What I’m Reading on 08/28/2014

  • “Experiences like those two are becoming common at campuses around the country, as students are showing up the universities that trained them by producing faster, easier-to-navigate, more informative and generally just better versions of the information systems at the heart of undergraduate life.”

    tags: bs apps colleges

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What I’m Reading on 08/27/2014

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What I’m Reading on 08/25/2014

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What I’m Reading on 08/22/2014

  • “Open Data Kit (ODK) is a free and open-source set of tools which help organizations author, field, and manage mobile data collection solutions.”

    tags: bs data open

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What I’m Reading on 08/07/2014

  • “One of those is the possibility to use Swift as a general OS “scripting” language – instead of bash, PyObjC or C or any other option that you might have opted for in the past. Moreover, you can do that entirely from outside of XCode – so write your Swift program in any editor and then simply use Terminal to execute it, as if it was pure script.”

    tags: bs swift

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What I’m Reading on 08/06/2014

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What I’m Reading on 08/01/2014

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What I’m Reading on 07/27/2014

  • “The Ruby language is 21 years old. Its strong community and adoption by the open source community has kept this language steady and improving. Ruby has changed drastically over the years. It has grown from a young child to the strong adult that it is today. But it didn’t get that way overnight. Let’s take a look at the life of the Ruby programming language.”

    tags: bs history ruby

  • “Enter Scrivener.  This program, produced by a company called Literature and Latte, was designed specifically for writers who are writing long documents like novels and movie/play scripts.  It is available for Windows, Mac, and LInux, and comes with a thirty day free trial. I have been using Scrivener to write my novels for about a year now, and I have to say it has made writing my novel sooooo much easier.”

    tags: bs novel writing scrivener

  • “One of the first things we like to talk about when you’re going to learn how to get into a kayak is keep in mind that more people tip over at the dock – getting either in or out – more than any other place on the water itself. We have a tendency to be overconfident about the fact that we should be able to get into a kayak with no problem.”

    tags: bs kayak dock

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What I’m Reading on 07/26/2014

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What I’m Reading on 07/24/2014

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What I’m Reading on 07/22/2014

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Supermoon over the Adirondacks

The Supermoon over Cranberry Lake, New York, in the New York Adirondack Mountains on 11 July, 2014.

Supermoon of Cranberry Lake, NY, on July 11, 2014, in the NY Adirondack Mountains.

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What I’m Reading on 07/16/2014

  • “This page attempts to collect information and links pertaining to the practice of AI and Machine Learning in python.”

    tags: bs python AI

  • “This app ranks the popularity of dozens of programming languages. You can filter them by listing only those most relevant to particular sectors, such as web or embedded programming. Rankings are created by weighting and combining 12 metrics from 10 sources. We offer preset weightings for those interested in what’s trending or most looked for by employers, or you can take complete control and create your own custom ranking by adjusting each metric’s weighting yourself. “

    tags: bs programming languages ieee

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IBM and Apple mobile announcement: important links

Yesterday IBM and Apple made an important announcement about partnering to significantly growth the use of mobile via Apple devices in the enterprise. That is, the collaboration will significantly increase the functionality and value that mobile brings to people in their jobs.

Here are some of the most important links about this announcement.

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What I’m Reading on 07/15/2014

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What I’m Reading on 07/13/2014

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What I’m Reading on 07/11/2014

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What I’m Reading on 07/10/2014

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What I’m Reading on 07/09/2014

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What I’m Reading on 07/07/2014

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What I’m Reading on 07/03/2014

  • “Maxima, a full featured computer algebra system, now runs on your Android mobile devices. Maxima, and its predecessor Macsyma is one of the most long-established software in the world, back in 1960s at MIT LCS and Project Mac. You can perform many many math operations such as integration, differentiation, matrix operations, rational numbers, symbolic treatment of constants such as pi, e, euler’s gamma, symbolic and numerical treatment of special functions such as sin(x), cos(x), log(x), exp(x), zeta(s), and many more.”

    tags: bs android maxima

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On tools

Having a collection of fewer high quality tools is better than having many cheap, inaccurate ones that won’t last long and may be dangerous.

When I was young, I couldn’t afford very good tools. I’m not talking about software here, I’m referring to things like power saws and kitchen pots. I bought them as I needed them, but they were never top end. Over time, I replaced them all.

