Craig Mundie is a geek, and I mean that in the best possible way. Microsoft’s chief research and strategy officer, the 17-year veteran of Redmond, WA, still talks like an engineer, throwing out terms like “heterogeneous machine architectures,” “GUIs” (graphical user interfaces), and “clouds and clients” like there’s no tomorrow. It’s kind of refreshing, given that he is in charge of setting the long-term agenda for one of the most powerful companies on the planet.

Mundie is in the midst of a weeklong tour of some top universities around the country. He called me yesterday from Cambridge, MA, where he had just finished a presentation to Harvard University students, faculty, and guests. He visits the University of Illinois at Urbana-Champaign (my alma mater) today, and comes to Kane Hall at the University of Washington tomorrow afternoon. It’s similar to the college tours Bill Gates used to do.

From what I can tell, the goal is to stir up interest in computer science, give audiences a glimpse of future computing systems as Microsoft sees them, and stimulate discussions about how these technologies can help solve some pressing global problems. (You can read more about Mundie’s tour and demos in this Seattle Times story.)

Besides hearing Mundie’s thoughts on computer science education and the future of computing, I wanted to drill down and ask him about the challenge of taking on Microsoft’s strategy development (after Gates stepped down last year) in the most difficult economic times in recent memory. I also wanted to ask him about the deeper culture of Microsoft, the renewed role of research in the company’s future, and the importance of nurturing relationships around the world—and his secret ally in that quest.

Here are some edited highlights from our conversation:

Xconomy: What are you trying to get across to university audiences on this tour?

Craig Mundie: In these presentations, I’m trying to get them to think not only about how computing evolves, but with that evolution, what kinds of problems will become approachable, and what are the new methods? Several things are evolving in parallel [and leading to more heterogeneous and complex machines]. That begets the requirement of how to do programming around parallel computing. With very high-scale computing facilities, the cloud and the client come together to form one system that people will program. They will use those things together with new display and sensing technologies.

Just as the GUI revolutionized computing, we could see a similar revolution with more natural interactions with machines, rather than just “type and point and click.” That will expand the number of people who can interact with computers. With the diversity, rooms can become computers [for instance]. You won’t think of them so much as a computer.

X: What are some of the global problems you think advanced computing will help solve?

CM: Beyond the computer science realm, I’ve talked about energy and the environment. I show one piece of research work we’re doing to compose computational models, a simplified climate model, at Princeton and Microsoft Research. It shows linkages between deforestation in the Amazon and atmospheric temperatures around the rest of the world. If you were a policy person, these kinds of things would give you tools to support your decision making.

In energy, we’re doing computer modeling and direct visualizations. I showed a model, loaned to us from TerraPower [the nuclear power firm spun off from Nathan Myhrvold’s Intellectual Ventures …Next Page »

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From the seas to the stars, Microsoft Research is trying to increase its impact. The Redmond, WA-based computer science research organization is releasing new software tools aimed at helping scientists manage and visualize huge amounts of information, and make discoveries in fields as diverse as astronomy and oceanography. The announcement of the free tools, called Project Trident, is being made today at the 10th annual Microsoft Research Faculty Summit in Redmond.

Everyone knows information overload is a huge issue. Just try being a scientist these days. With increasing amounts of data available from the Internet, satellites, telescopes, cameras, gene sequencers, and networked sensors, researchers—and organizations in general—are looking for ways to cut through the deluge and focus faster on doing the analysis and getting results, rather than sorting through data.

It’s also a problem faced by big companies, financial analysts, and medical institutions. So, ultimately, Project Trident is not aimed at spearing purely scientific research problems—it’s software that also could yield big results for business down the road. “If we look back at the challenges faced in business, scientists were facing them years if not decades before,” says Roger Barga, a Microsoft researcher and principal architect on Project Trident. “We’re getting an early look at what our business customers will expect in their products in 3-5 years. It’s pushing another Microsoft [Windows] platform into new areas.”

