Just a quick hit to link to Daniel Solove’s epic paper “A Taxonomy of Privacy” which has rapidly become a major influence on my work at Consent to Research. It’s a free download. But the first sentences of the abstract are a great teaser: Privacy is a concept in disarray. Nobody can articulate what it means. As one commentator has observed, privacy suffers from an embarrassment of meanings. Privacy is far too vague a concept to guide adjudication and lawmaking, as abstract incantations of the importance of privacy do not fare well when pitted against more concretely-stated countervailing interests. Agreed. I love the taxonomy’s distinction between information collection, processing, and dissemination. I do wish there was a discussion of harm in here because economic harm is a real consequence of information dissemination in health.

I’m speaking today on a panel at the Atlantic Live healthcare forum. Below are the themes I’m going to hit in my talk - but it felt like it was worth posting them here as well. We have engines to generate correlations out of massive data that are unreasonably effective. We’re not using them in health, because the machines don’t work very well on health data. It isn’t just that the data be massive, but that it be available (i.e. open) and at least somewhat standardized. Health data’s almost never either one. Here’s a key sentence from the Google paper linked above: “With a corpus of thousands of photos, the results were poor. But once they accumulated millions of photos, the same algorithm performed quite well.” Have we ever had millions of data records about health for algorithm training? Nope. That’s a tragedy. It’s not that these engines - machine learning - are the magic answer. But they’re an incredibly powerful toolkit for finding correlations, which helps us decide what experiments to run to test for causation. It’s like we’re carpenters and we’re sitting around building a house and saying, nah, we don’t want to use power tools. Hand saws for everyone! The Amish approach won’t scale. We have no idea how many people it’s going to take, or how much data about each person it’s going to take, to discover exactly how valuable machine learning is going to be in the health space. But that’s a terrible excuse to do nothing. In fact, it should be the spur that gets us started on the experiment itself. That’s what i am doing with the Portable Legal Consent project. It’s an experiment to test three things. 1. can we use a standardized approach to informed consent that disintermediates the traditional study systems, which are crusty and have insanely high transaction costs? 2. will people enroll and upload data, and of what type and quality? 3. what kind of results will emerge from the computational research? Until we know these three things we’re basically arguing about philosophy and not reality. We know that these systems are tremendously powerful and predictive in many areas. We know that we aren’t using them in health in a meaningful way. And we know that there’s nothing stopping us from trying except ourselves.

Seriously, I wish I could get cranked about yet another piece of “please protect my content industry from teh internetz” lobbying crap, but the only reaction I can really summon at this point is LOLCats and animated gifs of Bill Cosby.

So this happened yesterday, and it’s a good thing. But note Mike Eisen’s question below Ed Summers’ tweet.

On May 20, 2012, I joined Mike Carroll, Mike Rossner, and Heather Joseph to start a campaign for a federal policy to require free access to scholarly articles emerging from taxpayer funded research. We decided to launch a petition on the We the People website. We hit the 25,000 signature number pretty quickly, and I got a few calls from DC people asking what the hell was going on. This was before every maniac who wanted to secede started a petition - it was, and still is, a backwater, and we figured we could make some noise there. It worked. Since then, petitions on beer recipes, gun control, and the death star have received official responses from the White House. We have not. I am told there is a conversation going on. I am asked to be patient. I am tired of being patient. I’m tired of the power of publisher money carrying the day, delaying the policy, blocking the flow of knowledge. It’s time to make taxpayer funds turn into taxpayer goods. It’s up to the businesses to figure out how to make money in the new world - if you can’t figure out how to adapt  your business to the network, you will merely be the latest in a long line of dinosaurs dating back to Digital Equipment Corp and running straight through to Newsweek. I do not cry for you. It’s time to bring an end to the barriers to new businesses. Time to enable new entrepreneurs, who make money from increasing the free flow of information rather than by restricting it. Time for search engines that make it easy to find and integrate the literature. Time to enable people outside the institutional system who might take scholarly knowledge and turn it into products, into policies, into something of use. It’s time for an answer. And if we don’t get the answer that says, “you paid for it, it’s yours,” it’s going to be time to escalate this from something on a sleepy backwater petition site to a protest that the whole world will notice.