The problem with cheap tools is that they often do not work very well and they don’t last very long. Other than that, they’re great! (grin) Inexpensive screwdrivers twist and lose the shape of their tips, for example.

Take the power saw. Cheaper models do not have the power and often the precision to do the job right. Yes, they may be better than a hand saw but your work may be sloppy and inaccurate. That hand saw? Cheaper models may not be made of high quality wood and the metal may be be too thin, so it will wobble when you make a cut. It will likely dull faster as well.

In the kitchen, inexpensive knives will also dull quickly and may end up being downright dangerous. With any tool, cheap or otherwise, you need to know how to use it safely so that it will at least not be ignorance that caused the nicked finger, knuckle, or worse.

So while it is nice to say “buy better, more expensive tools,” that doesn’t solve the problem of affordability. Borrowing tools may work, but better from a relative than a friend. Better yet is having a skilled relative with good tools to help you!

Plan your strategy of getting good tools over time, and spend more sooner on the really important things you need. Start by thinking about what you will be using frequently.

For household work, construction, and carpentry, spend extra as soon as you can on screwdrivers, pliers, and tape measures. You can do a lot with an accurate electric saber saw and a square. Get the best quality cordless drill and drill bits you can afford.

For cooking, begin with the knives. You don’t need many of them, just a few very good ones. Don’t splurge on measuring spoons and cups since inexpensive ones are often good enough. Get a good Dutch oven sooner rather than later. Favor fewer stick-free pots and pans with new, high quality coating rather than a set of cheap pots. Sets can be cheaper, but you can also build up your collection piece by great piece as you have the money.

As a final suggestion, tools often come in three price ranges: inexpensive, moderate, and very expensive. If you know nothing else, go for the moderately priced tools. That said, do your research.

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What I’m Reading on 07/01/2014

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What I’m Reading on 06/30/2014

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What I’m Reading on 06/26/2014

  • “Back in the day, I used to look at a recipe that called for boiling something destined for the grill and think “What? Why cook it twice? Will there be any flavor left?” The answer for many foods turned out to be a resounding “Yes.” Parboiling can actually add flavor, plus speed your grilling time, reduce flare-ups and increase moisture and tenderness. Best of all, it can take a lot of guesswork out of that eternal question “Is it done yet?””

    tags: bs foods

  • “PixelCut today released PaintCode 2.1, adding support for the new Swift programming language to its popular developer tool. PaintCode is a unique vector drawing app that generates Objective-C or Swift code in real time, acting as a bridge between developers and graphic designers. With PaintCode, developers can create an app that is truly resolution-independent, using code (instead of a large number of image assets) to draw a user interface. PaintCode has been successfully adopted by numerous developers, including industry giants such as Apple, Disney Pixar, Twitter, Dell, Hewlett Packard and Evernote.”

    tags: bs swift

  • Google wants to be everywhere: In your home, your car and even on your wrist. That vision became increasingly clear at the search giant’s annual conference for software developers here on Wednesday. The company unveiled plans to expand Android, its mobile operating system, for new categories like wearable computers and automobiles.”

    tags: bs google android

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What I’m Reading on 06/23/2014

  • “Due to its early success and/or promise, Wink is about to become its own company, according to the New York Times. The company’s main technology is software that works like an operating system to connect all of your automated home devices. With the tap of Wink’s mobile app, a user is able to configure everything from a light that turns on when you walk in the door to security system settings. As a companion, Wink has just developed a hardware hub, so that devices that operate on Bluetooth, ZigBee and Z-Wave, rather than Wifi, can also connect to Wink.”

    tags: bs hub iot

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What I’m Reading on 06/20/2014

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What I’m Reading on 06/19/2014

  • Apple isn’t upgrading the iMac family today, but it is making the family a little bigger. The company is now offering a new $1,099 entry-level model that includes most of the perks of the 21.5-inch model introduced last year—the same unibody aluminum enclosure, 1080p screen, port layout, 8GB of RAM, and 802.11ac Wi-Fi adapter—but takes a significant step backward with CPU and GPU speed.”

    tags: bs apple imac desktop

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What I’m Reading on 06/18/2014

