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Mashable always give misleading news with misleading titles and ridiculous analysis. In France, you cannot do neither good nor bad ad for any brand or company in a TV program (unless you pay your ad slot of course). With the coming of social networks, people advertise their page and by the way facebook and twitter. That’s why the ban comes to say that facebook and twitter are also brands and companies like others. Actually, you can say “Facebook” and “twitter” and whatever you want… in any TV program in France, but you cannot advertise for them. So please be less simplistic and a little more percise in you articles.

By this logic no personal brand (i.e. Brad Pitt, Angelina Jolie, and so on) could be mentioned without them paying for it. And by this logic, public relations could not exist as a profession in France.

most scholars, whatever their disciplinary background, do not publish negative results.

I would admire it more if he didn’t elsewhere dismiss qualitative literary analysis as “a theological exercise.” (Moretti does not subscribe to literary-analytic pluralism: he has suggested that distant reading should supplant, not supplement, close reading.) The counterpoint to theology is science, and reading Moretti, it’s impossible not to notice him jockeying for scientific status. He appears now as literature’s Linnaeus (taxonomizing a vast new trove of data), now as Vesalius (exposing its essential skeleton), now as Galileo (revealing and reordering the universe of books), now as Darwin (seeking “a law of literary ­evolution”).

Literature is an artificial universe, and the written word, unlike the natural world, can’t be counted on to obey a set of laws. Indeed, Moretti often mistakes metaphor for fact. Those “skeletons” he perceives inside stories are as imposed as exposed; and literary evolution, unlike the biological kind, is largely an analogy. (As the author and critic Elif Batuman pointed out in an n+1 essay on Moretti’s earlier work, books actually are the result of intelligent design.)

Literature, he argues, is “a collective system that should be grasped as such.” But this, too, is a theology of sorts — if not the claim that literature is a system, at least the conviction that we can find meaning only in its totality.

The idea that truth can best be revealed through quantitative models dates back to the development of statistics (and boasts a less-than-benign legacy). And the idea that data is gold waiting to be mined; that all entities (including people) are best understood as nodes in a network; that things are at their clearest when they are least particular, most interchangeable, most aggregated — well, perhaps that is not the theology of the average lit department (yet). But it is surely the theology of the 21st century.

3. Collaboration at scale Across many economies, the number of people who undertake knowledge work has grown much more quickly than the number of production or transactions workers. Knowledge workers typically are paid more than others, so increasing their productivity is critical. As a result, there is broad interest in collaboration technologies that promise to improve these workers' efficiency and effectiveness. While the body of knowledge around the best use of such technologies is still developing, a number of companies have conducted experiments, as we see in the rapid growth rates of video and Web conferencing, expected to top 20 per cent annually during the next few years.

4. The growing ‘Internet of Things' The adoption of RFID (radio-frequency identification) and related technologies was the basis of a trend we first recognised as "expanding the frontiers of automation." But these methods are rudimentary compared with what emerges when assets themselves become elements of an information system, with the ability to capture, compute, communicate, and collaborate around information—something that has come to be known as the "Internet of Things." Embedded with sensors, actuators, and communications capabilities, such objects will soon be able to absorb and transmit information on a massive scale and, in some cases, to adapt and react to changes in the environment automatically. These "smart" assets can make processes more efficient, give products new capabilities, and spark novel business models. Auto insurers in Europe and the United States are testing these waters with offers to install sensors in customers' vehicles. The result is new pricing models that base charges for risk on driving behavior rather than on a driver's demographic characteristics. Luxury-auto manufacturers are equipping vehicles with networked sensors that can automatically take evasive action when accidents are about to happen. In medicine, sensors embedded in or worn by patients continuously report changes in health conditions to physicians, who can adjust treatments when necessary. Sensors in manufacturing lines for products as diverse as computer chips and pulp and paper take detailed readings on process conditions and automatically make adjustments to reduce waste, downtime, and costly human interventions.