The White House has published a response to our We the People petition, commonly known as the OA Monday petition. I’ll have a longer post up once I’ve had time to thoroughly review the policy, but the multi-year campaign to turn the NIH public access policy into something that applied to the entire federal research system is over. I’d like to thank the White House, especially the Office of Science and Technology policy, for listening to us through the various RFIs and then finally to the petition. This is good policy. And it’s nice to see something substantive emerge from the We the People platform, too. To the squeals of the publishers, I say only this. Jobs will be created by open content. I personally built a company years ago on the open data published by the NIH. I’m looking forward to watching others build companies on the open literature that will emerge under this policy. And the fight’s not over - it won’t be until we have reuse rights, not just free downloads. But for now, let’s dance.  We won.

Giving a talk at Designing Geopolitics 2. Based in large part on ideas in my post on designing for emergence. Since I’m speaking in front of the optiportal, I have no powerpoint, but instead a folder of files that I’m using as a mosaic. I can’t redistribute all of them, so I’m not able to show you everything. Will add a link to the HD video. These are not my comments as they will be delivered. Think of them as chord changes. We’ll see if it works. 0 (displaying a giant photo of Copernicus) knowledge from data Copernicus. Photo. cultural object. Creative work. But since it’s digital, it’s also data. It can now be effortlessly copied, distributed, at zero loss of quality or resolution. And Copernican theory led to Brahe, who made painstaking observations, which allowed Kepler and galileo to figure out planetary motion. 1 (displaying a mosaic of pictures of old data) they did this using what they called observations, what we call data. this is what data used to be. it reformed geopolitics (heliocentricism) and transformed knowledge distribution. 2 (displaying a mosaic of paleofuture slides) Remember that with the data we have at the moment, we ususaly get the future hilariously wrong. Future shock images. Futurism tells us more about now than the future a lot of the time. Thus any geopolitics needs to understand that we are at least mostly wrong. 3 (display images of analog data storage and copying tech) these are all ways that we wound up storing data, from the old to the last of the pre digital. quality degraded with copying. all analog. all kind of human: liable to age in ways we understood, intuitively (get images) 4 (display a large picture of the @ sign key on an old typewriter) Transition to digital and what it means. 5 (display pictures of data capture technologies and shots of pigpen from peanuts) capacity to capture data exploding. faster, better, smaller, ubiquitous. pigpen secreting dust as we secrete data. 6 (display pictures of the Dust Bowl era) dustbowl of data. dust bowl emerged from a national politics of exploitation of the land, coupled with an unusually rainy period on the great plains. “Rain follows the plow” was the idea. Devastating impact on humans, on economy, on land. 7 (black screen) not to mention that digital data, though of the human, is distinctly digitally not-necessarily-human stuff. 8 (wipe through a set of pictures of a greenhouse monoculture, the earth at night from space, black box.) monoculture emerging. that is the geopolitics we are getting. digital divide emerging. that is the geopolitics we are getting. the black box transaction. that is the geopolitics we are getting. 9 (black screen) but, the trick. we can build our own geopolitics without asking anyone else’s permission. 10 (display a set of soviet propaganda poster) it is commonly built, but it is not sovietism. 11 (display photo of pic saying no public access) it is a reaction to the increasing privatization and exploitation of digital assets. no public access is the default rule. access might be free of cost, but you trade your inner pigpen for access. 12 (display photo of public footpath) common public access. free software. creative commons. science commons. where commons based systems work, where they don’t. property rights and their limitations, privacy rights and their implications. 13 (display photo of one green shoot in a furrow) the consented commons as the green shoot growing. it does not take all of us, even very many of us, working together to create something amazing. that’s the real lesson. there is already an asymmetry between the number of people who make things and the number of people who consume them. when we invert the system through a shared open core we can benefit from that same asymmetry to make open systems deeply competitive with closed ones. that’s why there is resistance to the open. 14 (display pics of wright brothers at kitty hawk.) where we are now: first flight at kitty hawk, first experiments. the older i get the earlier it seems. we’re learning, trying, hacking, failing. that’s fine. that is indeed the point. 15 (display pics from NASA explorations) the blurring of the lines: jupiter photo (get more) - are they art? are they data? does it matter? 16 (display the following words across entire screen, white text on black background) geopolitics of data as the potential for emergence.