  • Apple seeded iOS 8 beta 2 to registered developers today with a number of new features and stability enhancements. The new iOS 8 beta 2 build, labeled 12A4297e, marks the return of the dedicated Podcasts app and a Safari feature that blocks ads from automatically redirecting to the App Store. Safari also includes a new pinch to tab view.”

    tags: bs ios beta

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What I’m Reading on 06/17/2014

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What I’m Reading on 06/13/2014

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What I’m Reading on 06/11/2014

  • “If you own an iPhone and a Mac, Apple‘s new system for connecting the two is one of the best new features for OS X 10.10 Yosemite. True, Apple is years behind Google when it comes to making and taking phone calls from the computer, but its better-late-than-never approach gives the company two big advantages over Google’s system: the fact that it easily syncs with your phone, and that it’s part of a tightly-integrated system that goes beyond making calls.”

    tags: bs macs os x yosemite iphone

  • “In an exciting collaboration with Mozilla and Google, Intel is bringing SIMD to JavaScript. This makes it possible to develop new classes of compute-intensive applications such as games and media processing—all in JavaScript—without the need to rely on any native plugins or non-portable native code. SIMD.JS can run anywhere JavaScript runs. It will, however, run a lot faster and more power efficiently on the platforms that support SIMD. This includes both the client platforms (browsers and hybrid mobile HTML5 apps) as well as servers that run JavaScript, for example through the Node.js V8 engine.”

    tags: bs javascript simd graphics

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What I’m Reading on 06/10/2014

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What I’m Reading on 06/09/2014

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What I’m Reading on 06/07/2014

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What I’m Reading on 06/06/2014

  • “This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses.”

    tags: bs python programming mit

  • “The general consensus from developers appears to be that Swift is a great programming language. Swift is similar in many ways to Python, another highly-regarded programming language. Swift should be a much easier programming language for newcomers to pick up than Objective-C. Python is regularly used as the language of choice for programming classes, so many programmers may already be familiar with much of the Apple Swift syntax.”

    tags: bs swift python

  • “That’s where Swift comes in. Described as a fast and modern solution designed for safety, Swift is faster than Objective-C or Python and “allows a level of interactivity never before seen on the platform” thanks to its support for “playgrounds” that allow developers to visualize Swift code in real-time within the Xcode developer environment. That means developers are able to see what an app looks like before they’re even finished coding it.”

    tags: bs swift apple programming language

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What I’m Reading on 06/05/2014

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What I’m Reading on 06/03/2014

  • “Swift is a new programming language for creating iOS and OS X apps. Swift builds on the best of C and Objective-C, without the constraints of C compatibility. Swift adopts safe programming patterns and adds modern features to make programming easier, more flexible, and more fun. Swift’s clean slate, backed by the mature and much-loved Cocoa and Cocoa Touch frameworks, is an opportunity to reimagine how software development works.”

    tags: bs apple swift programming books

  • “Swift seems to get rid of Objective C’s reliance on defined pointers; instead, the compiler infers the variable type, just as many scripting languages do. At the same time, it provides modern features similar to those found in C++ and Java, like well-defined namespaces, generics, and operator overloading. From the few fragments of code shown during the demo, Swift appears to rely heavily on the dot-notation that Apple introduced in an earlier iteration of Objective C.”

    tags: bs apple swift programming language

  • “Apple took the wraps off of the latest version of OS X on Monday. In many ways, Yosemite is to Macs what iOS 7 was to iPhones and iPads—it didn’t drastically reinvent the Mac’s user interface, but its design is a fairly drastic break from the last decade or so of interface updates.”

    tags: bs desktop os x apple

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What I’m Reading on 05/28/2014

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What I’m Reading on 05/27/2014

  • “There’s a new advantage to doing business in New York. A big one. START-UP NY, Governor Cuomo’s groundbreaking initiative, is transforming communities across the state into tax-free sites for new and expanding businesses. Now, businesses can operate 100% tax-free for 10 years. No income tax, business, corporate, state or local taxes, sales and property taxes, or franchise fees.”

    tags: bs startup ny

  • “This is a list of the best books for learning the python programming language.”

    tags: bs python books

  • “Memo to anyone who logs in to a WordPress.com-hosted blog from a public Wi-Fi connection or other unsecured network: It’s trivial for the script kiddie a few tables down to hijack your site even if it’s protected by two-factor authentication.”

    tags: bs wordpress

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What I’m Reading on 05/26/2014

