Cross-pollinating Web communities

Waterdrops inside The Animal Flower Cave, Barbados. By  Berit Watkin on Flickr.

Web projects are integration projects, combining skills from a number of disciplines. Lousy interfaces can obscure brilliant code, and ingeniously engineered back-end systems can still fail when they hit resource limits. “Content” lurks in many guises, requiring support not only from writers and illustrators but from video specialists, game designers, and many more. Marketers have built businesses on the Web, and influence conversations from design to analytics. You don’t have to be a programmer to do great work on the Web. The Web stack is vast.

Web development models include far more than code. Creating great websites and applications demands collaboration among content creators, designers, and programmers. As applications grow larger, supporting them requires adding a cast of people who can help them scale to demand. As projects grow, specialization typically lets people focus on specific aspects of those larger disciplines, supporting networking, databases, template systems, graphics details, and much more.

In some ways, that’s a recipe for fragmentation, and some days the edges are sharp. All of these communities have different priorities, which conflict regularly. Battles over resources sharpen the axes, and memories often linger.

At the same time, though, often even in environments where resources are scarce, different perspectives can reinforce each other or create new possibilities. Sometimes, it’s just because the intersection spaces have been left fallow for a long time, but other times, the combinations themselves create new opportunities.

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In design, what we really need is critical thinking


Download a free copy of Designing for the Internet of Things, a curated collection of chapters from the O’Reilly Design library. This post is an excerpt from Discussing Design, by Adam Connor and Aaron Irizarry, one of the books included in the curated collection.

One of the most common ways design discussions are initiated is for a team member to ask for feedback on something they’ve created or an idea they have. They might just grab someone at a nearby desk because they want to take a break from putting something together and think about what they’ve done so far. Or it could be part of a planned milestone or date in the project’s timeline, often called Design Reviews.

It’s not that either of these is a bad time to get other’s thoughts. Rather, the first real problem we encounter is from the word “feedback” itself. It’s a word that’s become engrained in our vocabulary. We use it all the time, a la “I’d love to get your feedback on something…”

What is feedback?

The issue with the term “feedback” lies in its broadness. Feedback itself is nothing more than a reaction or response. Designers talk about feedback and feedback loops all the time in their work. The user of a system or product interacts with it in some way, perhaps by clicking a button, and the system changes in one way or another. It could be that an animated loading bar appears while some new data is fetched and displayed, or maybe some elements in the interface move their position.

That reaction by the system is the feedback. It is the system’s response to what the user has done. Feedback is a reaction that occurs as a result of us doing something. In human-to-human interactions, such as the conversations we have in our projects, feedback can be nothing more than a gut reaction to whatever is being presented. And to be quite honest, even though we might not want to admit it, that’s often all it is.

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The next big thing sits between tech’s push and consumers’ pull


I recently sat down with Pilgrim Beart, co-founder of AlertMe, which he recently sold to British Gas for $100 million. Beart is a computer engineer and founder of several startups, including his latest venture 1248.

Identifying the gap between technology and consumers: How AlertMe was founded

I asked Beart about the early thinking that led him and his co founder, Adrian Critchlow, to create AlertMe. The focus seems simple — identify user need. Beart explained:

I co-founded AlertMe with Adrian Critchlow. He was from more of a Web services background … My background was more embedded technology. Over a series of lunches in Cambridge where we both lived at the time, we just got to discussing two things, really. One was the way that technology was going. Technology push — what changes were happening that made certain things inevitable, and also consumer pull. What were the gaps that technology wasn’t really addressing?

To some extent we were discussing at quite a high level the intersection of those two, perhaps not quite in that rational way, but as we talked about things we were interested in, that’s essentially what we were doing. We were triangulating between the technology push and the consumer pull, and trying to spot things that essentially would be inevitable because of those two things. Then that led us to thinking about the connected home platform and what could the killer apps for the connected home be, and isn’t it strange how, if you compare the home to the car for example, cars have a large number of computers in them, and the computers all work together seamlessly and invisibly to keep you safe, keep you secure, save you energy, and so on.