5. Experimentation and big data Could the enterprise become a full-time laboratory? What if you could analyse every transaction, capture insights from every customer interaction, and didn't have to wait for months to get data from the field? What if…? Data are flooding in at rates never seen before—doubling every 18 months—as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities and newly deployed smart assets. These trends are broadly known as "big data." Technology for capturing and analysing information is widely available at ever-lower price points. But many companies are taking data use to new levels, using IT to support rigorous, constant business experimentation that guides decisions and to test new products, business models, and innovations in customer experience. In some cases, the new approaches help companies make decisions in real time. This trend has the potential to drive a radical transformation in research, innovation, and marketing.

Using experimentation and big data as essential components of management decision making requires new capabilities, as well as organisational and cultural change. Most companies are far from accessing all the available data. Some haven't even mastered the technologies needed to capture and analyse the valuable information they can access. More commonly, they don't have the right talent and processes to design experiments and extract business value from big data, which require changes in the way many executives now make decisions: trusting instincts and experience over experimentation and rigorous analysis. To get managers at all echelons to accept the value of experimentation, senior leaders must buy into a "test and learn" mind-set and then serve as role models for their teams.

6. Wiring for a sustainable world Even as regulatory frameworks continue to evolve, environmental stewardship and sustainability clearly are C-level agenda topics. What's more, sustainability is fast becoming an important corporate-performance metric—one that stakeholders, outside influencers, and even financial markets have begun to track. Information technology plays a dual role in this debate: it is both a significant source of environmental emissions and a key enabler of many strategies to mitigate environmental damage. At present, information technology's share of the world's environmental footprint is growing because of the ever-increasing demand for IT capacity and services. Electricity produced to power the world's data centers generates greenhouse gases on the scale of countries such as Argentina or the Netherlands, and these emissions could increase fourfold by 2020. McKinsey research has shown, however, that the use of IT in areas such as smart power grids, efficient buildings, and better logistics planning could eliminate five times the carbon emissions that the IT industry produces.

7. Imagining anything as a service Technology now enables companies to monitor, measure, customise, and bill for asset use at a much more fine-grained level than ever before. Asset owners can therefore create services around what have traditionally been sold as products. Business-to-business (B2B) customers like these service offerings because they allow companies to purchase units of a service and to account for them as a variable cost rather than undertake large capital investments. Consumers also like this "paying only for what you use" model, which helps them avoid large expenditures, as well as the hassles of buying and maintaining a product.

In the IT industry, the growth of "cloud computing" (accessing computer resources provided through networks rather than running software or storing data on a local computer) exemplifies this shift. Consumer acceptance of Web-based cloud services for everything from e-mail to video is of course becoming universal, and companies are following suit. Software as a service (SaaS), which enables organisations to access services such as customer relationship management, is growing at a 17 per cent annual rate. The biotechnology company Genentech, for example, uses Google Apps for e-mail and to create documents and spreadsheets, bypassing capital investments in servers and software licenses. This development has created a wave of computing capabilities delivered as a service, including infrastructure, platform, applications, and content. And vendors are competing, with innovation and new business models, to match the needs of different customers.

8. The age of the multisided business model Multisided business models create value through interactions among multiple players rather than traditional one-on-one transactions or information exchanges. In the media industry, advertising is a classic example of how these models work. Newspapers, magasines, and television stations offer content to their audiences while generating a significant portion of their revenues from third parties: advertisers. Other revenue, often through subscriptions, comes directly from consumers. More recently, this advertising-supported model has proliferated on the Internet, underwriting Web content sites, as well as services such as search and e-mail (see trend number seven, "Imagining anything as a service," earlier in this article). It is now spreading to new markets, such as enterprise software: Spiceworks offers IT-management applications to 950,000 users at no cost, while it collects advertising from B2B companies that want access to IT professionals.

9. Innovating from the bottom of the pyramid The adoption of technology is a global phenomenon, and the intensity of its usage is particularly impressive in emerging markets. Our research has shown that disruptive business models arise when technology combines with extreme market conditions, such as customer demand for very low price points, poor infrastructure, hard-to-access suppliers, and low cost curves for talent. With an economic recovery beginning to take hold in some parts of the world, high rates of growth have resumed in many developing nations, and we're seeing companies built around the new models emerging as global players. Many multinationals, meanwhile, are only starting to think about developing markets as wellsprings of technology-enabled innovation rather than as traditional manufacturing hubs.