Evgeny Morozov’s been on a tear lately, with articles about “solutionism” in Slate and the New York Times, and an absolute destruction of Gavin Newsom’s new book on networked politics. I’m torn by Evgeny’s work. I tend to agree with what I perceive is one of his basic ideas: our culture of deifying the application has a nasty side effect of reducing the perceived importance of political change: don’t bother actually risking anything to protest, just like the Facebook page about the protest. I really liked the concept about the rise of the choosing algorithm and its impact on creativity.  I have a soft spot for a truly well written negative book review. And I think it’s vital that those of us who self-identify as “open” advocates engage with his work, because I think he’s onto something in more cases than I’d like to admit. On a related note, I’ve been reading The Theory That Would Not Die recently. It’s a nice look at the waxing and waning of probability and inference over hundreds of years. When we’re in periods where we don’t know what we’re looking for - and it’s important to be as right as possible as fast as possible - then Bayes’ table becomes a vital tool in the kit. In World War II, that was cracking Enigma. Unfortunately now, most of its usage is social, mobile, commercial. It offers me rehab in Napa Valley when I buy wine online. But I worry that in burying the algorithm and the application and the game, to kill its overestimation in culture and in politics, he fails to appreciate the places where those tools are yet to be applied, but might bring real change. By real change, I mean epistemic change, a change in the way that we know we know something. Science is one of those places. Science has a problem related to, but different than, solutionism. I’d call it “sensorism” perhaps - the belief that because we can make a machine that senses things more finely, more completely, and in massive parallel, we’ll somehow come to a greater understanding of the underlying thing being studied. Sensorism is rife in the sciences. Pick a data generation task that used to be human centric and odds are someone is trying to automate and parallelize it (often via solutionism, oddly - there’s an app to generate that data). What’s missing is the epistemic transformation that makes the data emerging from sensors actually useful to make a scientific conclusion - or a policy decision supposedly based on a scientific consensus. One of the reasons I do “open” work is that I think, in the sciences, it’s a philosophical approach that is more likely to lead to that epistemic transformation. If we have more data available about a scientific problem like climate change, or cancer, then the odds of the algorithms figuring something out that is “true” but incomprehensible to us humans go up. Sam Arbesman has written about this nicely both in his book the Half Life of Facts and in another recent Slate article. I work for “open” not because “open” solves a specific scientific problem, but because it increases the overall probability of success in sensorism-driven science. Even if the odds of success themselves don’t change, increasing the sample size of attempts will increase the net number of successes. I have philosophical reasons for liking open as well, and those clearly cause me cognitive bias on the topic, but I deeply believe that the greatest value in open science is precisely the increased sample size of those looking. I also tend to think there’s a truly, deeply political element to enabling access to knowledge and science. I don’t think it’s openwashing (and you should read this paper recommended by Morozov on the topic) to say that letting individuals read science can have a real political impact. I look forward to reading Morozov’s new book this weekend at SXSW. It’ll be a bracing antidote to what I expect will be rampant solutionism. My panel is political - it’s about who owns the data these solutions create, and what rights and risks those solutions entail. It’ll get a lot less attendees than a product launch. And I hope Morozov engages with sensorism one of these days. It’d be fun to see what he does with it.

I’m a relatively new dad. This is my second fathers’ day, but my son was so new last year that June is lost somewhere in the fog that comes along with four hours of sleep a night for weeks on end, 18 diapers a day, and feedings every two hours. It’s the first one I can really enjoy. Being a dad is a funny thing. I didn’t expect it to be this much fun . The diapers and the feeding and the repetitious activities are the things that so many people focused on before I had a kid, but very few people talked to me about how having a kid can drag you into the moment as well as, or better than, anything else. Watching the boy play on the patio in the warm afternoon sun. Giving him a bath. Helping him climb. Smelling his head in the morning while he takes his first bottle. I spend a lot of time - a LOT - plugged in and online and digitally present. My son tethers me to the real world. And he makes me appreciate my own dad more and more. I find myself unconsciously doing things my dad did. I make a silly face and catch myself in a mirror and it’s my dad’s face. I see his face in my son. I hear his voice in my voice when I talk, feel his structure in my structure. Happy fathers day, pops. Thanks for teaching me.