Project Trident started around 2006, when Barga began collaborating with legendary Microsoft researcher Jim Gray (who was lost at sea in January 2007) on tools to help oceanographers make sense of volumes of data on things like temperature, salinity, and the physics of seafloor hydrothermal vents. “There’s a clear understanding of the science and how to put instruments in the ocean, but there’s a gap in how to convert data streaming in from the ocean to useful analysis,” Barga says. “Jim had this vision of …Next Page »

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If there’s a theme to be found in the innovation news for San Diego last week, it might be comings and goings. While some companies are making layoffs or even shuttering their doors, we also found a number of new startups taking root here (although not as many as a year ago).

—In a report on San Diego’s innovation economy, the non-profit business group Connect found 73 new technology companies were started here during the last three months of 2008, a 58 percent decline compared to the year-ago period. It’s a sign the local tech economy is down, but not out.

—Luke profiled Amira Pharmaceuticals, a biotech startup founded in 2005 that is developing a drug to treat pulmonary fibrosis. In this recession, it’s worth noting that the three scientists who started Amira joined forces after Merck had shut down the San Diego operation where they had worked.

—A different kind of start-over is San Diego-based SpectraScience (OTCBB: SCIE). After salvaging the biomedical equipment maker from bankruptcy in 2004, local entrepreneur Jim Hitchin is just beginning to sell the company’s updated “optical biopsy” machines. The technology combines a low-power, fiber-optic blue laser with computerized spectroscopy.

—Another new biotech that Luke profiled is San Diego’s Pico Pharmaceuticals. The company is using research out of New York’s Albert Einstein College of Medicine to develop highly specific small molecule drugs that bind more tightly to their receptor targets.

—JP (Juha-Pekka) found that Dotmatics, a U.K. bioinformatics and visualization software developer, has opened a satellite office near San Diego as part of its expansion into the U.S. life sciences market.

—Sorenson Media, a Salt Lake City-based developer of video compression and encoding software, also has opened a new San Diego office to serve as the central hub of its business operations.

—On the other side of the ledger, I rounded up more layoffs that have come to light in San Diego in recent weeks. They included specialized laser maker Cymer, which with its latest round of 130 cuts has eliminated 38 percent of its workforce since …Next Page »

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Xconomy chose to set up shop in Kendall Square because we wanted to be at the epicenter of investment and innovation in the Boston area. But it was just luck that we ended up right across the street from IBM’s Cambridge research facility at 1 Rogers Street, which is home to both the Collaborative User Experience (CUE) Research group and the new Center for Social Software. The creative software engineers, user interface designers, and visualization researchers in the group have come up with a whole gallery of fascinating tools for studying the way business people (and average Web surfers) interact with data, including Many Eyes, a community portal for visualization experiments.

But one of the Web-based applications included in Many Eyes has taken on a surprising life of its own outside IBM. It’s a free visualization tool called Wordle, where users can dump a bunch of text into a window and then see it automatically yet artfully arranged into a cloud of words, with the size of each word corresponding to its frequency in the original passage. As the Wordle site puts it, it’s “a toy for generating ‘word clouds’ from text that you provide.”

These aren’t your father’s tag clouds: they’re playful, colorful, and made from attractive fonts. And they fill up the space around their center points in a clever way that often seems to say something profound about the nature of the ideas in the text. In fact, Wordle achieved minor fame during the 2008 presidential campaign, when several newspapers and other media outlets used the tool to analyze publications and speeches by the major candidates. It’s also found its way into popular culture: a Google image search for Wordle diagrams turns up more than 200,000 examples. (The Wordle word cloud on this page is based on the text of this article, and the one on page 2 is based in Lincoln’s Gettysburg Address.)

I dropped by the CUE Research group’s offices several weeks ago for a conversation with Wordle’s creator and shepherd, Jonathan Feinberg. Though Feinberg is a senior software engineer at CUE, he developed Wordle as a personal project, and maintains it on a server outside of IBM. Martin Wattenberg, a mathematician who lead’s the CUE Research group’s Visual Communications Lab, was also on hand for the talk. Below is an abridged transcription.

Xconomy: Where did Wordle come from?