10. Producing public good on the grid The role of governments in shaping global economic policy will expand in coming years. Technology will be an important factor in this evolution by facilitating the creation of new types of public goods while helping to manage them more effectively. This last trend is broad in scope and draws upon many of the other trends described above.

There are already three heavyweight groups that could be considered the official keepers of the world's climate data. Each publishes its own figures that feed into the UN's Intergovernmental Panel on Climate Change. Nasa's Goddard Institute for Space Studies in New York City produces a rolling estimate of the world's warming. A separate assessment comes from another US agency, the National Oceanic and Atmospheric Administration (Noaa). The third group is based in the UK and led by the Met Office. They all take readings from instruments around the world to come up with a rolling record of the Earth's mean surface temperature. The numbers differ because each group uses its own dataset and does its own analysis, but they show a similar trend. Since pre-industrial times, all point to a warming of around 0.75C.

You might think three groups was enough, but Muller rolls out a list of shortcomings, some real, some perceived, that he suspects might undermine public confidence in global warming records. For a start, he says, warming trends are not based on all the available temperature records. The data that is used is filtered and might not be as representative as it could be. He also cites a poor history of transparency in climate science, though others argue many climate records and the tools to analyse them have been public for years.

Then there is the fiasco of 2009 that saw roughly 1,000 emails from a server at the University of East Anglia's Climatic Research Unit (CRU) find their way on to the internet. The fuss over the messages, inevitably dubbed Climategate, gave Muller's nascent project added impetus. Climate sceptics had already attacked James Hansen, head of the Nasa group, for making political statements on climate change while maintaining his role as an objective scientist. The Climategate emails fuelled their protests. "With CRU's credibility undergoing a severe test, it was all the more important to have a new team jump in, do the analysis fresh and address all of the legitimate issues raised by sceptics," says Muller.

This latest point is where Muller faces his most delicate challenge. To concede that climate sceptics raise fair criticisms means acknowledging that scientists and government agencies have got things wrong, or at least could do better. But the debate around global warming is so highly charged that open discussion, which science requires, can be difficult to hold in public. At worst, criticising poor climate science can be taken as an attack on science itself, a knee-jerk reaction that has unhealthy consequences. "Scientists will jump to the defence of alarmists because they don't recognise that the alarmists are exaggerating," Muller says.

The Berkeley Earth project came together more than a year ago, when Muller rang David Brillinger, a statistics professor at Berkeley and the man Nasa called when it wanted someone to check its risk estimates of space debris smashing into the International Space Station. He wanted Brillinger to oversee every stage of the project. Brillinger accepted straight away. Since the first meeting he has advised the scientists on how best to analyse their data and what pitfalls to avoid. "You can think of statisticians as the keepers of the scientific method, " Brillinger told me. "Can scientists and doctors reasonably draw the conclusions they are setting down? That's what we're here for."

For the rest of the team, Muller says he picked scientists known for original thinking. One is Saul Perlmutter, the Berkeley physicist who found evidence that the universe is expanding at an ever faster rate, courtesy of mysterious "dark energy" that pushes against gravity. Another is Art Rosenfeld, the last student of the legendary Manhattan Project physicist Enrico Fermi, and something of a legend himself in energy research. Then there is Robert Jacobsen, a Berkeley physicist who is an expert on giant datasets; and Judith Curry, a climatologist at Georgia Institute of Technology, who has raised concerns over tribalism and hubris in climate science.

Robert Rohde, a young physicist who left Berkeley with a PhD last year, does most of the hard work. He has written software that trawls public databases, themselves the product of years of painstaking work, for global temperature records. These are compiled, de-duplicated and merged into one huge historical temperature record. The data, by all accounts, are a mess. There are 16 separate datasets in 14 different formats and they overlap, but not completely. Muller likens Rohde's achievement to Hercules's enormous task of cleaning the Augean stables.

The wealth of data Rohde has collected so far – and some dates back to the 1700s – makes for what Muller believes is the most complete historical record of land temperatures ever compiled. It will, of itself, Muller claims, be a priceless resource for anyone who wishes to study climate change. So far, Rohde has gathered records from 39,340 individual stations worldwide.

Publishing an extensive set of temperature records is the first goal of Muller's project. The second is to turn this vast haul of data into an assessment on global warming.

