Trailing the Tiger Trade

You can learn how stealth cameras work in the tiger exhibit at the Bronx Zoo. In at least one case, the picture recorded by the stealth cam   sealed the conviction for tiger poachers in Thailand last year.  Just like fingerprints, the patterns of tiger stripes are individually distinctive.  Consequently, the poacher’s picture proved that they did break the law. Thanks to the laws and enforcement that EIA works for, one was sentenced to four years and another to five, the longest such sentence yet for this sort of crime.  Read more about the efforts to save big cats with big data in

Trailing the Tiger Trade With Big Data

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Writer's homework

When I read articles by people who didn't bother to investigate the subject properly, I really wonder, why are they getting paid for this? I just read a Guardian piece on the advantages and drawbacks of  massive open online course AKA MOOCs.  Iit includes an assertion that the courses only can be given for subjects that involve multiple choice tests: 

Moocs are limited to subjects that can be assessed with multiple choice exams, marked automatically.Written any essays in your degree? Your professor's critique of them can't be replicated by a mooc – yet.

First of all, MOOCs like Coursera have come up with a way around that, as I explained in a blog posted last year:

Another innovative aspect to Coursera is the way it assesses student work in courses that are not limited to technology or mathematics.

As founder Ng observes, "Multiple choice doesn't really work for a poetry class." Also, with thousands enrolled in a single class, instructors would find it impossible to personalize responses to student work.

Coursera's solution to that problem is the introduction of "a system for peer grading, in which students will be trained to evaluate each other's work based on a grading rubric provided by the professor." This is not all that different from peer reviews encouraged in writers' groups, which some teachers employ in their own classroom, though the Coursera system is designed to ascertain that the students comprehend the instructor's standards before being allowed to grade another's work.

 Second of all, there are already some systems to automate grading for written work as I explained here:

For example, Pearson’s Write to Learn is designed to offer instant feedback and personalized direction on student writing. The software can be accessed at computers in the school or through an Internet connection remotely. Teachers using the software are happy to have much of the grunt work associated with guiding students through revision and editing lifted from their shoulders.  The automated critique also reduces personal confrontations. As one teacher featured in a Write to Learn case study says, there's no "evil professor" who delights in finding fault in student work.

Educational Testing Service's e-rater is another automated assessment tool. It can score 16,000 essays in 20 seconds, a breathtaking rate of productivity when compared to the one to two minutes per essay typically allotted to human scorers.

Students responded positively when the New Jersey Institute of Technology introduced e-raters. An assistant professor there, Andrew Klobucar, observes that whereas students see drafting and revising multiple times as "corrective, even punitive," when assigned by evil professors, they do not have the same negative view when doing it for an e-rater.

I do wish writers would do their own homework when offering an opinion on the current state of educational technology.

New site

I set up a new site at http://writewaypro.net

The Big Bow-Wow & a Bit of Ivory

Sir Walter Scott contrasted his style of writing with that of Jane Austen: "The big Bow-Wow strain I can do myself like any now going; but the exquisite touch which renders ordinary commonplace things and characters interesting from the truth of the description and the sentiment is denied to me". While he characterized his work as large, Jane Austen called her own small, a "little bit (two inches wide) of ivory on which I work with so fine a brush."

The two are married together, so to speak, by Mathew Jockers, who declares them the literary equivalent of Homo erectus, or, if you prefer, Adam and Eve,"

Read more about the humanities going Google, as one article put it in my Big Data Republic blog, The Big Bow-Wow & a Bit of Ivory

DNA data storage

The latest developments in data storage turn to biology. DNA sequencing, not only allows for big data to be stored for thousands of years, but allows for a more compact encoding system based on the 4 letters in the DNA bases rather than than binary zeros and ones that have been used until now. Still, the cost makes it prohibitive for now, and the fact that the sequencing make the data impossible to update within DNA make it not quite the same as a flash drive.  Read about it in  Big Data: Tiny Storage

Smartphone signals for retail analytics

Shopping online offers customers convenience and price transparency, but it offers retailers even more. As Amazon has demonstrated in its successful model, the information it derives from its customer behavior online gives it insight that it uses to tailor its marketing to the individual. As your online browsing tracks, not only what you buy, but what you considered buying, the retailer gets to learn a lot more about you than the person who rings up your purchase at a store. How can a bricks-and-mortar establishment compete with that kind of analytic edge?

