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A GUIDE TO LIBYA’S SURVEILLANCE NETWORK

OWNI.eu – By Jean Marc Manach

After repeated interrogations lead by Reflets.info, OWNI, the Wall Street Journal and the Figaro, Amesys, the French company that sold Internet surveillance systems to Gaddafi’s Libya tried to calm things down with a statement posted on its website (mirror):

The contract only concerned the sale of materials capable of analysing a fraction of existing internet connections, only a few thousand.

However, the documents in OWNI’s possession tell a different story, in fact, the exact opposite story. In contrast to traditional surveillance systems that target specific connections, the “massive” (sic) Amesys surveillance system is used to intercept and analyze the entirety of the telecommunications network, to the scale of an entire country.

In its presentations for the high-end surveillance service, Amesys flaunts EAGLE as having been conceived to monitor the whole spectrum of telecommunications: IP traffic (internet), mobile and landline telephone networks, WiFi, satellite, radio and micro waves thanks to its “passive waves, invisible and inaccessible to any intruder.”

The massive system (EAGLE GLINT, GLobal INTelligence, which was the system sold to Libya), was conceived to respond to interception and surveillance needs at a national level and to be capable of aggregating all kinds of information and analyzing, in real time, a national data flow, from a few terabytes to a few dozens petabytes [1peta-octet = 1024 tera-octets, 1 tera-octet = 1024 giga octets and that the total amount of everything ever written by the human race in all languages is estimated at 50 peta-octets…]


EAGLE is therefore able to aggregate, in an automatic fashion, email and physical addresses, telephone numbers, photos of suspects, but also to make automatic searches by date, hour, telephone number, email address, keyword, localization… [Read more…]

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BEST OF Chaos Communication Camp 2011 INTERVIEWS

OWNI.Eu

OWNI erected its tent at the Chaos Communication Camp this year for five days. Where? In an ancient Soviet military base, complete with airplanes and an open air museum. 3,500 hackers were expected for what is known to be the largest assembly of the kind in Europe. Here’s a collection of the best of OWNI’s interviews from these five days in the heart of hackerdom.

Birgitta Jónsdóttir: “Keep the freedom of information what it should be: free.”

The Icelandic deputy Birgitta Jónsdóttir is the backbone behind the Icelandic Media Modernization Initiative (IMMI), a resolution that aims to make Iceland into a paradise for freedom of expression.

[vimeo 27685673]

 

Macro: “I hope that being part of a hackerspace will no longer be so underground.”

Created in 1995 in Berlin, the C-Base was one of the first hackerspaces in the world, even if it has begun to think of itself as more of a makerspace. 350 members strong, it hosts CCC events and artistic performances. We look under the tent with Marco, their current “chief.”

[vimeo 27685289]

…

[Read more…] 

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DATA VISUALISING THE STORY OF FOOD AND EMOTION

OWNI.eu by EKATERINA YUDIN

How do we even begin to visualize and draw connections between the intimately complex relationship that exists between food and emotion? Here is a great article by Ekaterina Yudin that we picked for its compelling data visualisations. You can find the original version on the Masters of Media website, otherwise read on! It is worth it.

Can we discover patterns amongst global food trends and global emotional trends? Could data visualization help us weave a story, and make use of the complex streams of data surrounding food and its consumption, to reveal insights otherwise invisible to the naked eye? And why would we try to do so in the first place?

To begin, let’s just establish that one has an ambitious appetite.

For our group information visualization project we have set out to measure global food sentiment. The main objective of our project matches the very definition of information visualization first put forth by Card et al. (1999) – of using computer-supported, interactive, visual representations of data to amplify cognition, where the main goal of insight is discovery, decision making (as investigated in my last post), and explanation. Our mission is to gauge and visualize, in real-time, the planet’s feelings towards particular foods using Twitter data; does pizza make everyone happy, do salads make people sad, does cake comfort us? Will there be an accordance of food with nations?

Setting the visualization in the backdrop of country GDP and obesity levels we can begin to ponder how the social, political and cultural issues will play out and what reflections of globalization will emerge. Will richer countries be more obese? It should be noted that being restricted to English language tweets for now creates a huge bias in our visualization, and one should keep in mind that the snapshot of data will obviously not be completely representative of the entire world; for example, in developing countries it’s most probable that only rich/modern people speak English AND use Twitter at the same time.