So Mendeley got bought by Elsevier. And there was much teeth-gnashing. I won’t link to it but it spawned two solid hashtags: #mendelsevier and #mendelete. I have a Mendeley account, but never used it other than to test the system against Zotero, which is what  I use to track my own work. So I am not affected by this but I’ve been a bit stunned by the depth of the anger against Mendeley. I’ve waited to write this to try and understand it. Part of it, I assume, is just Elsevier rage. Danah Boyd has summarized why Elsevier is rage-worthy nicely in her post on the acquisition. But the greater part feels like the anger over what many seem to think is a broken promise made by Mendeley to be an “open” company. I don’t feel that way. I never thought Mendeley was an open company. I thought they were deploying a strategic approach to openness by exposing their data under CC-BY, but I always thought that openness wasn’t the point of the company. It’s why I didn’t use the product and why I wasn’t surprised, shocked, or saddened by the acquisition. It’s got me thinking though about companies and “open” - and what matters in deciding whether or not to use a product from a company claiming that mantle. For me it boils down to where the openness lives in a company. There’s a lot of ways to slice this, but a simple one would be: is the “open” part of the revenue model or is it part of the market acquisition strategy? If the former, like BioMed Central, I have a lot more faith that an acquisition will not destroy the openness, because “open” is part of the way that the company makes money. But the open access part of Mendeley to me always appeared to be a customer acquisition strategy. It appealed to the OA folks, it appealed to developers, and it never affected any monetization or revenues. There were always visible choices by management to hedge their open bets, as Jason Hoyt has laid out. And that makes it a risky bet to think they’ll stick with it now that they have access to a massively larger customer base while inside a company with traditional antipathy towards openness. Again, I’m not mad. I either avoid, from a professional basis, companies built on closure, or I mitigate my expectations of them and do a lot of backing up. Because at some point unless the revenues come from open, the customer acquisition strategy of openness will be deprecated. If it isn’t, then the management of the company will be replaced with managers who are willing to shut things down to make money. Always, always, always examine claims made by companies about openness. I’m not the world’s biggest Evgeny Morozov supporter, but he’s right to examine the way that the words “open” and “sharing” and “free” get co-opted. Facebook lets you share! It’s free, and always will be! Look the gift horse in the mouth. And if the revenue model of a startup isn’t built on open, then feel free to use the tool. But don’t get emotionally invested, or dependent, no matter how seductive the rhetoric may be. Because at some point your use and attention and content will be monetized, probably in a way that bothers you.

Just a quick note to put out a thought. I’ve done a lot of work with informed consent, and am one of the people pushing the idea that in its current form it isn’t serving our needs as a society, as patients, as scientists, as people. That’s pretty much the whole point of my TED talk. And I’m a supporter of projects like Reg4All, which embrace fair information services practices as their basis. There’s a real role to play for that approach, especially in aggregate level data, or in recruitment of people for studies that will in turn require informed consent. But I am noticing a disturbing trend in the conversation around consent, one that I intend to combat fiercely, which is the idea that informed consent itself is the problem. I don’t think it is. I think it’s the way we do it that’s a problem. When it’s used as a shield against patient involvement, or as an excuse to deny people their data, that’s a problem. When people don’t understand the forms and are rushed through the process, that’s a problem. When data can’t be integrated into larger and larger studies because of consent, that’s a problem. But the idea that we should be informed about the risks and benefits to ourselves and society before we decide to share our data? I don’t think that’s a problem that needs disrupting. We need to embrace better design for informed consent. We need to bring it into the 21st century, to make it compatible with distributed computing, with large-scale mathematics, with the internet. That’s clear. None of these problems, together or collectively, mean we should treat the issue of consenting people into research as a simple transaction cost. It’s not about reducing the “friction” of “participation” to a few clicks here or there. If we treat informed consent as a transaction cost to be minimized or eliminated, we may solve the problems of data liquidity. But data liquidity, as we’ve seen in national security, social media, and more, doesn’t always come alongside beneficence, justice, and respect for people. That’s the point of informed consent, not liquidity of data. Health data is one of the only places where informed consent - not just simple clicking - is part of our cultural heritage. I think that’s a feature, and not a bug. If we can’t find a way to balance informed consent, and its ethical heritage, with data liquidity, that failure is on us.

