Wednesday, July 24. 2013Who's Your Data? Urban Design in the New Soft City
Via Archinect -----
Smart city infrastructure can augment the ability of managers, planners, designers and engineers to define and implement a fundamentally better next generation of buildings, cities, regions — right? Maybe. For that to be a serious proposition, it’s going to have to be normal for planners and designers not only to collaborate productively with engineers, but to do so with the full and competent participation of the only people they mistrust more than each other ... customers.
"A city is not a BMW," writes Carl Skelton. "You can't drive it without knowing how it works." In a weighty think-piece on Places, he argues that the public needs new tools of citizenship to thrive in a "new soft world" increasingly shaped by smart meters, surveillance cameras, urban informatics and big data. "To be a citizen of a digital city requires understanding what the databases do and don’t contain, and what they could contain, and how the software used to process that data and drive design decisions does, doesn’t, and might yet perform."
Posted by Patrick Keller
in Architecture, Interaction design, Science & technology, Territory
at
08:49
Defined tags for this entry: architecture, artificial reality, digital, interaction design, monitoring, science & technology, smart, territory
Troubleshooting The Smart City
Via Forbes ----- By Anna Secino
Smart cities have been creating a lot of buzz lately—thanks, in no small part, to the recent controversy over NSA surveillance, which cast a rather sinister light over visions of cities made more efficient through data collection of public resources. “It starts with monitoring water usage,” the naysayers cry, “But where does it end?” This past week, two cities—Montpellier, France, and Dallas, Texas—released statements concerning their own attempts towards smartening up their infrastructure, which got us thinking about “Informed and Interconnected: A Manifesto for Smarter Cities,” a 2009 paper by Harvard Business School Professor Rosabeth Moss Kanter and IBM IBM +0.03% International Foundation President Stanley S. Litow. Its thoughts on and solutions for smart cities continue to be relevant four years later, as the cases in Montpellier and Dallas attest to. A major concern with regards to smart cities is figuring out who, exactly, is in charge of all this data collection? The government? The tech companies? As a city strives towards streamlined convergence, how does it avoid creating an especially unscrupulous monopoly? “It is important to note that new technologies have additional potential to make communities smarter by combining sets of data and making them available not only to immediate decision makers but to a much wider network of officials and agencies so that they can make more informed decisions,” Kanter and Litow write. Michel Aslanian, Montpellier’s Vice President of Innovation, believes that he has found the answer through making the $5.4 million research and development project a joint effort among stockholders, universities, startups, public utility operators, and Montpellier everymen. “The citizen is being made the author and actor in the development of the region,” he said regarding the “Ecocité” initiative, which hopes to collect data on public transportation, water usage, and other factors of city life that could lead to a greener, more efficient future. Other cities have not been quite so eager to jump on the bandwagon. In Dallas, where most corporate and municipal buildings operate on old, inefficient equipment, the switch to newer, more energy-efficient models has been ponderous. Europe requires that buildings be energy efficient, but U.S. politicians have been reluctant to pitch their support behind a similar initiative. And with the majority of office buildings dating back sixty to seventy years, updating existing structures can be costly. For all the money that cities and businesses waste every year through electricity, water, and other resources, many refuse to fund a never-ending progression of equipment repair. Supporters of both Dallas’s tortoise and Montpellier’s hare may want to acquaint themselves with Kanter and Litow’s vision for a city where high-tech advances help build efficient, egalitarian communities. Via a streamlined, interconnected approach, they argue, there would be less exclusion of racial or ethnic groups, as communities gather strength through individual differences, united in their efforts towards a better quality of life. In this scenario, technology serves merely as a tool for enhancing the very human pursuits of social- and self-betterment, with the monetary cost far outweighed by the environmental and communal benefits. To learn more about Kanter’s and Litow’s ideas for the snowballing smart city movement—including their list of the top eight problems commonly faced by smart cities, and how these can be avoided—read their full manifesto here, on the HBS Working Knowledge website. About the author: Writer Anna Secino is a student at Smith College in Northampton, Massachusetts.