The relationships between all the variables is already an enigmatic one, particularly when each carry their own layers of baggage, so a narrative of complexity emerges even before the visualization can be realized. Incidentally this is the story the data is already beginning to weave, which makes it a perfect calling for data visualization to reduce the complexity, present it in a meaningful way we can understand and use its power of storytelling to understand our puzzling relationships towards food — a story worth discovering.

WHY FOOD?

Food is at the core of our daily survival, with broad-ranging effects on personal health, and a particularly hot topic these days with everyone having some opinion about it — after all, everyone needs it, which makes food intrinsically emotional. So it is no surprise that a wealth of conversations emerge about food when today’s increased citizen interest, health focus and demand for a transparent food industry collide; to top it off, this is all happening amidst concerns of food security, shortages, rising food prices, obesity, hunger, addiction and diseases. With data related to food increasingly open, the benefits of using data visualization, as well as the empowerment that access to layers of hidden information produces, is already being explored on the web.

A brief survey of food visualizations reveal: the ten most carnivorous countries, world hunger visualization, how the U.S.A was much thinner not that long go, snacks available in middle and high school vending machines, calories per dollar, driving is why you’re fat, where Twinkies come from, and so on.

Health issues related to food run high in the corpus of visualizations and it is no surprise. With improved access to information about food (sources, ingredients, effects, consumption statistics, etc.) presented in a visually engaging way, we can begin to distill the essential changes that could then impact our food-purchasing choices, enable better health, and enhance the design of an open food movement. [An additional reel of 60 food/health infographics can be found here].

Food is not just a lifestyle that is essential and important to the world. It can also be one of the most effective ways to reshape health, poverty issues, and relationships; and because it touches all facets of life, it shouldn’t be treated as just a lifestyle’y sort of thing. –Nicola Twilley (FoodandTechConnect Interview)

What’s the insight worth?

Beyond helping discover new understandings amidst a profoundly complicated world where massive amounts of information create a problem of scaling, a great visualization can help create a shared view of a situation and align people on needed action — it can often make people realize they are more similar than different, and that they agree more than they disagree. And it is precisely via stories — which are compelling and have always been used to convey information, experiences, ideas and cultural values — that we can begin to better understand the world and transform the interdependent factors of food and sentiment discussions into a visual form that makes sense. In this way, food – a naturally social phenomenon — can become our lens that reveals patterns in society.

A multitude of blogs, projects and companies such as GOOD’s Food Studies, Food+Tech Connect,The Foodprint Project, innovation series like the interactive future of food research) and lest not forget Jamie Oliver’s food revolution, to name just a few, propel the exploration, understanding and the reshaping of conversation about food, health and technology today and in the future. (Food+Tech Connect, 2011). But it is the newest wave of infographics and data visualizations that seek to draw our attention to epidemics such as food shortages and obesity by illustrating meaning in the numbers for people to truly see and understand the implications.

 

A WEB OF FEELINGS

We also can’t entirely separate feelings from food. People consistently experience varying emotional levels (see Natalie’s post on this very subject) and these play key roles in our daily decision-making. Emotions, too, have now begun to be mapped out in visualizations ranging from a mapping of a nation’s well being to a view of the world mean happiness.

 

 

Taking food and emotion together we come to understand that this data of the everyday paints a picture and hyper-digitizes life in a way that self-portraits and global portraits of food consumption patterns begin to emerge. As psychology researchers have shown us, people are capable of a diverse range of emotions. And because food provides a sense of place – a soothing and comforting feeling — it makes food evoke strong emotions that tie it right back to the people (Resnick, 2009).

Now that we spend a majority of our time online, our feelings and raw emotion, too, find their way to the web. We can visualize this phenomenon with projects like We Feel Fine, which taps into our and other people’s emotions by scanning the blogosphere and mapping the entire range of human emotions (thereby essentially painting a picture of international human emotion), I want you to want me, which explores the complex relationship on love and hope amongst people, Lovelines, which illuminates the emotional landscape between love and hate, and The Whale Hunt, which explores death and anxiety.