23andme has an API. They announced it in a talk called “Own Your Data” - which i thoroughly recommend. And they back it up in terms of your actual genotype on their website. You can download your SNPs, and upload them (as I have in multiple places). They also provide on their site interpretations of the genotype. Those interpretations are what make the data useful to us as patients. They’re at the center of the FDA-23andme battle, which isn’t the point of this post. I can’t download and export my interpretations the way I can download and export my genotype, and that seems a missed opportunity. It’s directly supported in the API, which features the elements at the bottom of the post. So, I hereby pledge to give $500 to the first person who makes a web application that works in Firefox, and lets me log into 23andme and download my health and ancestry data into a structured file (CSV at least - no text files). The app must have its source code on github, and be licensed under an FSF approved free software license. The app must work not just for me, but for four more testers. It must pass a security review to make sure it’s not leaking passwords. The file should contain my genomic and health data, not my user data or my ancestry data. “First” will be judged by twitter timestamp - send me a message if you have a submission. I know $500 isn’t a lot. If I could code, I would. But I suck at it. This is out of my own pocket. I’ll also promise to give just incredible amounts of attribution, acclaim, and more. It’s a chance to get known too. It’s part of my “stop complaining and do useful stuff” resolution. If no one bites, I’ll post this as a claimable job somewhere else. User\label{user} GET /user GET /names GET, POST /profile_picture GET, PUT, POST /publish GET, PATCH, POST /introduction \tightlist Genetics\label{genetics} GET /genotypes GET /genomes \tightlist Ancestry\label{ancestry} GET /haplogroups GET /ancestry GET /neanderthal GET, PATCH /relatives \tightlist Health\label{health} GET /risks GET /carriers GET /drug_responses GET /traits \tightlist

Well, that didn’t take long. Less than seven hours after I posted a request and reward for a 23andme app, I had two submissions. Beau Gunderson and Eric Jain (who turn out to be friends) both submitted short programs that fulfilled my request. The winning version is at Beau’s site. First, a little context. The point of this wasn’t to create a consumer experience, so don’t go to the link and expect one. It’s a download tool, no more and no less. But it didn’t exist before and now it does. What you will get if you click the link is the ability to store local copies of your genotype and health results. You will have to accept conditions to execute the app. Read them carefully before you do so. I am not sure if the 20 user limit is concurrent or total, and the tool may break at some point if it’s the latter until it goes through account review. This is alpha software, caveat emptor, you should probably wait to use it until lots of other people do, and so forth. I generated a zip file and downloaded it, for reference’s sake. Second, let’s thank 23andme for supplying the API and enabling the health GET commands. They didn’t have to do that at all, much less make it so easy to do. This doesn’t get done in seven hours without clean API design. Credit where it is deserved. More reason to hope they can get data into the FDA that gets approved and they keep DTC genomics economically accessible. Third, we now have the challenge of integrating the output into a Blue Button format, so it can benefit from the ecosystem of applications emerging there. I’m not sure I can pull that off in a twitter challenge but we’ll see - at least we’ve moved to the next step of the process. More in a bit. I’m going to wire this into a few places over the next week and think about it some more. This was both wonderful and unexpected in the best way. Thanks to everyone who joined the conversation and to 23andme for making the API available.