Posted by Patrick Keller
in Architecture, Culture & society, Interaction design, Science & technology, Territory
at
08:45
Defined tags for this entry: architecture, culture & society, data, interaction design, monitoring, public, science & technology, smart, territory, urbanism
Tuesday, July 23. 2013New system uses low-power Wi-Fi signal to track moving humans — even behind walls
Via MIT News -----
Illustration: Christine Daniloff/MIT
The comic-book hero Superman uses his X-ray vision to spot bad guys lurking behind walls and other objects. Now we could all have X-ray vision, thanks to researchers at MIT’s Computer Science and Artificial Intelligence Laboratory.
Personal comment: This will probably restart the interests of private companies to provide "public" or private wifi "for free" or at least to equip large urban areas without charging for the work and the hardware (as you won't need to be connected to the wifi to be tracked, see?). As long as they'll be allowed to collect data, mine for crowd patterns and behaviors... (a new case for persons in charge of data protection).
Posted by Patrick Keller
in Architecture, Science & technology
at
07:57
Defined tags for this entry: architecture, artificial reality, monitoring, research, science & technology, surveillance
Wednesday, June 19. 2013Augmenting Social Reality in the Workplace
----- By Ben Waber
A new line of research examines what happens in an office where the positions of the cubicles and walls—even the coffee pot—are all determined by data.
Can we use data about people to alter physical reality, even in real time, and improve their performance at work or in life? That is the question being asked by a developing field called augmented social reality. Here’s a simple example. A few years ago, with Sandy Pentland’s human dynamics research group at MIT’s Media Lab, I created what I termed an “augmented cubicle.” It had two desks separated by a wall of plexiglass with an actuator-controlled window blind in the middle. Depending on whether we wanted different people to be talking to each other, the blinds would change position at night every few days or weeks. The augmented cubicle was an experiment in how to influence the social dynamics of a workplace. If a company wanted engineers to talk more with designers, for example, it wouldn’t set up new reporting relationships or schedule endless meetings. Instead, the blinds in the cubicles between the groups would go down. Now as engineers passed the designers it would be easier to have a quick chat about last night’s game or a project they were working on. Human social interaction is rapidly becoming more measurable at a large scale, thanks to always-on sensors like cell phones. The next challenge is to use what we learn from this behavioral data to influence or enhance how people work with each other. The Media Lab spinoff company I run uses ID badges packed with sensors to measure employees’ movements, their tone of voice, where they are in an office, and whom they are talking to. We use data we collect in offices to advise companies on how to change their organizations, often through actual physical changes to the work environment. For instance, after we found that people who ate in larger lunch groups were more productive, Google and other technology companies that depend on serendipitous interaction to spur innovation installed larger cafeteria tables. In the future, some of these changes could be made in real time. At the Media Lab, Pentland’s group has shown how tone of voice, fluctuation in speaking volume, and speed of speech can predict things like how persuasive a person will be in, say, pitching a startup idea to a venture capitalist. As part of that work, we showed that it’s possible to digitally alter your voice so that you sound more interested and more engaged, making you more persuasive. Another way we can imagine using behavioral data to augment social reality is a system that suggests who should meet whom in an organization. Traditionally that’s an ad hoc process that occurs during meetings or with the help of mentors. But we might be able to draw on sensor and digital communication data to compare actual communication patterns in the workplace with an organizational ideal, then prompt people to make introductions to bridge the gaps. This isn’t the LinkedIn model, where people ask to connect to you, but one where an analytical engine would determine which of your colleagues or friends to introduce to someone else. Such a system could be used to stitch together entire organizations. Unlike augmented reality, which layers information on top of video or your field of view to provide extra information about the world, augmented social reality is about systems that change reality to meet the social needs of a group. For instance, what if office coffee machines moved around according to the social context? When a coffee-pouring robot appeared as a gag in TV commercial two years ago, I thought seriously about the uses of a coffee machine with wheels. By positioning the coffee robot in between two groups, for example, we could increase the likelihood that certain coworkers would bump into each other. Once we detected—using smart badges or some other sensor—that the right conversations were occurring between the right people, the robot could move on to another location. Vending machines, bowls of snacks—all could migrate their way around the office on the basis of social data. One demonstration of these ideas came from a team at Plymouth University in the United Kingdom. In their “Slothbots” project, slow-moving robotic walls subtly change their position over time to alter the flow of people in a public space, constantly tuning their movement in response to people’s behavior. The large amount of behavioral data that we can collect by digital means is starting to converge with technologies for shaping the world in response. Will we notify people when their environment is being subtly transformed? Is it even ethical to use data-driven techniques to persuade and influence people this way? These questions remain unanswered as technology leads us toward this augmented world.