What all these visualizations have in common is the critical component of an emotional aesthetic — the display of people’s bubbling feelings that are often removed from visualizations but is the very human aspect we tend to remember. This is in line with Gert Nielsen’s philosophy that he shared with the audience at the Wireless Stories conference early last month — that you can’t take the human being out of the visualization or else you take out the emotion, too; the key, it seems, is data should ‘enrich’ the human stuff and the powerful human stories that are waiting to be captured and told.

MAKING DISCOVERIES AND SPREADING AWARENESS IN A SEA OF DATA

Which brings us to our data deluge world. We’re increasingly dependent on data while perpetually creating it at the same time. But creating data isn’t the question (at least not for Western and emerging countries, whereas producing relevant data for developing countries is still quite a challenge) – it’s whether someone is paying attention to the data, and whether someone is using the data usefully in an even larger question (Resnick, 2009).

The age of data accessibility, information [sharing], and connectivity allows people, cultures and institutions to share and influence each other daily via a plethora of broadcast platforms available on the web; these function as a public shout box for daily chatter, emotional self-expression, social interaction, and commiseration. Twitter – the social media network, twenty-four-hour news site and conversation platform that connects those with access across the world — is also the chosen data pool for our project. It’s a place to share just as much as it is to peek into other lives and conversations. And precisely because it’s a place where millions of people express feelings and opinions about every issue that the distillation of knowledge from this huge amount of unstructured data becomes a challenging task. In this case visualization can serve to extend the digital landscape to better understand broadcasts of human interaction. Our digital lives, and conversations within them, are full of traces we leave behind.  But by transcoding and mapping these into visual images, representations, and associations, we can begin to comprehend meanings and associations.

Twitter is also a narrative domain, and serves as a platform for Web 2.0 storytelling – the telling of stories using Web 2.0 tools, technologies, and strategies (Alexander & Levine, 2008). Alexander and Levine (2008) distinguish such web 2.0 projects as having features of micro-content (small chunks of content, with each chunk conveying a primary idea or concept) and social media (platforms that are structured around people). With the number of distributed discussions across Twitter, a new environment for storytelling emerges — one we will explore to uncover and analyze global patterns amongst conversations surrounding food sentiment.

SO WHAT’S THE FOOD + EMOTION STORY?

As put forth by Segel & Heer (2009), each data point has a story behind it in the same way that every character in a book has a past, present, and future, with interactions and relationships that exist between the data points themselves. Thus, to reveal information and stories hiding behind the data we can turn to the storytelling potential of data visualization, where visualization can serve to create new stories and insights that can ultimately function in place of a written story. These new types of stories — ones that are made possible by data visualization — empower an open door for the free exploration and filtering of visual data, which according to Ben Shneiderman also allow people to become more engaged (NYTimes, 2011).

To date, the storytelling potential of data visualization has been explored and popularized by news organizations such as the NY Times and the Guardian, where visualizations of news data are used to convince us of something (humanize us), compel us to action, enlighten us with new information, or force us to question our own preconceptions (Yau, 2008). There is a growing sense of the importance of making complex data visually comprehensible and this was the very motivation behind our project; of linking food and emotion sentiment with country GDP and obesity to see if insightful patterns emerge using this new visual language. With our visualization still in progress, and data still dispersed, I’m still wondering what’s the story and what could the story of our visualization become? Will the visualization of our data streams produce something insightful? What will we be able to say about how people feel towards foods in different countries? At this point it’s only a matter of time until we dig deeper into the complexities of our real world data ti understand the (food <–> emotion) <–> (income <–> obesity) paradox.

—

This post was originally published on Masters of Media

Photo Credits: The New York Times, R. Veenhoven, World Database of Happiness, Trend in Nations, Erasmus University Rotterdam, World Food Program, GOOD and Hyperakt, A Wing, A prayer, Zut Alors, Inc. and GOOD, and Flickr CC Kokotron

References:

Alexander, B. & Levine, A. (2008). “Web 2.0 Storytelling: Emergence of a New Genre”. Web. Educause. Accessed on 19/04/11

Card, K.S., Mackinlay, J. D., & Shneiderman, B. (1999). “Readings in Information Visualization, using vision to think”. Morgan Kaufmann, Cal. USA.

Resnick, M. (2009). “The Moveable Feast of Memory”. Web. PsychologyToday.com. Accessed on 20/04/11

Segel, E. & Heer, J. (2010). “Narrative Visualization: Telling Stories with Data”.