Pete Stark lost his House seat last night. He’d held it for 40 years. He is a divisive figure to some. He’s a hero for his legislative work to others. And I’m not going to address any of that, though I believe history will judge him very kindly on the merits of his record. I just want to thank a man who did more for me than I did for him. Pete hired me in 1996, when I was so wet behind the ears I could water plants just by sitting next to them. I was a legislative assistant in his Washington office, which is a fancy way to say I read through the legislation that the new Republican majority was ramming down our throats and tried to find some of the nastier bits and get them taken out. One little anecdote from those days. It was my first few weeks on the job and I was overwhelmed. A previous staffer dropped a massive set of files on my desk and said, “this is the Headwaters file - you’ll want to start reading it soon.” That night I got a call at home, after midnight, that a clause had been inserted into an appropriations bill that would allow the logging of Headwaters. I had to taxi into the office, start writing Dear Colleague letters, and help whip a campaign to get the clause taken out when the bill came to the floor. I had no idea what I was doing. I was 23. When the floor debate came, I was watching it on CSPAN, which ran 24 hours in the office. We were just across the street. Pete grabbed his 2-minute comments that I’d drafted off the printer and walked over. I saw him stride up on the TV, and to my horror, he started reading the press release, not the speech for the chambers. The press release was completely over the top. It called Charles Hurwitz, the then-owner of much of Headwaters, a “blood sucking corporate vampire” (not my words, but the product of a gifted, and awesome, press secretary). You can’t attack an individual like that on the floor of the House. Pete was immediately called for censure. I nearly wet my pants. I was surely going to be fired for this mistake. The time it took for him to walk back to the office was epic torture. He came back, clapped me on the back and said, “Aw hell, I decided to read the release because I thought it would be more fun - relax, kid.” He was a great boss. Pete gave me my first big professional break. Pete’s office is where I learned how to run a database. His Mac is where I wrote my first webpage, in plain text in 1996. He gave me my first bottle of great wine. His chief of staff got me backstage at a Jerry Jeff Walker show at the Birchmere, and took me to the National Democratic Club on the night Clinton was re-elected. Pete, I left before I ever got good at working for you. But you were good to me, and you served your country well. I hope somehow this gets to you. Thanks for your service, and thanks for giving a kid a lot of breaks a long time ago. ps - we won the debate on Headwaters, and I look forward to taking my son to see those trees, when he’s old enough, and telling him this story.

Yale University published a draft “Open Data Access policy” on November 15th to make available rhBMP-2 clinical trial data that they created in conjunction with Medtronic. Let me get this out of the way before I go negative: the fact that this policy exists, is on the web, and is open to comment is an unalloyed Good Thing. It’s progress. It’s to be commended. For those who aren’t initiates in the arcane world of open data or pharmaceutical testing, this is data related to a clinical trial of a kind of biological chemical found in our bodies that plays a role in bone development. Most of the time, this kind of data is collected once, then locked away, never to be seen or used again. One of the reasons drugs cost so much is that we never re-use the data from clinical trials, so we never learn anything from failures, or from secondary uses of data. It’s an incredibly inefficient system. This project at Yale is an attempt to address that inefficiency by making the data available. But that’s the extent of my nice words. What follows is a point by point review of the policy. The short version: this is not an “open data” policy. It’s a data access policy, and if they’re not going to fix it, they need to rename it. Because those of us who care about the definition of “open data” actually meaning something are going to criticize, persistently and loudly,  if there’s any attempt to claim the title for data under this policy. I apologize in advance for the length of this rant, but it’s a long policy. Also, they’re using the name of Yoda in vain.

Sam Arbesman’s new book, The Half Life of Facts, is coming out soon. I’ve had the pleasure of reading both a galley proof and an advance print, and I can tell you it’s a great book. Sam demonstrates, quantitatively, something we all know implicitly but probably don’t think about very much. Everything we know, or think we know, has an expiration date. For a long time, we “knew” that the sun revolved around the earth. For a long time, we “knew” that atoms were the smallest part of matter. But we learn. And we learn more. And what we “know” decays, over time. The Half Life of Facts is a great read for those who are interested in science, or philosophy of science, or who just need a reminder to have a little less hubris about how smart we are. Because to the future, we’re all phrenologists. Disclosure: Sam works at the Kauffman Foundation, where I am a non-resident Senior Fellow. But I like his book anyway.