Ben Waber is cofounder and CEO of Sociometric Solutions and the author of People Analytics: How Social Sensing Technology Will Transform Business, published by FT Press.
Personal comment:
Following my previous posts about data, monitoring or data centers: or when your "ashtray" will come close to you and your interlocutor, at the "right place", after having suggested to "meet" him...
Posted by Patrick Keller
in Architecture, Interaction design, Science & technology
at
07:48
Defined tags for this entry: architecture, behaviour, code, data, design (environments), interaction design, monitoring, research, science & technology
Tuesday, May 28. 2013Arctic Instruments
Via BLDGBLOG ----- de noreply@blogger.com (Geoff Manaugh)
[Image: Via the Extreme Environments & Future Landscapes program].
Returning briefly to the theme of landscape devices—particularly in the run-up to the launch of Landscape Futures—I thought I'd post a quick look at a trip to the Arctic island of Svalbard last autumn led by David Garcia with students from the University of Lund School of Architecture. As part of Lund's Extreme Environments & Future Landscapes program, students flew up to visit "the far north, beyond the Polar Circle, to Svalbard, to study the growing communities affected by the melting ice cap and the large opportunities for transportation and resources that the northeast passage now offers." [Image: Via the Extreme Environments & Future Landscapes program]. There, the students would also research first-hand the performance of "urban structures in the extreme cold." [Images: From a series of "light beacon studies" by Marta Nestorov]. However, Garcia adds, during their time in the extreme environment of the north, the group also "tested and probed the surroundings with surveying equipment designed and built for the expedition, at urban and natural landscapes, from -30 degrees Celsius to overcast blackout weather." [Image: An instrument for analyzing "perception and interpretation of the aurora borealis" by Christopher Erdman]. Some of that equipment is pictured here, ranging from a colorful audio device "used for testing sound absorption properties of snow" to a kind of portable oven meant for testing the thermal-insulation qualities of "ice tiles" that might someday be used in constructing frozen architecture. [Image: Device "for testing sound absorption qualities of snow," by Milja Lindberg and Liina Pikk]. For their test of the acoustic properties of snow, for example, using tripods seen in the above photo, students Milja Lindberg and Liina Pikk designed an experiment that would operate "by transmitting sound onto snow and reflecting it to a receiver": The device consists of three parts. A blue transmitter tube (Ø 60mm) sends focused sound frequencies through a speaker fitted at one end of the tube. A red receiver tube 20mm wider in diameter picks up sound waves reflected from the snow test bed. Both tubes are connected to tripods with an angle adjuster that works as a protractor to set the right angle. This piece also connects two lasers on top of the tubes. The lasers meet in the middle of the snow test bed. [Images: The aforementioned device "used for testing sound absorption qualities of snow," by Milja Lindberg and Liina Pikk].
Posted by Patrick Keller
in Architecture, Science & technology, Territory
at
13:07
Defined tags for this entry: architecture, climate, devices, monitoring, research, science & technology, territory
Friday, May 10. 2013Brooklyn Developer Offers Up His Personal Data on Kickstarter
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A man had data mined himself so he can fund an app that helps others sell their own personal data.
