e-Xploration

CONTEXTUAL COMPUTING: OUR SIXTH, SEVENTH, AND EIGHTH SENSES

In the coming years, there will be a shift toward what is now known as contextual computing, defined in large part by Georgia Tech researchersAnind Dey and Gregory Abowd about a decade ago. Always-present computers, able to sense the objective and subjective aspects of a given situation, will augment our ability to perceive and act in the moment based on where we are, who we’re with, and our past experiences. These are our sixth, seventh, and eighth senses.

Hints of this shift are already arriving. Mobile devices with GPS deliver location-based services, which sets a baseline for the many ways your phone can gather information it will use to make your life easier down the line. Amazon’s and Netflix’s recommendation engines, while not magnificently intuitive, feed you book and video recommendations based on your behavior and ratings. Facebook’s and Twitter’s valuations are premised on the notion that they can leverage knowledge of your acquaintances and interests to push out relevant content and market to you in more effective ways.

 

YOUR PERSONAL GRAPH CONTAINS (GULP) ALL YOUR BELIEFS

This is the set of data relating to a person’s deepest held beliefs, core values, and personality. It’s what makes a person unique in the world, just as the social graph helps to show what makes her similar to others. The data set is under-developed at the moment, and it’s quite difficult to design for, even conceptually.

Given that psychology still struggles to explain exactly how our personal identities function, it’s not surprising that documenting such information in a computable form is slow to emerge. There are early indicators that this will change, however. For example, Proust.com, a relatively new (and struggling) social-networking service, asks users to document intimate details of their lives and their beliefs based on the idea of the famed Proust Questionnaire. People have, quite reasonably so, been reluctant to share such information in a publicly viewable social network.

A more successful example is Evernote, which has built a large business based on making it incredibly easy and secure to document both recently consumed information and your innermost thoughts. Scraping such intimate files for data is currently the questionable realm of the NSA, however. Entirely new solutions will need to be created if the potential of the personal graph is to be reached.

 

YOUR BEHAVIOR CAN BE EASILY GRAPHED

It’s easy for data to depict what you actually do instead of what you claim to do. Sensors do the job. So do, if less elegantly, self-reporting mechanisms. This data can sit in pivotal contrast to the interest graph, allowing computers to know, perhaps better than you, how likely you are to go for a jog. It would be useful, too, for a travel site that notes how you tell friends you’d like to visit China but records that you only vacation in Europe. Rather than uselessly recommending vacation deals to Beijing, a smart travel app would instead feed you deals to Paris or Berlin. The behavior graph provides the foundation, to some extent, of Google Search, Netflix recommendations, Amazon recommendations, iTunes Genius, Nike+ run tracking, FourSquare, FitBit, and the entire "quantified self" movement. When mashed against the other three graphs, there’s a potential for real insight.

Are you an avid user of Snapchat, that kind of person who likes bits that go poof? If you or your kids are under 25, chances are you do. The wildly popular photo-sharing app—which promises that pictures self-destruct after 10 seconds—is a clear sign that many people long for privacy. Snapchat claims to have finally delivered to us a medium that does not forever save and store our data. We want that! Of course we do.

Unfortunately, Snapchat doesn’t quite transport us to the land of data privacy. It sounds too good to be true, and it is. In much the same way that Facebook deludes people into the belief that they can actually be private, it gives us a false sense of security. Twitter makes no bones about privacy; it is, and claims to be, an open public network where you are public by default. With the likes Snapchat and Facebook—and most of social media, in fact—many mistakenly believe in the illusion of being private.

 

The specific problem with Snapchat, of course, is that while the photo message on Snapchat disappears from the phone of the recipient after a few seconds, it does not prevent the nimble-fingered receiver from taking a screenshot. If that happens you get an alert, but what good does that really do? It certainly doesn’t prevent the screenshot from being shared with others, as happened at this New Jersey high school. There’s another hack to work around that alert. And last but far from least, a US-based company Decipher Forensics told the Guardian that they figured out how to recover photos from the Android version of Snapchat in a matter of days. The company is now trying to recover photos from the iOS version of Snapchat. The photo-app has been downloaded more than five million times in the Android marketplace and has been at the top of the Apple app store for quite a while.

 

In 2010 New York City added 54 million metric tons of carbon dioxide to the atmosphere (75% from buildings, the bulk of the rest from transport) but that number means little to most people because few of us have a sense of scale for atmospheric pollution.

 

Carbon Visuals, supported by Environmental Defense Fund, have created a film that makes those emissions feel more real - the total emissions and the rate of emission. Designed to engage the ‘person on the street’, this version is exploratory and still work in progress.