Jonathan Feinberg: It came from a Lotus project I worked on called Dogear. It was a social bookmarking engine. In every piece of social software there’s a tag cloud, and I have implemented some, but I thought they were ugly and boring. I was prompted by Dogear to think about the ways you could fit words together on a page. The core bit of code I wrote was a Java applet within Dogear called TagExplorer, but when Dogear came out as a product and TagExplorer was not part of it, because Java applets are considered too slow to load. Then two years later, while clearing out one of my workspaces, I stumbled onto the code and thought I’d like to do something with it. That’s when I built Wordle. So, the sand that formed the pearl was a tag cloud, but it’s really divorced from that idea now.

There was no way to put it out there as a branded IBM thing. I didn’t even begin working on the real Web application for Wordle until I had gotten permission to use the code externally. The lawyers and the product managers didn’t want this code for a product, and I got permission to use it non-commercially—which serviced me well, because I don’t like doing business. So Wordle the Web app belongs to me personally, not ManyEyes.

Martin Wattenberg: But ManyEyes has Wordle in it, and it’s become one of the most popular visualization types on ManyEyes.

X: What’s really wrong with conventional tag clouds?

MW: If you look at how the academic community has viewed things like tag clouds, it’s been with a certain amount of suspicion and skepticism about what they convey. And that skepticism has been backed up by studies. If you are going to try to convey a list of word frequencies and measure what people remember about a text, it’s not clear that tag clouds give you any benefit over, say, a list of words ordered by frequency.

That said, when Wordle went up, Jon positioned it as a toy. To me there is a fine line between a toy and an experiment. We’ve had thousands of people from all over the Web experimenting with Wordle and finding all sorts of things to do with it. There is a blog on the top 25 uses for Wordle. For me that is an indication that there is a lot more to it than just being a toy. There are teachers who have found that it’s extremely useful as part of their teaching. And maybe if you are analyzing a text very serious, a Wordle diagram has no advantage over a list of word frequencies. But if you are trying to convey something emotionally, Wordle has a huge advantage.

There is this analogy with cameras. A Wordle is almost like a Polaroid camera for text. It lets people take snapshots that mean something to them. We’ve found more than one blog where guys talk about getting “boyfriend points” by making Wordles out of their love letters to their girlfriends. All of these things point to really interested new uses of visualization.

JF: But how am I ever going to get back all of the husband points I lost by spending all that time making Wordle?

MW: One of the interesting things we’ve seen is a bunch of fairly high profile media outlets like the Boston Globe and the Washington Post have used Wordles to illustrate articles about speeches. That indicates that it is in some sense more than a toy. Poeple who are professional political analysts find this an interesting way to illustrate their points. Jon looked at tag clouds, thought about what was wrong with them, and created this fantastic alterantive. And by putting it on the Web, we’ve seen ways that it’s useful that I don’t think we would have invented ourselves or trusted. It’s a little counterintuitive, and it’s certianly contrary to the usual paradigm of interface design, were you have a task in mind and an audience in mind before you start.

JF: Calling it a toy was a defensive measure. I don’t want to make any claims for Wordle as a visualization tool that gets you an accurate idea of your text. People write to me and say ‘Wow, I made a Wordle and now I see wasn’t writing about what I thought I was writing about.’ But I feel very resistant to those kinds of analyses.

MW: That raises a research question about what people are getting out of this way of visualizing text and what they think they’re getting. Wordle really is the starting point of an important line of research. We are looking at the way it’s being used, and are in the midst of writing our first paper on it. By putting it out in public without making any strong claims about it, we get to see …Next Page »

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Seattle data-visualization firm Tableau Software announced its 16th consecutive quarter of record sales, and a host of new customers acquired in the last three months of 2008. Tableau’s new customers include AAA Allied Group, Active Network, Mitel Networks, the University of Texas at El Paso, and U.S. Auto Parts.

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Everybody should be back from vacation, and the deal flow surging—but someone forgot to tell the dealmakers, as the past week was pretty light for Seattle tech and life sciences action.