Software developer Federico Zannier has data-mined himself, and now he’s raising money on Kickstarter to build an iPhone app and Chrome browser extension so that others can easily do the same.
Fork over $2 to the campaign and you get a day’s worth of the 1.5 gigabytes of text and 30,000 photos he’s collected from his online activities since February. That means a fun-filled 24-hours of websites, screenshots, webcam images, cursor movements, app logs, and GPS locations he’s tracked. Is it a bargain? No, not at all—and that’s his point. Today, companies on the web track him and everyone else and make billions selling the data. By violating his own privacy, as he puts it, he hopes that he can collect some of this value. “If more people do the same, I’m thinking marketers could just pay us directly for our data. It might sound crazy, but so is giving all our data away for free,” he writes. Zannier is not the first to dream up such an idea (see “A Dollar for Your Data”). One problem is that the data isn’t worth much on its own to marketers. They want to buy in bulk. That’s why Facebook and Google can make so much money. They can group people together that marketers want to reach. So though its hard to imagine what his data is good for on its own, already with 68 backers he’s exceeded his modest funding goal of $500 for his project. If he’s successful in getting lots of people to use his data mining app, though, maybe he’ll become the next of the big data brokers. MIT Technology Review is now exploring the issues Zannier raises in this month’s Business Report series “Big Data Gets Personal.” These articles discuss one important point that gets lost when people like Zannier dicuss their dissatisifaction with giving away their data for free: Though people are giving up more of their data than ever before, they are also getting more and more value back (see “The Data Made Me Do It.”).
Personal comment: More and more societal questions around data... In this case, a new "business model": opening up one's own personal data (you are the product!), possibly crowd fund a mining system that would gather them from other people who act in the same way and do at best a fraction of the mining job Facebook or others could do, then get financially rewarded for breaking up one's own privacy... Instead of big corps. who do the same.
Posted by Patrick Keller
in Culture & society, Science & technology
at
10:19
Defined tags for this entry: culture & society, data, identification, mining, monitoring, science & technology
Wednesday, May 08. 2013Stephen Wolfram on Personal Analytics
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The creator of the Wolfram Alpha search engine explains why he thinks your life should be measured, analyzed, and improved.
Personal control: Stephen Wolfram created the search engine Wolfram Alpha
Don’t be surprised if Stephen Wolfram, the renowned complexity theorist, software company CEO, and night owl, wants to schedule a work call with you at 9 p.m. In fact, after a decade of logging every phone call he makes, Wolfram knows the exact probability he’ll be on the phone with someone at that time: 39 percent. Wolfram, a British-born physicist who earned a doctorate at age 20, is obsessed with data and the rules that explain data. He is the creator of the software Mathematica and of Wolfram Alpha, the nerdy “computational knowledge engine” that can tell you the distance to the moon right now, in units including light-seconds. Now Wolfram wants to apply the same techniques to people’s personal data, an idea he calls “personal analytics.” He started with himself. In a blog post last year, Wolfram disclosed and analyzed a detailed record of his life stretching back three decades, including documents, hundreds of thousands of e-mails, and 10 years of computer keystrokes, a tally of which is e-mailed to him each morning so he can track his productivity the day before. Last year, his company released its first consumer product in this vein, called “Personal Analytics for Facebook.” In under a minute, the software generates a detailed study of a person’s relationships and behavior on the site. My own report was revealing enough. It told me which friend lives at the highest latitude (Wicklow, Ireland) and the lowest (Brisbane, Australia), the percentage who are married (76.7 percent), and everyone’s local time. More of my friends are Scorpios than any other sign of the zodiac. It looks just like a dashboard for your life, which Wolfram says is exactly the point. In a phone call that was recorded and whose start and stop time was entered into Wolfram’s life log, he discussed why personal analytics will make people more efficient at work and in their personal lives.
What do you typically record about yourself? E-mails, documents, and normally, if I was in front of my computer, it would be recording keystrokes. I have a motion sensor for the room that records when I pace up and down. Also a pedometer, and I am trying to get an eye-tracking system set up, but I haven’t done that yet. Oh, and I’ve been wearing a sensor to measure my posture. Do you think that you’re the most quantified person on the planet?