The big three groups – Nasa, Noaa and the Met Office – work out global warming trends by placing an imaginary grid over the planet and averaging temperatures records in each square. So for a given month, all the records in England and Wales might be averaged out to give one number. Muller's team will take temperature records from individual stations and weight them according to how reliable they are.

This is where the Berkeley group faces its toughest task by far and it will be judged on how well it deals with it. There are errors running through global warming data that arise from the simple fact that the global network of temperature stations was never designed or maintained to monitor climate change. The network grew in a piecemeal fashion, starting with temperature stations installed here and there, usually to record local weather.

Among the trickiest errors to deal with are so-called systematic biases, which skew temperature measurements in fiendishly complex ways. Stations get moved around, replaced with newer models, or swapped for instruments that record in celsius instead of fahrenheit. The times measurements are taken varies, from say 6am to 9pm. The accuracy of individual stations drift over time and even changes in the surroundings, such as growing trees, can shield a station more from wind and sun one year to the next. Each of these interferes with a station's temperature measurements, perhaps making it read too cold, or too hot. And these errors combine and build up.

This is the real mess that will take a Herculean effort to clean up. The Berkeley Earth team is using algorithms that automatically correct for some of the errors, a strategy Muller favours because it doesn't rely on human interference. When the team publishes its results, this is where the scrutiny will be most intense.

Despite the scale of the task, and the fact that world-class scientific organisations have been wrestling with it for decades, Muller is convinced his approach will lead to a better assessment of how much the world is warming. "I've told the team I don't know if global warming is more or less than we hear, but I do believe we can get a more precise number, and we can do it in a way that will cool the arguments over climate change, if nothing else," says Muller. "Science has its weaknesses and it doesn't have a stranglehold on the truth, but it has a way of approaching technical issues that is a closer approximation of truth than any other method we have."

It might not be a good sign that one prominent climate sceptic contacted by the Guardian, Canadian economist Ross McKitrick, had never heard of the project. Another, Stephen McIntyre, whom Muller has defended on some issues, hasn't followed the project either, but said "anything that [Muller] does will be well done". Phil Jones at the University of East Anglia was unclear on the details of the Berkeley project and didn't comment.

Elsewhere, Muller has qualified support from some of the biggest names in the business. At Nasa, Hansen welcomed the project, but warned against over-emphasising what he expects to be the minor differences between Berkeley's global warming assessment and those from the other groups. "We have enough trouble communicating with the public already," Hansen says. At the Met Office, Peter Stott, head of climate monitoring and attribution, was in favour of the project if it was open and peer-reviewed.

Peter Thorne, who left the Met Office's Hadley Centre last year to join the Co-operative Institute for Climate and Satellites in North Carolina, is enthusiastic about the Berkeley project but raises an eyebrow at some of Muller's claims. The Berkeley group will not be the first to put its data and tools online, he says. Teams at Nasa and Noaa have been doing this for many years. And while Muller may have more data, they add little real value, Thorne says. Most are records from stations installed from the 1950s onwards, and then only in a few regions, such as North America. "Do you really need 20 stations in one region to get a monthly temperature figure? The answer is no. Supersaturating your coverage doesn't give you much more bang for your buck," he says. They will, however, help researchers spot short-term regional variations in climate change, something that is likely to be valuable as climate change takes hold.

Despite his reservations, Thorne says climate science stands to benefit from Muller's project. "We need groups like Berkeley stepping up to the plate and taking this challenge on, because it's the only way we're going to move forwards. I wish there were 10 other groups doing this," he says.

Muller's project is organised under the auspices of Novim, a Santa Barbara-based non-profit organisation that uses science to find answers to the most pressing issues facing society and to publish them "without advocacy or agenda". Funding has come from a variety of places, including the Fund for Innovative Climate and Energy Research (funded by Bill Gates), and the Department of Energy's Lawrence Berkeley Lab. One donor has had some climate bloggers up in arms: the man behind the Charles G Koch Charitable Foundation owns, with his brother David, Koch Industries, a company Greenpeace called a "kingpin of climate science denial". On this point, Muller says the project has taken money from right and left alike.