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What I’m Reading on 05/24/2014

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What I’m Reading on 05/22/2014

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What I’m Reading on 05/21/2014

  • “Atom, GitHub’s new open source text editor, was designed to steamroll over the old way of doing things. You use modern conveniences instead of fighting the text editor—for instance, you customize it with a graphical user interface (GUI)—so you can focus on your code alone. In short, it’s a text editor designed with beginners and amateur developers in mind.”

    tags: bs github atom editor

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What I’m Reading on 05/20/2014

  • “The power of wearables is to make the invisible visible. To show us what’s really happening around us. The last time I felt this way about a device was Fitbit. Seeing how you actually move during the day, versus what you think, is a profound realization, and Fitbit has motivated the world to move more and remember activity as the key to wellness. Perhaps the Clip’s power is similar. Perhaps through vivid memories and moments, we can become more present, more aware and yes, more happy.”

    tags: bs camera wearable

  • Microsoft Corp. MSFT -0.42% introduced a larger-screen version of one of its Surface tablet computers, offering a lighter and thinner device Microsoft touted as a potential replacement of existing laptops.”

    tags: bs microsoft surface tablet

  • “As virtual reality gains steam, the question of virtual worlds is never far behind. Philip Rosedale is best known for online community Second Life. But since last year, we’ve been watching for news on High Fidelity, a new project meant to blend his previous work with cutting-edge telepresence technology. The system, announced in 2013, was compared to the OASIS of Ready Player One: a series of worlds connected to each other by a central network and economy, provided — obviously — by Rosedale himself. At the Silicon Valley Virtual Reality Conference in Mountain View, we’re seeing the first hints of what that could mean, as well as a sense of the many hurdles left to jump.”

    tags: bs v inside fidelity

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What I’m Reading on 05/18/2014

  • “Some users who updated their Macs to OS 10.9.3 yesterday are reporting that their Users folder has disappeared. Like the name suggests, the Users folder holds all of the folders for a given computer, and something about yesterday’s update could cause it to hide itself for some.”

    tags: bs mac users folder

  • “And then there are the real fanatics – the Dylan obsessives who dig in the singer’s trash, buy the high chair he used as a baby and crash his sons’ bar mitzvahs. It’s those devotees who are the subject of The Dylanologists: Adventures in the Land of Bob, a new book by Pulitzer Prize–winner David Kinney examining the well worn legacy of rock & roll’s biggest enigma through the theories and fixations of his most devoted zealots.”

    tags: bs Bob Dylan music

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What I’m Reading on 05/16/2014

  • “The news today at Bloomberg  is that Rackspace has hired Morgan Stanley to look at “strategic options” for the future. Rackspace has long been something of a bridesmaid in the cloud infrastructure space. Previously dwarfed by the number one player, Amazon Web Services, the San Antonio-based company now has to contend with some very strong cloud infrastructure plays from others including Microsoft MSFT -1.54%, Google GOOGL -1.02% and IBM – all companies with far bigger footprints, and deeper pockets than it has.”

    tags: bs cloud

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What I’m Reading on 05/13/2014

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What I’m Reading on 05/11/2014

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What I’m Reading on 05/10/2014

iOS Development

General

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What I’m Reading on 05/02/2014

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Photo: Some books for work and interests

Works for work and interests

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What I’m Reading on 05/01/2014

  • “That’s all well and good, but hypervisor support takes up a lot of system resources — every VM runs not merely a full copy of an operating system, bur a virtual copy of all the hardware that operating system needs to run. That’s great for using otherwise unused memory or CPU cycles, but say you’re running multiple VMs and your users want more VMs — more I tell you! — then the fact that these fat VMs take up a lot of RAM and clock time starts to be troublesome. That’s where containers (a different take on virtualization) comes in.”

    tags: bs containers virtualization linux

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What I’m Reading on 04/30/2014

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What I’m Reading on 04/27/2014

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APIs and SDKs for Wearables

Wearables are the hot new thing, though the market is still shaping up. Nike has already exited the hardware part of the business. Here are some public descriptions of APIs and SDKs for wearables that could be used for mobile apps or other applications. Some of the APIs may be for the phones/tablets, some might be for the wearables.