 

Emissions in 2010 were 12% less than 2005 emissions. The City of New York is on track to reduce emissions by 30% by 2017 - an ambitious target. Mayor Bloomberg’s office has not been involved in the creation or dissemination of this video.

See how we can help cities engage their citizens in carbon issues.

See video on YouTube

 

Street-level view of 10 metre (33 ft) spheres of carbon dioxide gas emerging at a rate of one every 0.58 seconds

 

For the technically minded:

In 2010 (the latest year for which data is available) New York City added 54,349,650 metric tons of carbon dioxide to the atmosphere = 148,903 tons a day = 6,204 tons an hour = 1.72 tons a second.

 

City of New York, Inventory of New York City Greenhouse Gas Emissions, September 2011, by Jonathan Dickinson and Andrea Tenorio. Mayor’s Office of Long-Term Planning and Sustainability, New York, 2011

At standard pressure and 59 °F a metric ton of carbon dioxide gas would fill a sphere 33 feet across (density of CO₂ = 1.87 kg/m⊃3;).

 

If this is how carbon dioxide gas was actually emitted in New York we would see one of these spheres appear every 0.58 seconds.

Google propose une nouvelle fonctionnalité dans son onglet « Tendance des recherches » : la possibilité de visualiser en temps réel les recherches effectuées sur le réseau. Cette fonctionnalité n’est disponible actuellement que pour 11 régions du monde (Etats-Unis, Taiwan, Inde, Japon, Australie, Canada, Hong Kong, Israël, Royaume-Uni, Singapour, Russie) mais l’interface est fluide et sympathique.

 

Google permet aussi de visualiser les tops des recherches aux Etats-Unis, depuis 2004, selon différents critères : auteurs, équipes de basket, éléments chimiques, pop stars,… Et d’intégrer ces divers éléments dans ses sites.

El objetivo es ayudar a los usuarios a evaluar la fiabilidad de la información que reciben de los medios sociales mediante el análisis del comportamiento de los reporteros ciudadanos. En concreto, Monroy, en colaboración con los otros autores de la investigación “Narcotuits: Social Media en tiempos de Guerra” ha recogido y analizado un importante volumen de datos de hashtags (etiquetas que permiten seguir un tema) como #Mtyfollows o #RiesgoMty. Por ejemplo, 600.000 tuits que contenían algúnhashtag relacionado con la guerra de la droga.

 

El enfoque social que desde sus inicios como investigador ha mostrado Monroy se sembró en su niñez. Su familia estuvo muy involucrada en movimientos políticos progresistas durante los años 80. Y a este entorno se unió su fascinación por la ciencia y la tecnología. “Me gustaba mucho leer una revista científica para niños llamada Chispa, de la cual aprendí mucho, y la enciclopedia Proteo, que era mitad historia de ciencia ficción sobre un robot y mitad enciclopedia científica”, recuerda el joven.

 

En la actualidad, Monroy trabaja en Microsoft Research y en el Centro Berkman para Internet y Sociedad en la Universidad de Harvard, ambas en EE.UU.. Desde ahí sigue trabajando para promover la participación ciudadana. “Más allá de mi interés personal por el hecho de ser algo que aflige a mi país de origen, el caso de los narcotuits me pareció fascinante desde el punto de vista científico porque las redes sociales han permitido que los ciudadanos tomen el rol del Estado y de los medios de comunicación tradicionales", explica. Por ello Monroy destaca el papel del ciudadano como seleccionador de contenidos; más aún teniendo en cuenta la dificultad que entraña la misma propagación de la información o -lo más difícil de cuantificar- la desinformación.

If you were to walk into my office, I’d have a pretty decent sense of your gender, your age, your race, and other identity markers. My knowledge wouldn’t be perfect, but it would give me plenty of information that I could use to discriminate against you if I felt like it. The law doesn’t prohibit me for “collecting” this information in a job interview nor does it say that discrimination is acceptable if you “shared” this information with me. That’s good news given that faking what’s written on your body is bloody hard. What the law does is regulate how this information can be used by me, the theoretical employer. This doesn’t put an end to all discrimination – plenty of people are discriminated against based on what’s written on their bodies – but it does provide you with legal rights if you think you were discriminated against and it forces the employer to think twice about hiring practices.