No one who spoke to the Guardian about the Berkeley Earth project believed it would shake the faith of the minority who have set their minds against global warming. "As new kids on the block, I think they will be given a favourable view by people, but I don't think it will fundamentally change people's minds," says Thorne. Brillinger has reservations too. "There are people you are never going to change. They have their beliefs and they're not going to back away from them."

How can we assess the competence of a scientist? Past performance is, realistically, the only way to judge future performance. Past performance can only be assessed by looking at their publications. Were they in a similar area? Are they considered significant? Are they numerous? Curiously, though, the second question is also answered by looking at publications—if a topic is considered significant, then there will be lots of publications in that area, and those publications will be of more general interest, and so end up in higher ranking journals.

So we end up in the situation that the editors of major journals are in the position to influence the direction of scientific funding, meaning that there is a huge incentive for everyone to make damn sure that their work ends up in Science or Nature. But why are Science, Nature, and PNAS considered the place to put significant work? Why isn't a new optical phenomena, published in Optics Express, as important as a new optical phenomena published in Science?

The big three try to be general; they will, in principle, publish reports from any discipline, and they anticipate readership from a range of disciplines. This explicit generality means that the scientific results must not only be of general interest, but also highly significant. The remaining journals become more specialized, covering perhaps only physics, or optics, or even just optical networking. However, they all claim to only publish work that is highly original in nature.

Are standards really so different? Naturally, the more specialized a journal is, the fewer people it appeals to. However, the major difference in determining originality is one of degree and referee. A more specialized journal has more detailed articles, so the differences between experiments stand out more obviously, while appealing to general interest changes the emphasis of the article away from details toward broad conclusions.

as the audience becomes broader, more technical details get left by the wayside. Note that none of the gene sequences published in Science have the actual experimental and analysis details. What ends up published is really a broad-brush description of the work, with the important details either languishing as supplemental information, or even published elsewhere, in a more suitable journal. Yet, the high profile paper will get all the citations, while the more detailed—the unkind would say accurate—description of the work gets no attention.

And that is how journals are ranked. Count the number of citations for each journal per volume, run it through a magic number generator, and the impact factor jumps out (make your checks out to ISI Thomson please). That leaves us with the following formula: grants require high impact publications, high impact publications need citations, and that means putting research in a journal that gets lots of citations. Grants follow the concepts that appear to be currently significant, and that's decided by work that is published in high impact journals.

This system would be fine if it did not ignore the fact that performing science and reporting scientific results are two very different skills, and not everyone has both in equal quantity. The difference between a Nature-worthy finding and a not-Nature-worthy finding is often in the quality of the writing. How skillfully can I relate this bit of research back to general or topical interests? It really is this simple. Over the years, I have seen quite a few physics papers with exaggerated claims of significance (or even results) make it into top flight journals, and the only differences I can see between those works and similar works published elsewhere is that the presentation and level of detail are different.

articles from the big three are much easier to cover on Nobel Intent than articles from, say Physical Review D. Nevertheless, when we do cover them, sometimes the researchers suddenly realize that they could have gotten a lot more mileage out of their work. It changes their approach to reporting their results, which I see as evidence that writing skill counts for as much as scientific quality.

If that observation is generally true, then it raises questions about the whole process of evaluating a researcher's competence and a field's significance, because good writers corrupt the process by publishing less significant work in journals that only publish significant findings. In fact, I think it goes further than that, because Science, Nature, and PNAS actively promote themselves as scientific compasses. Want to find the most interesting and significant research? Read PNAS.

The publishers do this by extensively publicizing science that appears in their own journals. Their news sections primarily summarize work published in the same issue of the same magazine. This lets them create a double-whammy of scientific significance—not only was the work published in Nature, they also summarized it in their News and Views section.

Very few of the other journals do this. I don't get early access to the Physical Review series, even though I love reporting from them. In fact, until this year, they didn't even highlight interesting papers for their own readers. This makes it incredibly hard for a science reporter to cover science outside of the major journals. The knock-on effect is that Applied Physics Letters never appears in the news, which means you can't evaluate recent news coverage to figure out what's of general interest, leaving you with... well, the big three journals again, which mostly report on themselves. On the other hand, if a particular scientific topic does start to receive some press attention, it is much more likely that similar work will suddenly be acceptable in the big three journals.