 Read more in In-Store Customer Analytics Get Digital Twist

Post-Sandy Street Views

One thing about big data: it is not static. As there is always changes in a situation, what reflected reality one day can be out of date the next. That is especially true when a hurricane of the likes of Sandy sweeps through and alters the landscape and the structures built on it. 

But not everyone is pleased about updates that include images of their hurricane-ravaged homes. Read more at New Maps After Sandy

That's big data entertainment!

In the past, the device held by someone watching television was usually a remote control. In the future, it is just as likely to be a mobile device. Starting next fall, television ratings will be measured in tweets as well as Nielsen numbers as social conversations are analyzed to calculate the reach of a program. Nielsen and Twitter announced the new form rating last month, but their partnership has been in the works for over a year. 

Snoopy was prophetic. 3-D movies have made a comeback. Consequently, movies today pack a lot more data per frame. But big data is also involved in the trend toward data streaming that is displacing discs and in the data on what people want to watch. 

Big data drives today’s movie industry, both in terms of the amount of data packed into each frame you see at theaters and in terms of video streaming online.  It’s what delivers 3-D effects in the theater and personalized recommendations to Netflix viewers.  And very big numbers ride on both.

In the past few years, 3-D movies have staged a comeback on a scale much greater than their  brief heyday in the 1950s. Adding in the 3-D effect adds "anywhere from 100% to 200% more data per frame," according to Jeff Denworth, vice president of marketing for DataDirect Networks (DDN). Denworth attributes the proliferation of present-day 3-D films to the huge success James Cameron had with the 3-D film "Avatar" in 2009, which packed a petabyte of data. 

"Avatar" cost about $237 million to produce, but it brought in more than ten times that amount. It earned the distinction of   IMDB identifies it as "the highest-grossing film of all time."  By the beginning of 2010, it had taken in $2,779,404,183.  A rash of 3-D films followed this success, and many did very well. According to iSuppli Market Intelligence (owned by IHS)  in 2011 3-D films brought in $7 billion at the box-office, 16 percent more than the previous year.

 The full figures for 2012 are not yet in, though they will likely be higher as the number of 3-D screens have gone up from about 9,000 in "2009 to 43,000 in by the third quarter" of 2012. One of the biggest draws of the year, Marvel’s 3D superhero flick, "The Avengers," grossed  $1,511,757,910 in 2012.  As 3-D has grown so common at the theater, movie-makers have to point to something else to distinguish their offering.

 "The Hobbit: An Unexpected Journey" had to do 3-D one better with its "brand new format High Frame Rate 3D (HFR 3D)." Instead of the 24 frames per second, which is the movie standard, it packs in 48. The advantage to the viewer, it claims, is that the greater number offers an experience "closer to what the human eye actually sees." Perhaps so, but quite a number of viewers were less than thrilled by the effect. Nevertheless, by December 29, 2012, "The Hobbit" had already taken in $600,508,000, according to IMDB figures.  

Big data is also the key to watching movies on the small screen. Instead of picking up a disc when they buy or rent a movie, people now can just have it come right to them. As Dan Cryan, senior principal analyst at HIS  observed, in 2012 Americans made  "a historic switch to Internet-based consumption, setting the stage for a worldwide migration from physical to online." 

 Estimates of  online movie payments for the US in 2012 are “3.4 billion views or transactions, up from 1.4 billion in 2011.  This form of video streaming is dominated by Netflix in the US, where it makes up "33% of peak period downstream traffic"  Amazon, Hulu, and HBO Go follow far behind at 1.8%, 1.5%, and .5% respectively.  It intends to keep its lead with the help of big data.

Netflix was the subject of a WSJ blog on using big data to improve streaming video.  Though Netflix still offers to mail out the DVDs people select for rental, more customers now opt for streaming.  In the interest of improving efficiency on that end, Netflix transferred its holdings to Amazon’s cloud. It also started using Hadoop, which enables it "to run massive data analyses, such as graphing traffic patterns for every type of device across multiple markets." That helps plan for improved data transmission and better understanding of the customer.

In addition to using big data solutions for delivery of content, Netflix applies algorithms to predict what their customers would likely want to watch next.  This type of data mining technology makes Netflix confident that it can handle hosting original content. In fact, it bet more than  $100 million on it; that’s the reported sum paid for the rights to two seasons of House of Cards, one of several original content series it plans on streaming. 

 As Netflix’s Chief Communications Officer, Jonathan Friedland, says, "We know what people watch on Netflix and we’re able with a high degree of confidence to understand how big a likely audience is for a given show based on people’s viewing habits." 

So what do you think? Is it possible to guarantee a hit with big data?