Singer, N. (2011). “When the Data Struts Its Stuff”. Web. NYTimes.com. Accessed on 19/04/11

Yau, N. (2008). “Great Data Visualization Tells a Great Story”. Web. FlowingData.com. Accessed on 20/04/11


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10 CHARTS ABOUT SEX [Infographics]

OWNI.EU

Data journalism can make sense out of very complicated and sometimes uncommon information. But some creative minds came up with really good data visualisation regarding our daily life activities and in this instance: Sex. So here is an article from OWNI.eu, originally published on OkCupid’s blog, dealing with many aspects of our tumultuous sex life. . . Enjoy!

This was one of the first infographics ever made:

Later remembered as “the map that made a nation cry”, it depicts Napoleon’s failed invasion of Russia in 1812. The wide tan swath shows his Grande Armée, almost half a million strong, marching East to Moscow; the black trickle shows the few who straggled back. It’s an elegant fusion of geography, time, and temperature into a single statement of military disaster.

Of course, using modern tools of analysis, like circles and the color blue, we can get an even clearer picture of history:

It is our goal today to create graphics of similar concision and power, but about something more useful than war—sex.

All the data below, even the most personal stuff, has been gleaned from real user activity on OkCupid. Some of it our users have told us outright by answering match questions; some of it we’ve had to learn from observation.

Other than the unifying theme, sex, there’s no big point or thesis to this post: just comparisons, correlations, and quirky trends.

Chart #1

We found this by crossing the match questions Do you like to exercise? and Is it difficult for you to have an orgasm?, and, as you can see, women who don’t like working out report twice the orgasm problems of women who do.

Chart #2

Here, we took a single question—Is your ideal sex rough or gentle?—and scraped people’s profile text for the words that most correlated to each answer. Here are word clouds for women and men in their 20s.

The text is basically Hot Topic versus, I dunno, Burberry. But beyond the words the interesting thing is how men’s and women’s preferences change with age:

This dataset only includes single people, of course, but I was still very surprised at how many old men like it rough. Looks like I’m going to have to rethink a cherished part of my worldview.

Chart #3

The odds shown in this chart, and the others like it later in the post, are odds “in favor”—in this case, odds in favor of being into giving oral sex. The higher a group’s odds, the more into it they are.

Since so much sexual slang involves meat—”hot dog,” “sausage,” “burger,” “beef injection,” “another beef injection,” and so on—I thought this would be a fine occasion to point out that there are plenty of veggie alternatives:

Vegetarian-Friendly Sex Slang
Peeling the banana.
Tossing the salad.
Squeezing the melons.
Zeroing in on a grown man’s nuts and nutsack.
Putting Monsanto in yoursanto.
Ordering the split pea soup.
Sorry, that’s got ham.

Cornholing others.

Charts #4 & #5

Frequent tweeters have shorter real-life relationships than everyone else, probably via some bit.ly hack. Unfortunately, we have no way to tell who’s dumping who here; whether the twitterati are more annoying or just more flighty than everyone else. There is also this:

If someone tweets every day, it’s 2-to-1 that they’re #ingthemselves just as often. Like the “shorter relationships” thing, this is true across all age and gender groups.

Chart #6:

In the Bible, in between the part where Reuben kills a he-goat so he can dip some clothes in the blood of the he-goat and where Judah tries to give Tamar a goat but decides maybe she should be burned to death instead, God kills a man named Onan because Onan intentionally spills his seed on the ground.

(1) Thou shalt not whack off. (2) Mo goats mo problems.

Life lessons! From the Iron Age!

Charts #7 & #8

This bubble chart, plotting body type, sex drive, and self-confidence, is dynamic—you can use the slider at the bottom change it. As you can see as you move the control from left to right, a woman’s sexuality peaks in her twenties, holds more or less steady for twenty years, and then falls to the floor. And while sex drive waxes and wanes, self-confidence steadily grows.

Remember, the women themselves select their body-descriptions; the bubbles show the size of each group. Though many of the words are just a shade of meaning apart, there are dramatic differences in the traits of the people who choose them. Go through the animation and compare full-figured to curvy orskinny to thin.