—In a deal worth approximately $131 million, Bellevue, WA-based Captaris (NASDAQ: CAPA), which makes business and documents management software, announced it is being acquired by Open Text, a business-software company based in Waterloo, Ontario.

—Tableau Software, a Seattle maker of data visualization tools, announced it has raised a $10 million Series B round from New Enterprise Associates. The funds will be used to expand the sales and product lines of Tableau, which is already profitable and selling its software to customers like Microsoft, Google, and Yahoo.

—Bothell, WA-based biotech company Acucela partnered with Tokyo-based Otsuka Pharmaceutical to develop ACU-4429, its lead drug candidate for the “dry” form of macular degeneration, the top cause of blindness among the elderly. Under the deal, Acucela will receive $5 million up front, and potential milestone payments worth $258 million, with the companies divvying up expenses and profits around the world should ACU-4429 get to market.

—Seattle biotech ZymoGenetics (NASDAQ: ZGEN) agreed to hand over its rights to atacicept—its leading drug candidate for autoimmune diseases like lupus, rheumatoid arthritis, and multiple sclerosis—to its partner, Merck KGaA. Darmstadt, Germany-based Merck, which will now have 100 percent of the worldwide commercial rights to the drug, will pay for all of atacicept ’s development costs, potentially saving ZymoGenetics more than $200 million over the next several years as the drug advances through the last stages of clinical trials.

—Oncothyreon (NASDAQ: ONTY), a Seattle biotech company developing drugs against cancer, said it will sell 5.1 million additional shares of stock in the second week of September. The company plans to use the proceeds to support clinical trials of two of its drugs in development, PX-478 and PX-866, and seek a partner to further develop another drug, PX-12.

—Amazon is teaming up with Cambridge, MA-based One Laptop Per Child Foundation. The “Give One, Get One” program offered by OLPC last holiday season gave U.S. and Canadian consumers the opportunity to buy two XO laptops for $400: one for themselves, the other for a child in a developing country. But the implementation, as Wade noted, “was a fiasco.” This holiday season, OLPC plans to repeat the offer—but it’s put Amazon in charge. If any company can fulfill orders during the holidays, it’s Amazon.

—It wasn’t about one particular deal, but a host of them, past and future, as Greg got the lowdown on why the Seattle startup community wants Bay Area VCs to spend more time in Seattle. (Hint: it might not just be the money.)

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In February 2006, Swedish physician, statistician, and global health expert Hans Rosling brought down the house at TED (the Technology, Entertainment, and Design conference in Monterey, CA) with a presentation on health and economic trends in developing nations. But it wasn’t the content of the presentation so much as the software he was using that grabbed the audience: called Trendalyzer, the program converted Rosling’s data into colorful animated graphs. By representing countries as dots of varying size that moved against the x and y axes over time, Trendalyzer brought vivid life to changes such as the last century’s general improvements in income and life expectancy—and highlighted how health and wealth in once-lagging regions such as Asia have surged ahead, while they have improved much more slowly in areas such as sub-Saharan Africa.

To many in the audience (and to me, when I watched the online video of Rosling’s TED talk), the Trendalyzer presentation was a revelation, seemingly heralding a new era in which clever design choices coupled with serious graphics-processing power would cause all sorts of interesting trends in complex data to leap out at computer users. Indeed, the next year, Google announced that it had acquired the Trendalyzer software from Rosling’s non-profit Gapminder Foundation, saying that it hoped to improve and expand Trendalyzer and make it “freely available to any and all users capable of thinking outside the X and Y axes.” Unfortunately, like many other early-stage technologies that get anointed by the massive buzz amplifier that is TED, Trendalyzer has since receded from view. Google hasn’t done much with the software, beyond making a Trendalyzer-like gadget called “MotionChart” available as part of Google Spreadsheets.

Meanwhile, there’s a company in Newton, MA, that has spent the better part of this decade quietly applying many of the same design principles behind Trendalyzer to business problems—and selling its software, to boot. It’s called Visual I|O, and I spent some time recently learning about the company’s remarkably beautiful Web-based business analytics software, called DecisionIris, from company co-founder, president, and CEO Angela Shen-Hsieh.