That said, I should point out that judging the significance of scientific work is a process fraught with difficulty. Why do you think it takes around 10 years from the publication of first results through to obtaining a Nobel Prize? Because it can take that long for the implications of the results to sink in—or, more commonly, sink without trace.

I don't think that we can reasonably expect journal editors and peer reviewers to accurately assess the significance (general or otherwise) of a new piece of research. There are, of course, exceptions: the first genome sequences, the first observation that the rate of the expansion of the universe is changing. But the point is that these are exceptions, and most work's significance is far more ambiguous, and even goes unrecognized (or over-celebrated) by scientists in the field.

The conclusion is that the top three journals are significantly gamed by scientists who are trying to get ahead in their careers—citations always lag a few years behind, so a PNAS paper with less than ten citations can look good for quite a few years, even compared to an Optics Letters with 50 citations. The top three journals overtly encourage this, because it is to their advantage if everyone agrees that they are the source of the most interesting science. Consequently, scientists who are more honest in self-assessing their work, or who simply aren't word-smiths, end up losing out.

scientific competence should not be judged by how many citations the author's work has received or where it was published. Instead, we should consider using a mathematical graph analysis to look at the networks of publications and citations, which should help us judge how central to a field a particular researcher is. This would have the positive influence of a publication mattering less than who thought it was important.

Science and Nature should either eliminate their News and Views section, or implement a policy of not reporting on their own articles. This would open up one of the major sources of "science news for scientists" to stories originating in other journals.

One might think that such an esteemed organization would prove an insurmountable challenge for a bunch of disaffected kids to hack. World-renowned, government-recognized experts against Anonymous? HBGary should be able to take their efforts in stride. Unfortunately for HBGary, neither the characterization of Anonymous nor the assumption of competence on the security company's part are accurate, as the story of how HBGary was hacked will make clear. Anonymous is a diverse bunch: though they tend to be younger rather than older, their age group spans decades. Some may still be in school, but many others are gainfully employed office-workers, software developers, or IT support technicians, among other things. With that diversity in age and experience comes a diversity of expertise and ability.

consistent with George's analysis, authorities last week relaxed past regulations that limited the use of the Internet and social media for election campaigning. Political parties and candidates will be allowed to use a broader range of new media platforms, including blogs, micro-blogs, online photo-sharing platforms, social networking sites and electronic media applications used on mobile phones, for election advertising. The loosening, however, only applies for political party-run websites, chat rooms and online discussion forums. Candidates must declare the new media content they intend to use within 12 hours after the start of the election campaign period. George warned in a recent blog entry that the new declaration requirements could open the way for PAP-led defamation suits against new media using opposition politicians. PAP leaders have historically relied on expensive litigation to suppress opposition and media criticism. "The PAP won't subject everyone's postings to legal scrutiny. But if it decides that a particular opposition politician needs to be utterly demolished, you can bet that no tweet of his would be too tiny, no Facebook update too fleeting ... in order a build the case against the individual," George warned in a journalism blog.

While opposition politicians will rely more on new than mainstream media to communicate with voters, they already recognize that the use of social media will not necessarily translate into votes. "[Online support] can give a too rosy a picture and false degree of comfort," said the RP's Jeyaretnam. "People who [interact with] us online are those who are already convinced with our messages anyway."

“Companies will become more transparent as a necessity – customers now see that as an essential part of the trust equation.” The bigger impact may come from the technology that is making access to this data a mobile phenomenon. “This industry is de-linking access to data from physical location,” he says. In a world where shoppers can check out the competition’s prices while they’re in your store, keeping control of data is no longer an option.

for now, managing the information out there is the priority. Access to information was once the big problem

Then it quickly flipped, through technology, to data overload. “We were brought up to believe more data was good, and that’s no longer true,” he argues.

Laurence refuses to read reports from his product managers with more than five of the vital key performance indicators on them. “The amount of data is obscene. The managers that are going to be successful are going to be the ones who are prepared to take a knife to the amount of data… Otherwise, it’s like a virus.

Data plus hunch equals a powerful combination. Or, as Laurence concludes: “Data on its own is impotent.”