It’s particularly interesting to isolate skinny—a deprecating way to say something generally considered positive (being thin)—and curvy—an empowering way to say something generally considered negative (being heavy). Here are those bubbles’ complete paths across the graph:

Curvy women pass skinny ones in self-confidence at age 29 and never look back. They also consistently have the highest sex drive among the groups. Curvy, as a word, has the strongest sensual overtones of all our self-descriptions. So we’re getting a little insight into the real-world implications of a label.

This is the “complete path” plot for men:

Things to notice: (1) almost no men choose curvy or full-figured as self-descriptions, so those words aren’t plotted here; (2) men of all body types have roughly the same peak sex drive; (3) and the thing that matters most for guys is simply to not be overweight. The other four body types are clustered relatively together at most ages.

Chart #9

For this chart, we took our own data and mixed it with a little outside stuff: college tuitions from U.S. News & World Report.

Generally speaking, the more your parents are paying for your education, the more horny you are. If only Freud were still around to help us understand; instead we have psychology majors, those Adidas shower sandals, and darkness.

You can think of the dotted best-fit line as dividing the good sex-ed values (above the line) from the bad ones (below). The line also gives us a handy sliding scale: given a 36-week school year and the average partner, every $2,000 spent on your college tuition is an extra time you could be having sex that year.

Chart #10

The correlation between sex and money is robust for colleges, but it gets even stronger when extended to entire nations.

We were amazed at this result—money seems to be a more powerful influence on sex drive than culture or even religion.

You have, for example, Portugal, Oman, Slovenia, and Taiwan within a few pixels of each other on the right side of the graph, and Syria, Sri Lanka, and Guatemala almost stacked on the left, and all of them sit along the trend line.

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This post was originally published on OkCupid’s blog

Photo Credits: OkCupid and Flickr CC HikingArtist.com

 

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Data Journalism: The Story So Far

DATA MINER UK – by Nicola Hughes

Such a great article on the story of data journalism by Nicola Hughes that we decided to put it all! Get the original article on Data Miner UK…

[youtube 3YcZ3Zqk0a8]

And here’s what Tim Berner-Lee, founder of the internet, said regarding the subject of data journalism:

Journalists need to be data-savvy… [it’s] going to be about poring over data and equipping yourself with the tools to analyse it and picking out what’s interesting. And keeping it in perspective, helping people out by really seeing where it all fits together, and what’s going on in the country

How the Media Handle Data:

Data has sprung onto the journalistic platform of late in the form of the Iraq War Logs (mapped by The Guardian), the MP’s expenses (bought by The Telegraph) and the leaked US Embassy Cables (visualized by Der Spiegel). What strikes me about these big hitters is the existence of the data is a story in itself. Which is why they had to be covered. And how they can be sold to an editor. These data events force the journalistic platform into handling large amounts of data. The leaks are stories so there’s your headline before you start actually looking for stories. In fact, the Fleet Street Blues blog pointed out the sorry lack of stories from such a rich source of data, noting the quick turn to headlines about Wikileaks and Assange.

Der Spiegel - The US Embassy Dispatches
Der Spiegel – The US Embassy Dispatches

 

So journalism so far has had to handle large data dumps which has spurred on the area of data journalism. But they also serve to highlight the fact that the journalistic platform as yet cannot handle data. Not the steady stream of public data eking out of government offices and public bodies. What has caught the attention of news organizations is social media. And that’s a steady stream of useful information. But again, all that’s permitted is some fancy graphics hammered out by programmers who are glad to be dealing with something more challenging than picture galleries (here’s an example of how  CNN used twitter data).

So infographics (see the Stanford project: Journalism in the Age of Data) and interactives (e.g. New York Times: A Peek into Netflix Queues) have been the keystone from which the journalism data platform is being built. But there are stories and not just pictures to be found in data. There are strange goings-on that need to be unearthed. And there are players outside of the newsroom doing just that.

How the Data Journalists Handle Data:

Data, before it was made sociable or leakable, was the beat of the computer-assisted-reporters (CAR). They date as far back as 1989 with the setting up of the National Institute for Computer-Assisted Reporting in the States. Which is soon to be followed by the European Centre for Computer Assisted Reporting. The french group, OWNI, are the latest (and coolest) revolutionaries when it comes to new age journalism and are exploring the data avenues with aplomb. CAR then morphed into Hacks/Hackers when reporters realized that computers were tools that every journalist should use for reporting. There’s no such thing as telephone-assisted-reporting.  So some whacky journalists (myself now included) decided to pair up with developers to see what can be done with web data.