 

The Internet has made it possible for you to create digital bodies that reflect a whole lot more than your demographics. Your online profiles convey a lot about you, but that content is produced in a context. And, more often than not, that context has nothing to do with employment. This creates an interesting conundrum. Should employers have the right to discriminate against you because of your Facebook profile? One might argue that they should because such a profile reflects your “character” or your priorities or your public presence. Personally, I think that’s just code for discriminating against you because you’re not like me, the theoretical employer.

 

Of course, it’s a tough call. Hiring is hard. We’re always looking for better ways to judge someone and goddess knows that an interview plus resume is rarely the best way to assess whether or not there’s a “good fit.” It’s far too tempting to jump on the Internet and try to figure out who someone is based on what we can drudge up online. This might be reasonable if only we were reasonable judges of people’s signaling or remotely good at assessing them in context. Cuz it’s a whole lot harder to assess someone’s professional sensibilities by their social activities if they come from a world different than our own.

 

Given this, I was fascinated to learn that the German government is proposing legislation that would put restrictions on what Internet content employers could use when recruiting.

Acxiom is one of the largest data brokers in the world, yet few average consumers know much about it. You’re about to find out a bit more. But before I get into that I’d like to correct two errors related to Acxiom that appeared recently in TY4NS.

 

Contrary to a report published in the Financial Times, which was later repeated by CNETand yours truly, Acxiom is not planning to open the kimono and let us all take a peek inside at the data it has collected about us. According to an Acxiom spokesperson, while the company is looking into the possibility of offering more transparency to consumers, it’s not yet on their radar, in part due to the enormous engineering challenges such disclosure would entail.

 

Second: A while back I ran an interview with Ray Everett, currently director of advertising privacy at Yahoo, in which I called him the first person to hold the title of Chief Privacy Officer for any organization. Well, turns out I was wrong there too. Ray got tabbed as CPO for the now defunct AllAdvantage in 1999. That’s 8 years after Jennifer Barrett Glasgowdoffed that title for Acxiom. (If there any CPOs who’ve held the title longer, please ping me – I’m keeping a scrapbook.)

 

So I when was offered the opportunity to interview the oldest — err, longest tenured -- privacy officer in the world, I jumped at the chance. But first some background about Acxiom.

Most people know the company as a data broker. Some people know it as an online tracking company. But very few know that Acxiom is also an IT services firm. Given that it’s been gathering data about hundreds of millions of consumers since 1969, storing it on banks of mainframes at its headquarters in Little Rock and elsewhere, that shouldn’t be surprising. According to Gartner, Acxiom is one of the top three mainframe outsource providers in North America.

Technology that incorporates social network analysis, which helps establish connections and relationships between people, and predictive coding, which provides machine-learning techniques that help systems learn fraud patterns, are among the weapons agencies are enlisting to combat fraudulent payments, according to industry experts.

 

The Los Angeles County Department of Public Social Services is using social network and predictive analytics from SAS Analytics to identify potential fraud and prevent improper assistance payments. The Data Mining Solution for Child Care Welfare Fraud Detection, based on the SAS Fraud Framework for Government and SAS data mining techniques, debuted in May 2011.

 

Using the software, DPSS investigators detected two conspiring groups and mapped a network of participants and providers to display their relationships. Using the framework’s social relationship network capabilities, they created a display showing a web of complex relations linked by common telephone numbers and addresses. In one case, DPSS staff found a child care provider serving many participants working together in fraudulent activities.

Una nueva aplicación desarrollada por un joven estadounidense permite a los consumidores comprar productos de empresas cuyos principios comparten, así como tomar parte en campañas a favor o en contra de ciertas ideas.

Ivan Pardo, un estadounidense de 26 años de edad de Los Angeles, tardó unos 16 meses en crear una aplicación que lleva el nombre de Buycott. Su funcionamiento consta de dos partes. Una vez descargada la aplicación, los usuarios pueden buscar los grupos disponibles que abogan por apoyar o boicotear varias iniciativas y unirse a ellos.   

Una de las campañas más populares es la que se denomina 'Diga 'no' a Monsanto', que incluye a unos 10.000 usuarios que se oponen a la empresa biotecnológica que produce alimentos genéticamente modificados. Unas 29.000 personas también se unieron al grupo 'Exija la etiquetación de los OGM'. 

Las campañas se dividen por temas: la educación, el medio ambiente, la justicia económica, la responsabilidad social o los derechos de los inmigrantes, entre otros. Por el momento, la aplicación cuenta con más de 100 campañas y la lista sigue aumentando. Pardo insta a la gente a crear campañas si existe alguna causa que ellos quieren ver en la aplicación. 