So, big news today in the DTC genomics world was that 23andme has decided to publish an API. The blog announcement optimistically announces that there is “no monopoly on great ideas”and encourages developers to apply for access to write applications to the API. I’ve gotten quite a few requests for my thoughts on the announcement. I’m torn between wanting to praise 23andme and wanting to scream DANGER DANGER DANGER at the top of my lungs. So, I’m going to do both. First, bravo. Publishing an API is smart business move for 23andme, and holds the potential to create a lot of genomics apps on the data they hold. Second, DANGER. Publishing an API is a smart business move. Let me repeat that: it’s a business move. It’s not because they’re nice. There is a very serious difference between “we’ve opened our API to you” and freedom. Developers must apply for permission to make applications. Developers must tell 23andme, before developing, what their apps will do. And there is nothing that prevents the strategic shrinking of an API, or the subtle or not so subtle pressure to turn off applications that compete with core business functions or revenues of 23andme. ’ The fundamental problem is monetization. If you write an awesome app to a closed API, it makes good business sense to give you the Sopranos treatment. You make the app, it gets popular, you get the bust out. Twitter started with a wide open API and is basically phasing it out. Sucks if you invested your time there. Or if you’re like Dalton Caldwell, being strongarmed by Facebook when his app competed with FB’s App Center. So that’s the fundamental thing. Develop to a corporate API knowing full well that if you are successful, there’s a better chance that you wind up Scaltino and not Zuckerberg. And despite all the press that App.net is getting now, remember that social networks achieve network effects before they shut down functions in the API. And once a social network gets to that network effect, it’s very hard to build a competitor from the open. Anyone out there use Diaspora? Didn’t think so. Code carefully, my friends. And choose your monopolies wisely.

Today is the White House’s Champions of Change event celebrating Open Science. You can watch and join in at 1PM US Eastern time today. But on this day, I wanted to remind everyone that “open” is a word that comes with history and, more importantly, with meaning. It’s not a word that someone can take and sprinkle on their work and claim without understanding the history and the meaning. If someone does that, they are going to get bullshit called on them - like the Yale-Medtronic supposedly open data agreement, which is anything but open. So let’s get this clear. Just because you’re making something available that wasn’t previously available doesn’t qualify as open. Just because you’re reducing the transaction costs of access to something doesn’t qualify as open. Just because you’re involving more people than before doesn’t qualify as open. Open means that there is no prejudice against any kind of user, anywhere, any time. Open means that commercial use is allowed, in advance. Open means that new works, new research, new products are allowed, in advance. Open means following the Open Definition. Here’s the Definition. It’s short and sweet. “A piece of data or content is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and/or share-alike.” The reason for a definition is so that the word open actually means something. Open is a great word. But it has to mean something for it to mean anything. And it’s hard to meet this definition. It means you can’t be granular, or differential, or non-commercial, or academics only, or only for some kinds of uses in science and not for other kinds of uses. It means a bright line test that a project either meets or doesn’t meet. The Yale-Medtronic example is a classic case of misappropriation of the word open. It’s anything but. Yet there goes the science establishment trumpeting it as such. If “open” is going to mean something in science the way it means something in culture and in software, those of us who’ve spent years toiling in the trenches have to collectively examine, carefully, every claim to open science. And we have to speak truth to power, to hold those who would claim openness as their mantle to the definitions and call them out when they fail to meet them. Otherwise, the nascent open science movement will suffocate under the weight of semi-open science, content that is segregated by incompatible and overly restrictive licenses, data that comes with complex terms of use, service, field of use restrictions, and patents that pop up out of the blue when open projects attempt to scale. Being open - really open - is hard to do. It doesn’t give the people what they want. As Bob Young noted in his keynote at this year’s Sage Congress, what people wanted out of Red Hat software was for it to run Microsoft Office. He didn’t give them that. He gave them what they needed, which was the right and the power to control their own operating systems. And people thought he was crazy for not giving them what they wanted, for not compromising on open, right up until Red Hat was so successful that everyone agreed it had been obvious all along that open was the smart choice. It wasn’t easy being open in software, then. It isn’t easy now in science. But the value comes over the long term from the decision of a small set of people being unreasonably committed to making true public goods. Today’s event is a small but pivotal step in recognizing those people, and in carrying those true public goods forward.