This now seems to be catching on in the newsroom. The Chicago Tribune has a data center, to name just one. In fact, the data center at the Texas Tribune drives the majority of the sites traffic. Data journalism is growing alongside the growing availability of data and the tools that can be used to extract, refine and probe it. However, at the core of any data driven story is the journalist. And what needs to be fostered now, I would argue, is the data nose of a (any) journalist. Journalism, in its purest form, is interrogation. The world of data is an untapped goldmine and what’s lacking now is the data acumen to get digging. There are Pulitzers embedded in the data strata which can be struck with little use of heavy machinery. Data driven journalism and indeed CAR has been around long before social media, web 2.0 and even the internet. One of the earliest examples of computer assisted reporting was in 1967, after riots in Detroit, when Philip Meyer used survey research, analyzed on a mainframe computer, to show that people who had attended college were equally likely to have rioted as were high school dropouts. This turned the publics’ attention to the pervasive racial discrimination in policing and housing in Detroit.

Where Data Fits into Journalism:

I’ve been looking at the States and the broadsheets reputation for investigative journalism has produced some real gems. What stuck me, by looking at news data over the Atlantic, is that data journalism has been seeded earlier and possibly more prolifically than in the UK. I’m not sure if it’s more established but I suspect so (but not by a wide margin). For example, at the end of 2004, the then Dallas Morning News analyzed the school test scores of the Texas Assessment of Knowledge and Skills and uncovered one school’s alleged cheating on standardized tests. This then turned into a story on cheating across the state. The Seattle Times piece of 2008, logging and landslides, revealed how a logging company was blatantly allowed to clear-cut unstable slopes. Not only did they produce and interactive but the beauty of data journalism (which is becoming a trend) is to write about how the investigation was uncovered using the requested data.

The Seattle Times: Landslides in the Upper Chehalis River Basin
The Seattle Times: Landslides in the Upper Chehalis River Basin

 

Newspapers in the US are clearly beginning to realize that data is a commodity for which you can buy trust from your consumer. The need for speed seems to be diminishing as social media gets there first, and viewers turn to the web for richer information. News in the sense of something new to you, is being condensed into 140 character alerts, newsletters, status updates and things that go bing on your mobile device. News companies are starting to think about news online as exploratory information that speaks to the individual (which is web 2.0). So the The New York Times has mapped the census data in its project “Mapping America: Every City, Every Block”. The Los Angeles Times has also added crime data so that its readers are informed citizens not just site surfers. My personal heros are the investigative reporters at ProPublica who not only partner with mainstream news outlets for projects like Dollars for Doctors, they also blog about the new tools they’re using to dig the data. Proof the US is heading down the data mine is the fact that Pulitzer finalists for local journalism included a two year data dig by the Las Vegas Sun into preventable medical mistakes in Las Vegas hospitals.

Lessons in Data Journalism:

Another sign that data journalism is on the up is the recent uptake at teaching centres for the next generation journalist. Here in the UK, City University has introduced an MA in Interactive Journalism which includes a module in data journalism. Across the pond, the US is again ahead of the game with Columbia University offering a duel masters’ in Computer Science and Journalism. Words from the journalism underground are now muttering terms like Goolge Refine, Ruby and Scraperwiki. O’Reilly Radar has talked about data journalism.

The beauty of the social and semantic web is that I can learn from the journalists working with data, the miners carving out the pathways I intend to follow. They share what they do. Big shot correspondents get a blog on the news site. Data journalists don’t, but they blog because they know that collaboration and information is the key to selling what it is they do (e.g Anthony DeBarros, database editor at USA Today). They are still trying to sell damned good journalism to the media sector!  Multimedia journalists for local news are getting it (e.g David Higgerson, Trinity Mirror Regionals). Even grassroots community bloggers are at it (e.g. Joseph Stashko of Blog Preston). Looks like data journalism is working its way from the bottom up.

Back in Business:

Here are two interesting articles relating to the growing area of data and data journalism as a business. Please have a look: Data is the New Oil and News organizations must become hubs of trusted data in a market seeking (and valuing) trust.