I couldn’t imagine that that was the case until maybe a year ago, when I collected together a bunch of this data and wrote a blog post on it. I was expecting that there would be people who would come forward and say, “Gosh, I’ve got way more than you.” But nobody’s come forward. I think by default that may mean I’m it, so to speak. You coined this term “personal analytics.” What does it mean? There’s organizational analytics, which is looking at an organization and trying to understand what the data says about its operation. Personal analytics is what you can figure out applying analytics to the person, to understand the operation of the person. Why have you been analyzing Facebook data? We are trying to feel out the market for personal analytics. Most people are not recording all their keystrokes like I am. But the one thing they are doing is leaving lots of digital trails, including on Facebook, and that is one of the pieces we’ve been experimenting with. We’ve accumulated a lot of Facebook data—you’re seeing the story of people’s lives, played out in the level of data. You can see relationship status as a function of age, or the evolution of the clustering of friends at different ages. It’s really quite fascinating to see how all this stuff is just right there in the data.
Social grid: People’s friend networks on Facebook are presented as cluster diagrams.
Isn’t a lot of what you find kind of obvious? Like friends from college aren’t connected to the ones from grammar school? Yes, but then you get a case where the data analysis is buggy. You get some curve, and your reaction is, “Oh, yeah, I understand why the curve is that way, I’ve got an argument for it.” But then, oops, there was a bug in the analysis and actually the curve is something different. That reminds you things aren’t quite so obvious. If you actually measure it, that’s doing science. What’s the connection to the search engine you built? Right now Wolfram Alpha is strong on public knowledge: accumulating and searching the knowledge of the civilization. But what you have to do in personal analytics is try to accumulate the knowledge of a person’s life. Then the two can actually be integrated, and I’ll give a kind of silly example. You might ask: “Who do I know that can go out into their backyard and go and look at the night sky right now?” For that you have to be able to compute who is in nighttime, who doesn’t have cloudy weather, and things like this. And we can compute all that stuff. What do you see as the big applications in personal analytics? Augmented memory is going to be very important. I’ve been spoiled because for years I’ve had the ability to search my e-mail and all my other records. I’ve been the CEO of the same company for 25 years, and so I never changed jobs and lost my data. That’s something that I think people will just come to expect. Pure memory augmentation is probably the first step. The next is preëmptive information delivery. That means knowing enough about people’s history to know what they’re going to care about. Imagine someone is reading a newspaper article, and we know there is a person mentioned in it that they went to high school with, and so we can flag it. I think that’s the sort of thing it’s possible to dramatically automate and make more efficient. Then there will be a certain segment of the population that will be into the self-improvement side of things, using analytics to learn about ourselves. Because we may have a vague sense about something, but when the pattern is explicit, we can decide, “Do we like that behavior, do we not?” Very early on, back in the 1990s, when I first analyzed my e-mail archive, I learned that a lot of e-mail threads at my company would, by a certain time of day, just resolve themselves. That was a useful thing to know, because if I jumped in too early I was just wasting my time. What technologies are needed to do personal analytics at a large scale? It’s data science and the whole cluster of technologies that come with that. Then it’s having computational knowledge about the world and being able to make queries in natural language. Then you need to sense things about the world, whether it’s with sensors or being able to do visual recognition to know what one is seeing. Then the final thing is just all the plumbing infrastructure to get all of these devices to communicate and feed their information to a place where one can do analysis. Where do you stand on commercializing these ideas? The personal analytics of Facebook for Wolfram Alpha is a deployed project, and there will be more of those in the personal-analytics space. We think we can do terrific things, but you have to be able to get to the data. That has been the holdup. The data isn’t readily available. Recently we’ve been working with different companies to try and make sure we can connect their sensors to kind of a generic analytics platform, to take people’s data, move it to the cloud, and do analytics on it. How much better do you think that people or organizations can become with some data feedback? I think it will be fairly dramatic. It’s like asking how much more money can you make if you track your portfolio rather than just vaguely remembering what investments you made.