APIs and SDKs

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What I’m Reading on 04/25/2014

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What I’m Reading on 04/24/2014

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What I’m Reading on 04/23/2014

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What I’m Reading on 04/21/2014

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What I’m Reading on 04/19/2014

  • “Johnny Depp, who’s built a brilliant career despite many of his lamentable film choices, may not be the first actor you think of to play a genius – much less humanity’s destroyer or savior. But he’s weirdly perfect in “Transcendence,” an inelegant, no doubt implausible (maybe not) science-fiction film about a futurist whose consciousness is uploaded onto the Internet. “

    tags: johnny depp transcendence nytimes bs

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What I’m Reading on 04/10/2014

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What I’m Reading on 04/05/2014

  • “For over eight years, ProgrammableWeb has served as the Web’s defacto journal of the API economy; offering news, advice, API directories, research data, and other information when it comes to the world of Internet-based APIs. Now, as a part of our continuing mission to serve as the world’s leading resource for developers, API providers and stakeholders, we’re announcing the the launch of ProgrammableWeb’s first-ever face-to-face conference; APIcon.”

    tags: bs api conference developers

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What I’m Reading on 04/04/2014

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What I’m Reading on 04/01/2014

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What I’m Reading on 03/31/2014

  • “GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable.”

    tags: bs math octave

  • “The NAG Library for Python gives users of the Python language access to over 1,700 mathematical and statistical routines in the NAG Library. It has been enhanced in-line with Python2.7 and Python3, as well as an improved pythonic interface and a new python egg installer.”

    tags: bs python library nag

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For the Love of Big Data: What is Big Data?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

What is Big Data?

For the Love of Big Data: What is Big Data?

Big data is being generated by everything around us

I think many people are aware of the data that is available every time you do a transaction on the web or buy something in a store. In the latter case, even if you do not use a credit card, the purchase data can be used for restocking inventory, determining how well something is selling, and finding what items are often bought together. This could then be used in marketing and coupon campaigns.

Online, even more information is kept about what you did. Not only does a given vendor know what you bought, they know everything you ever bought from them. They may then guess what you will buy next. They possibly know how you rate an item and can offer you future deals based on your habits. They may also have some sense of your buying network, or “friends,” and can use this data to drive sales by giving extra incentives to those in the network who are the most influential.

Social data such as that in Twitter, Facebook, LinkedIn, and Pinterest is also used, though this is often highly unstructured. That is, it may be free text that must be interpreted. This is not always the case, however, because if you choose to specify the schools you went to from a given list, this data now has exact structure which can be mined.

Perhaps more interesting is the sensor data that is being created by the devices all around you. These include your phones, car, home, and appliances, plus wind turbines, factory machines, and many previously mechanical things that have become more electronic and increasingly connected into the Internet of Things.

Every digital process and social media exchange produces it

If a process is digital, that means data is involved. How much of that is saved and can be used for later analysis?

When you take part in a social network someone knows what you are saying, when you said it in context of your other updates, if it was part of a conversation, possibly what you you were discussing (“rotfl mebbe not”), and the influence structure of your extended network. That is, what you say is just the very beginning of a very long chain of direct and inferred collection of data.

Much of this data is actually metadata. When I do a status update on Twitter, my text is the data, but the time I tweeted and where I was when I did it are both examples of metadata.

When you use a mobile app, a lot of metadata is available too. It’s not just what you did, it’s the sequence in which you did things and with whom. This information can be used to improve the app for you, or allow the app provider to make its services, possibly paid, more attractive to you.

Systems, sensors and mobile devices transmit it

If something is connected to the Internet, it is possible for data to be transmitted and received. This might be via wifi or a cellular connection, although technologies like BlueTooth may be used for local data collection that is then later transmitted at higher bandwidth.

Not everything has to be connected all the time. Some remote machines like tractors allow farmers to employ USB sticks to periodically collect performance and diagnostic data. This may then be used for predictive asset maintenance: let me fix something as late as is reasonable but before it breaks down and causes expensive delays. In this case, the data from the USB stick might be analyzed too late, and a direct network connection would be better.

Big data is arriving from multiple sources at amazing velocities, volumes and varieties

So data is coming from everywhere, and I’ve seen estimates that the amount of metadata is at least ten times greater in size than the original information. So the data is coming in fast (velocity), there is a lot of it (volume), and it is very heterogeneous or even unstructured (variety).