Now, that’s probably the first time I’ve ever used “beautiful” and “business analytics software” in the same sentence. While Visual I|O markets DecisionIris as a business intelligence tool, and making sense of complex business data is certainly one of its strengths, it would be grossly unfair to lump the program in with the kinds of graphical tools offered by traditional business intelligence companies like SAP and Cognos, which are closer to the primitive chart wizards in Microsoft Excel than to anything a professional information designer might conceive. If you’re an aficionado of the work of Yale information designer Edward Tufte—author of The Visual Display of Quantitative Information and Visual Explanations and the man the New York Times has described as “the da Vinci of data”—then you will immediately feel at home with the way DecisionIris represents logical relationships and changes over time, and with the innate sense of color and proportion built into the software.

I’m gushing, I know, but bear with me. The program’s beauty is undoubtedly traceable to the fact that Shen-Hsieh and her fellow co-founder Mark Schindler are both Harvard-trained architects, not software engineers. The pair created Visual I|O as a spinoff of Chicago-based consulting firm Schindler + Associates (where Mark was a partner) in 2002; they wanted to take the visualization software the firm had created to help clients such as pharmaceutical companies get a high-level view of their data and turn it into a commercial product.

Shen-Hsieh (pronounced “shen-shay”) and Schindler felt sure that there was a larger market for software that would help business managers visualize data more flexibly—switching between space-based and time-based representations, for example—depending on the kinds of insights being sought. After all, why go the trouble of collecting terabytes of data about a company’s performance and assembling it into huge, expensive databases and data warehouses if you can’t play with it at will? “If you look at the history of information technology, so much of it is focused on storing and accessing data,” Shen-Hsieh says. “We focus in the last 18 inches–from the screen to the brain. We’re about the cognitive piece.”

Since a picture equals one kiloword, I’ll refer you at this point to the picture at right. It’s a screen shot from a demo Shen-Hsieh walked me through, based on real data about residential properties for sale in the Boston suburbs of Brookline, Newton, Waltham, and Watertown. It illustrates how DecisionIris can help users draw meaning from a mess of data by bringing out multiple dimensions of the data simultaneously; an example about real estate seems easier for most people to relate to than heavy business analytics. (Click on the picture for a larger version.)

Each dot in the chart represents a house. The size of the dot represents the house’s asking price, and its color shows which town it’s in—Brookline is purple, Newton is blue, Waltham is green, and Watertown is yellow. The horizontal axis indicates the year the house was built, and the vertical axis indicates its square footage. (Notice how that’s already four dimensions of data, packed into a type of graph usually used for no more than two dimensions.)

What observations can be drawn from the chart? Well, right away, it’s obvious that houses for sale in Newton are older, bigger, and more expensive than houses in the other cities. That makes sense, given that Newton (where Visual I|O happens to be located) was one of Boston’s first major suburbs, and is still home to …Next Page »

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With the wrong visualization tools, data can be deathly boring—just think of all the dry, meaningless PowerPoint presentations and Excel spreadsheets you’ve endured in darkened lecture halls and conference rooms. But with the right tools and context, data can come alive, as Yale information designer Edward Tufte has famously argued and you’ll understand yourself if you’ve seen the inspiring 2006 and 2007 TED videos of Swedish researcher Hans Rosling using his Trendalyzer software to illustrate global demographic trends.

The folks at IBM’s Lotus division also seem to understand the power of good data graphics, and last week I had the opportunity to walk across Rogers Street from the Xconomy world headquarters to the division’s Cambridge lab to talk with the brains behind Many Eyes, the company’s grand experiment in collaborative data visualization.

At the Many Eyes portal, anyone can register for a free account, upload a data set, and select one of about 16 ways to display it, from a traditional bar chart or fever chart to a sophisticated scatter plot, tag cloud, or treemap. For example, here’s a tag cloud I created in about 15 minutes, by pasting the text from last week’s Xconomy blog posts (excluding news briefs) into the Many Eyes upload page.

