workflow also support a data science workflow! To see why, let's first see what a data scientist's job looks like...

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