El segundo servicio que ofrece la aplicación es escanear y analizar el código de barras de productos e identificar su marca y la empresa productora. Después, la aplicación comprueba si estas actúan contra la filosofía de las campañas que el usuario seleccionó.

Texto completo en: http://actualidad.rt.com/actualidad/view/94880-aplicacion-boicotear-monsanto-gmo-eeuu

Accumulation of marine floating debris originated from highly populated coastal regions

 

Plastic pollution in the oceans represents a major global environmental challenge. At a global scale, man-made debris has been observed to accumulate in remote areas of the ocean in large circulating gyres. The source of this plastic is assumed to be mostly land based, however little is known about the relative contribution of different land based sources to each gyre.

Did you know there’s new information collected about you, every time you go to the doctor? But what happens to that data after you leave? Roughly 80 percent of collected health data is stored in hundreds of different forms such as lab results, images and medical transcripts, making it virtually useless.

 

That’s why health-care organizations are leveraging big data technology to capture patient information. The idea is to improve health care through care coordination, population health management and patient engagement and outreach.

 

Marty Kohn, chief medical scientist for IBM Research and a former ER doctor said, “The U.S. lags most other countries in health care. Our health-care system needs a transformation to compare to those around the world. We need to make it more personalized to make it more efficient and safer.”

Kohn offered three examples of how big data is already transforming patient health care at various organizations.

 

Data-driven decisions: This is when new evidence, or secondary evidence, is drawn from existing data. Big data can search for patient similarities through thousands of characteristics to help diagnose a problem.

 

Stream computing: In stream computing, data is not collected and stored. It’s used “near real-time,” or the time minus minimal processing delays.

 

At The Hospital for Sick Children in Toronto, for example, every baby in the neo-natal ICU has vitals monitored and can predict an upcoming problem before it happens. Hospital staff will be alerted to a life-threatening infection up to 24 hours earlier than current practices.

 

Patient Care and Insight: This third use involves predictive data analysis for high-risk patients.

 

Kohn said using the information around us will help doctors make better decisions. Technology enables doctors and health-care providers to create better health-care patterns for the future, he said.

At the end of 2012, comScore estimated there were 52.4 million tablet owners in the U.S.; Applesold another 19.5 million iPads in the first three months of 2013 alone. So it shouldn’t come as a surprise that some companies, such as Roambi, Tableau, and Bloomberg are starting to offer mobile, touch-aware data visualization apps.

 

But dropping your desktop user interface onto a tablet doesn’t really take the best advantage of all of those touches and gestures now, does it?

 

................................................

 

here are plenty of open design questions to work out for touchable data visualization: How to make intuitive gestures that are easy to discover and remember, whether touch may have advantages in data storytelling interfaces, and how to blend gestures into more traditional UI designs, among others. And deep research questions are also waiting to be resolved. Petra Isenberg, a researcher at INRIA in France, published a paper on data visualization on interactive surfaces that stipulates some key questions: “[We] don’t fully understand how touching virtual data affects comprehension or memorability of information,” she writes.

So whether you’re a practitioner or a researcher, there is a lot to work on here. Not only will tablet usage continue to grow, but other opportunities for museum installations, kiosks, and large-format presentation systems offer plenty of use-contexts to explore data visualization that takes advantage of the full interaction bandwidth afforded by these new displays and devices

Chapters

1. “Introductory Lab.” Nowak, Michael and Daniel A. McFarland. 2010.

2. “Methodological Beginnings – Basic Triadic and Cohesion Measures.” Nowak, Michael and Daniel A. McFarland. 2010. 

3. “Clusters, Factions and Cores.” Nowak, Michael and Daniel A. McFarland. 

4. “Centralities and Their Interrelation.” Sukumaran, Abhay,Michael Nowak and Daniel A. McFarland.

5. "Affiliation Data and Network Mobility." Messing, Solomon and Daniel A. McFarland. 2010. 

6. "Structural Equivalences and Block-Modeling." Nowak, Michael, Solomon Messing, Sean J. Westwood and Daniel A. McFarland. 2010. 

7. “Peer Influence and QAP Regression." Messing, Solomon, Sean J. Westwood and Daniel A. McFarland. 2010.

8. "Exponential-Family Random Graph Models.” Westwood, Sean J. and Daniel A. McFarland. 2010.

9. "Converting igraph to SoNIA with R." Westwood, Sean J. and Daniel A. McFarland. 2010.

10. "rSoNIA and Visualizing Social Network Dynamics." Bender-deMoll, Skye and Daniel A. McFarland. 2010.