In the home, you have a similar number of computers, but they’re not talking to each other, and as a result, it’s really far from ideal. You have no idea what’s going on in your home most of the time, and it’s not energy efficient, it’s not secure, etc. We saw a huge opportunity there, and we saw the potential for some technological advances to help address those problems.

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Open source won, so what’s next?

OSCON 2014 show floor

Twenty years ago, open source was a cause. Ten years ago, it was the underdog. Today, it sits upon the Iron Throne ruling all it surveys. Software engineers now use open source frameworks, languages, and tools in almost all projects.

When I was putting together the program for OSCON with the other program chairs, it occurred to me that by covering “just” open source, we weren’t really leaving out all that much of the software landscape. It seems open source has indeed won, but let’s not gloat; let’s make things even better. Open source has made many great changes to software possible, but the spirit of the founding community goes well beyond code.

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5 reasons why Python is a popular teaching language

Download a free copy of Python in Education. Editor’s note: this is an excerpt from Python in Education, a free report written by Nicholas Tollervey.

I am going to answer a very simple question: which features of the Python language itself make it appropriate for education? This will involve learning a little Python and reading some code. But don’t worry if you’re not a coder! This chapter will hopefully open your eyes to how easy it is to learn Python (and thus, why it is such a popular choice as a teaching language).

Code readability

When I write a to-do list on a piece of paper, it looks something like this:

Fix broken gutter
Mow the lawn

This is an obvious list of items. If I wanted to break down my to-do list a bit further, I might write something like this:

Fix broken gutter:
    Borrow ladder from next door
    Find hammer and nails
    Return ladder!
Mow the lawn:
    Check lawn around pond for frogs
    Check mower fuel level

Intuitively, we understand that the main tasks are broken down into sub-tasks that are indented underneath the main task to which they relate. This makes it easy to see, at a glance, how the tasks relate to each other.

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Demand-Driven Innovation: An Integrative Systems-Based Review of the Literature

International Journal of Innovation and Technology Management, Volume 12, Issue 02, April 2015. In this paper, we provide a comprehensive review of the literature on demand-driven innovation, using a generic national innovation ecosystem map as a unifying framework. We organize the literature review around four key innovation dimensions and seven related demand-driven processes. Our review … Read more

Redefining power distribution using big data

power_distribution_alex.ch_FlickrWhen I first hear of a new open source project that might help me solve a problem, the first thing I do is ask around to see if any of my friends have tested it. Sometimes, however, the early descriptions sound so promising that I just jump right in and try it myself — and in a few cases, I transition immediately (this was certainly the case for Spark).

I recently had a conversation with Erich Nachbar, founder and CTO of Virtual Power Systems, and one of the earliest adopters of Spark. In the early days of Spark, Nachbar was CTO of Quantifind, a startup often cited by the creators of Spark as one of the first “production deployments.” On the latest episode of the O’Reilly Data Show Podcast, we talk about the ease with which Nachbar integrates new open source components into existing infrastructure, his contributions to Mesos, and his new “software-defined power distribution” startup.

Ecosystem of open source big data technologies

When evaluating a new software component, nothing beats testing it against workloads that mimic your own. Nachbar has had the luxury of working in organizations where introducing new components isn’t subject to multiple levels of decision-making. But, as he notes, everything starts with testing things for yourself:

“I have sort of my mini test suite…If it’s a data store, I would just essentially hook it up to something that’s readily available, some feed like a Twitter fire hose, and then just let it be bombarded with data, and by now, it’s my simple benchmark to know what is acceptable and what isn’t for the machine…I think if more people, instead of reading papers and paying people to tell them how good or bad things are, would actually set aside a day and try it, I think they would learn a lot more about the system than just reading about it and theorizing about the system.

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