Click on this graphic to go to a live version of the tag cloud, where you can mouse over individual words to see how many times they turned up in our stories. Be sure to try visualizing using both the one-word and two-word modes by clicking the radio buttons. In one-word mode, you’ll see that the most common word in Xconomy stories last week—and probably every week—was “company,” followed by “Taylor” (Eons CEO Bill Taylor was the subject of a long profile by Bob on October 30) and “EMC” (which has captured a lot of mindshare recently due to a string of acquisitions and the mind-boggling rise of share prices in its subsidiary VMware). The most common two-word phrases were “Virtual Iron” (a VMware competitor), “gene therapy,” and “operating systems.”

None of that is particularly earthshaking, of course. But it’s fun. It’s the kind of information that would have been hard to obtain before Many Eyes came along without resorting to specialized software. And most importantly, it’s shared. If you clicked on the tag cloud graphic above, it took you to a public Many Eyes page, where anybody can view it and opine upon it.

“The traditional view of data visualization is that it’s solitary, like looking through a microscope,” says Martin Wattenberg, leader of the Visual Communications Lab at IBM Lotus’s Collaborative User Experience (CUE) Research Group. “But really, it’s the stories people tell around visualizations that make them interesting. We wondered if that is something you can design around. And we decided the best way to test that was to build a site and deliberately design it around collaborative visualization.”

Wattenberg’s group launched Many Eyes in January as part of IBM’s Alphaworks, a Web environment where early adopters can test specific IBM software innovations before they get incorporated into products (and 40 percent of them do). Since then, users have uploaded more than 8,700 data sets and saved more than 6,000 visualizations based on them.

Often, the conversations about the visualizations are as interesting as the visualizations themselves. That’s partly because of the community customization features built into the Many Eyes interface. Even if someone else uploaded a data set, for example, a visitor can select a customized view of that data, then save and share a snapshot of that view for discussion. For one dataset, giving a breakdown of federal spending from 1962 to 2004, a visitor isolated a view showing a huge spike in spending on “deposit insurance” from 1987 to 1992 and asked what had caused it. Within days, other visitors had provided an answer: “Appears to be the savings and loan bailout cost,” one wrote. Wattenberg calls this exchange an example of “social data analysis in motion.”

But as any veteran Washington watcher knows, quantitative data can be fuel for political as well as social discussion, and Many Eyes has seen its share of polemics. The Sunlight Foundation, a nonprofit organization in the nation’s capital devoted to using technology to ensure greater transparency in government, has made extensive use of visualizations from Many Eyes to illustrate the epidemic of congressional earmarks. For fun, in September Wattenberg posted Alberto Gonzales’s testimony to Congress regarding the firings of U.S. attorneys. Users immediately used the data to create word trees, which showed that the word “don’t” in Gonzales’s testimony was most frequently followed by the word “recall,” giving a rather blunt illustration of the former attorney general’s self-serving memory lapses. But within 90 minutes, Wattenberg says, someone else (presumably a Republican) published an equally damning word tree of Bill Clinton’s testimony in the Monica Lewinsky scandal.

Of course, new tools are always vulnerable to abuse. Many of the thousands of visualizations published by Many Eyes users are mystifying, nonsensical, or just plain painful. “We definitely see people make visualizations that just aren’t the right type for their data,” says Wattenberg. “But I make an analogy to the early days of the Macintosh and desktop publishing, when people would use twelve different fonts in the same document, just because they could. Nowadays most people are very typographically literate. I think we’re likely to follow the same course with visualization tools.”

I asked Wattenberg what unexpected findings were emerging from the Many Eyes experiment so far. Most important, he said, was the way Many Eyes visualizations have become part of a larger conversation going on across the Web. “Most of the conversation is happening on blogs around the site, rather than on the Many Eyes site itself,” he says. That’s still important data for IBM, Wattenberg says, because the company is interested in helping people use data in the ways that feel most natural to them. “These are all cases of people talking about numbers—which people do in business all the time.”

“We had expected to create a conversation” within the Many Eyes site, Wattenberg says. “But at this point we feel like it’s enough to be a component of the larger Web community.”

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