Related Links:
Posted by Patrick Keller
in Culture & society, Science & technology
at
15:57
Defined tags for this entry: artificial reality, culture & society, data, identification, mining, monitoring, science & technology, surveillance
Driving Miss dAIsy: What Google’s self-driving cars see on the road
Via Slash Gear via Computed·Blg -----
We’ve been hearing a lot about Google‘s self-driving car lately, and we’re all probably wanting to know how exactly the search giant is able to construct such a thing and drive itself without hitting anything or anyone. A new photo has surfaced that demonstrates what Google’s self-driving vehicles see while they’re out on the town, and it looks rather frightening.
The image was tweeted by Idealab founder Bill Gross, along with a claim that the self-driving car collects almost 1GB of data every second (yes, every second). This data includes imagery of the cars surroundings in order to effectively and safely navigate roads. The image shows that the car sees its surroundings through an infrared-like camera sensor, and it even can pick out people walking on the sidewalk. Of course, 1GB of data every second isn’t too surprising when you consider that the car has to get a 360-degree image of its surroundings at all times. The image we see above even distinguishes different objects by color and shape. For instance, pedestrians are in bright green, cars are shaped like boxes, and the road is in dark blue. However, we’re not sure where this photo came from, so it could simply be a rendering of someone’s idea of what Google’s self-driving car sees. Either way, Google says that we could see self-driving cars make their way to public roads in the next five years or so, which actually isn’t that far off, and Tesla Motors CEO Elon Musk is even interested in developing self-driving cars as well. However, they certainly don’t come without their problems, and we’re guessing that the first batch of self-driving cars probably won’t be in 100% tip-top shape.
Posted by Patrick Keller
in Interaction design, Science & technology, Territory
at
08:22
Defined tags for this entry: automation, interaction design, monitoring, perception, presence, science & technology, smart, territory, vision
Electronic Sensors Printed Directly on the Skin
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New electronic tattoos could help monitor health during normal daily activities. By Mike Orcutt on March 11, 2013
Electronic tattoo: The image shows a colorized micrograph of an ultrathin mesh electronic system mounted on a skin replica.
Taking advantage of recent advances in flexible electronics, researchers have devised a way to “print” devices directly onto the skin so people can wear them for an extended period while performing normal daily activities. Such systems could be used to track health and monitor healing near the skin’s surface, as in the case of surgical wounds. So-called “epidermal electronics” were demonstrated previously in research from the lab of John Rogers, a materials scientist at the University of Illinois at Urbana-Champaign; the devices consist of ultrathin electrodes, electronics, sensors, and wireless power and communication systems. In theory, they could attach to the skin and record and transmit electrophysiological measurements for medical purposes. These early versions of the technology, which were designed to be applied to a thin, soft elastomer backing, were “fine for an office environment,” says Rogers, “but if you wanted to go swimming or take a shower they weren’t able to hold up.” Now, Rogers and his coworkers have figured out how to print the electronics right on the skin, making the device more durable and rugged. “What we’ve found is that you don’t even need the elastomer backing,” Rogers says. “You can use a rubber stamp to just deliver the ultrathin mesh electronics directly to the surface of the skin.” The researchers also found that they could use commercially available “spray-on bandage” products to add a thin protective layer and bond the system to the skin in a “very robust way,” he says. Eliminating the elastomer backing makes the device one-thirtieth as thick, and thus “more conformal to the kind of roughness that’s present naturally on the surface of the skin,” says Rogers. It can be worn for up to two weeks before the skin’s natural exfoliation process causes it to flake off. During the two weeks that it’s attached, the device can measure things like temperature, strain, and the hydration state of the skin, all of which are useful in tracking general health and wellness. One specific application could be to monitor wound healing: if a doctor or nurse attached the system near a surgical wound before the patient left the hospital, it could take measurements and transmit the information wirelessly to the health-care providers. Rogers says his lab is now focused on developing and refining wireless power sources and communication systems that could be integrated into the system. He says the technology could potentially be commercialized by MC10 (see “Making Stretchable Electronics”), a company he cofounded in 2008. If things go as planned, says Rogers, in about a year and half the company will be developing more sophisticated systems “that really do begin to look like the ones that we’re publishing on now.”