As you you start making connections among all the data, such as linking “Bob Sutor” coming from one place with “R. S. Sutor” coming from another, the size can increase by another order of magnitude.

To extract meaningful value from big data, you need optimal processing power, storage, analytics capabilities, and skills

So with all this bigness, you have a lot of information and you need to process it quickly, possibly in real time. This may require high performance computing, divide-and-conquer techniques using Hadoop or commercial Map Reduce products, or streams. If you are saving data, you need a lot of storage. People are increasingly using the cloud for this data storage and scalable processing.

Now that you have the information, what are you going to do with it? Will you just try to understand what is happening, as in descriptive analytics? How about predictive analytics to figure out what will happen if trends continue or if you modify conditions? Can you optimize the situation to get the result you want? (You might want to see my short “Simple introduction to analytics” blog entry for more detail.)

Technologists are trying to get us closer to the “plug in random data and get exactly the insights you want with amazing visualizations” dream, though it may just be enough to get you started in your explorations. You need solid analytics to do valuable things with the data, and people with the skills to build new and accurate models that can then drive insights you can use.

IBM Watson Analytics is doing some interesting work in this space.

Next: Why do data scientists want more data, rather than less?

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For the Love of Big Data: Why do data scientists want more data, rather than less?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

Why do data scientists want more data, rather than less?

For the Love of Big Data: Why do data scientists want more data, rather than less?

It is there

This may seem simplistic, but if you are a statistician or someone looking for patterns via machine learning or data mining, you love data. A lot of data. More is better.

Data is the basis of the models we create to explain, predict, and affect behavior

Just like physics uses mathematical tools like partial differential equations to model the universe both large and small, data analytics uses other parts of mathematics like statistics, probability, and linear algebra to model what is happening by looking for patterns and behavior from the data we can discern.

Both kinds of models can vary from the very accurate to the really imprecise, depending on our skills, understanding, and information available. New techniques merge physical and data approaches to increase accuracy and decrease the computational load.

With more data, our models become more sophisticated and, we hope, more accurate

The more you know, the more you can fit together the pieces into a coherent whole. Modeling a city, for example, needs a lot of different kinds of data, and this information is often interdependent and redundant. It is non-trivial, however, to put models and simulations based on different techniques together and this often requires advanced, Ph.D.-level knowledge.

Do you know what the relationships are? That is data unto itself and improves the model. Separating the signal from the noise will help you pull out the important parts for analysis, but knowing why the noise is there will teach you about the accuracy of what you are measuring as well as how it is being measured.

How much data is too much data?

When Twitter was first available, people scoffed at the silliness of people talking about what they had for lunch, where, and with whom. Now this is called “social marketing data.”

We just don’t know what techniques we will develop tomorrow that can make better sense of the data we collect today. New work on statistical summarization can help reduce what we save, but it is best to err on the side of saving more data if you can. We might really need that detailed sales information and social media discussions going back five years to see patterns that can help your business grow tomorrow.

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For the Love of Big Data: What issues can analytics present?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

What issues can analytics present?

For the Love of Big Data: What issues can analytics present?

Are all aspects of privacy, anonymization, and liability understood by the practitioners?

Absolutely not, and that’s why you may need to get guidance from an attorney or a privacy professional. Look for precedent on your intended use just as much as you look for someone having done something technically similar before.

If you are a data scientist and not a privacy expert, don’t pretend to be one. It could be a stupid and a costly mistake.

Be especially careful when working with Personally Identifiable Information – data about people, often coming from HR systems within organizations.

If I tell you that you cannot look at some data but you can infer the information (e.g., gender) anyway, is that all right?

Generally, no.

This can be tricky: if you get a non-negative answer to questions about the number of weeks taken for maternity or paternity leave, you might infer the gender. Certain types of color blindness are 16 times more likely in men than women, so that and other hints might lead you to believe with high probability that someone is male.

Check local laws and policies before you engage in any sort of this “go around the rule” cleverness. It’s not just about gender. You must know privacy restrictions before you start playing with data.

It’s also not just about personal data. If I’m a farmer and you have data about what is growing in my fields, that is my data. I very possibly care what you do with it. This is not just an ownership question: does the data tell you more about me and how I operate than I want to share with you?

What are the rules for working with metadata and summarized data?