Monday, April 22. 2013A new way to report data center's Power and Water Usage Effectiveness (PUE and WUE)
Via Computed.Blg via Open Compute Project -----
Today (18.04.2013) Facebook launched two public dashboards that report continuous, near-real-time data for key efficiency metrics – specifically, PUE and WUE – for our data centers in Prineville, OR and Forest City, NC. These dashboards include both a granular look at the past 24 hours of data and a historical view of the past year’s values. In the historical view, trends within each data set and correlations between different metrics become visible. Once our data center in Luleå, Sweden, comes online, we’ll begin publishing for that site as well. We began sharing PUE for our Prineville data center at the end of Q2 2011 and released our first Prineville WUE in the summer of 2012. Now we’re pulling back the curtain to share some of the same information that our data center technicians view every day. We’ll continue updating our annualized averages as we have in the past, and you’ll be able to find them on the Prineville and Forest City dashboards, right below the real-time data. Why are we doing this? Well, we’re proud of our data center efficiency, and we think it’s important to demystify data centers and share more about what our operations really look like. Through the Open Compute Project (OCP), we’ve shared the building and hardware designs for our data centers. These dashboards are the natural next step, since they answer the question, “What really happens when those servers are installed and the power’s turned on?” Creating these dashboards wasn’t a straightforward task. Our data centers aren’t completed yet; we’re still in the process of building out suites and finalizing the parameters for our building managements systems. All our data centers are literally still construction sites, with new data halls coming online at different points throughout the year. Since we’ve created dashboards that visualize an environment with so many shifting variables, you’ll probably see some weird numbers from time to time. That’s OK. These dashboards are about surfacing raw data – and sometimes, raw data looks messy. But we believe in iteration, in getting projects out the door and improving them over time. So we welcome you behind the curtain, wonky numbers and all. As our data centers near completion and our load evens out, we expect these inevitable fluctuations to correspondingly decrease. We’re excited about sharing this data, and we encourage others to do the same. Working together with AREA 17, the company that designed these visualizations, we’ve decided to open-source the front-end code for these dashboards so that any organization interested in sharing PUE, WUE, temperature, and humidity at its data center sites can use these dashboards to get started. Sometime in the coming weeks we’ll publish the code on the Open Compute Project’s GitHub repository. All you have to do is connect your own CSV files to get started. And in the spirit of all other technologies shared via OCP, we encourage you to poke through the code and make updates to it. Do you have an idea to make these visuals even more compelling? Great! We encourage you to treat this as a starting point and use these dashboards to make everyone’s ability to share this data even more interesting and robust. Lyrica McTiernan is a program manager for Facebook’s sustainability team.
Personal comment:
The Open Compute Project is definitely an interesting one and the fact that it comes with open data about centers' consumption as well. Though, PUE and WUE should be questioned further to know if these are the right measures about the effectiveness of a data center.
Posted by Patrick Keller
in Architecture, Science & technology, Sustainability
at
07:52
Defined tags for this entry: architecture, data, energy, information, monitoring, opensource, science & technology, sustainability
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fabric | rblgThis blog is the survey website of fabric | ch - studio for architecture, interaction and research. We curate and reblog articles, researches, writings, exhibitions and projects that we notice and find interesting during our everyday practice and readings. Most articles concern the intertwined fields of architecture, territory, art, interaction design, thinking and science. From time to time, we also publish documentation about our own work and research, immersed among these related resources and inspirations. This website is used by fabric | ch as archive, references and resources. It is shared with all those interested in the same topics as we are, in the hope that they will also find valuable references and content in it.
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