If I tweet something, the metadata about that includes when I tweeted it and maybe where I was (location data is not always available). Summarized data might be a statistical snapshot that gives you information about means, standard deviations, counts, and so on. Other technology can start with a very big data set and produce a smaller one that has many of the same statistical properties you care about.

Assume, to start, that data, metadata, and summarized data all have the same privacy restrictions. If I cannot move data out of an organization or a country, assume the same about the other two. From there, look to see if laws or contractual agreements soften this at all.

You may need to know where the data resides. If you put the data in a cloud, can you guarantee that it never leaves a country’s boundaries if that is a requirement?

How do we process static, collected data together with more real-time, rapidly changing information such as location?

This question is really asking about how we combine traditional structured information in databases—Systems of Record—with data and metadata coming from social, mobile, and Internet of Things interactions—Systems of Engagement.

While some analytics can be done in batch mode that is relatively non-urgent, some must be done in close to real time. If you are looking to make a stock transaction based on fluctuations in the market, you can’t wait 12 hours after you’ve crunched the numbers all night. If you need to adjust a patient’s treatment based on information streaming in from 5 different kinds of sensors, sooner rather than later will more likely guarantee a better result.

However, if you analyzing the sales results for the last year to better understand why revenue was up in some geographies yet down in others, that can be done in batch. This may mean you use something like Hadoop to break the problem into smaller pieces and then recombine the results at the end, but this is not the only technique. It really depends on the amount and type of data. Similarly, if you are doing healthcare analytics based on longitudinal studies of patients’ responses to treatment regimens, it does not have to be done in real time.

Analytics today often use a combination of static collected data with information that is coming in quickly. Techniques like map/reduce are combined with streams. Data may be put in traditional relational databases, social and network graph databases, other NoSQL databases, or just discarded after it is seen.

The trick is to combine the right underlying big data information management infrastructure with the right analytics and mathematical techniques to achieve the result you need.

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For the Love of Big Data: Approach to policy can determine outcomes

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

Approach to policy can determine outcomes

For the Love of Big Data: Approach to policy can determine outcomes

Reductions in the amount and kinds of data can produce diminished or inaccurate results

I think this is obvious: if crucial data that could help define the context is missing, then the model will probably be incomplete. Therefore, it will be hard for you to produce results that have a high confidence level, or you will be missing factors that are needed for better prediction or optimization.

Think of all the data that is necessary to predict how a particular farm field of tomatoes will do during this next summer season. Geography with elevation, expected sun and rain amounts, wind, soil conditions, planned fertilization, and natural or irrigated water supply all have an effect on what will actually happen. If your model is missing these, your prediction or your ability to tweak the factors to maximize yield will be compromised.

Policy must take into account the value received by individuals for the use of their personal data

You as a consumer may happily give a coffee shop information about your  location in order to get a discount on your next beverage. This is not exactly being “off the grid.”

Increasingly people are willing to give up personal information in exchange for discounts, higher quality, and position within social networks. Formal policy must take into account that privacy is not a fixed idea and will vary over time from person to person as more lucrative items can be traded for it.

Enforced data localization may decrease analytical completeness unless we can move intermediate results or the site of computation

If I am forced to keep all my data, metadata, and derived results within some geographical boundaries, my ability to combine these with information elsewhere will be curtailed. Can we move those other results to the constrained site for more extensive computation? Indeed, can we move the computation to the data instead of the other way around?

These are issues of both policy and cloud technology. What we do and where we do it is limited by both, but as technology often seems to advance far faster than policy, there will be a mismatch between what we can (and should) do with what we are allowed to do.

Big Data is not just about the data. It is about the intended use and the location of that use. Privacy, security, and data ownership are all important considerations that must be factored in before we do the “science” with the data.

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What I’m Reading on 03/27/2014

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What I’m Reading on 03/24/2014

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What I’m Reading on 03/20/2014

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What I’m Reading on 03/18/2014

  • “Like Mountain Lion (OS X 10.8) and Lion (OS X 10.7), Mavericks (OS X 10.9) doesn’t ship on a disc—it’s available only as an installer app downloadable from the Mac App Store, and that installer doesn’t require a bootable installation disc. But there are a good number of reasons you might want a bootable Mavericks installer on an external hard drive or a thumb drive (USB stick).”

    tags: bs mavericks osx

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