David Weinberger's Blog, page 88

My inner voice

As I have mentioned before, I have what I think is particularly strong inner narrator, especially when I’m alone. I’ve always attributed this to my proclivities towards writing, since my narrator drafts and often redrafts descriptions of what I’m experiencing. It’s either that or I’m a little schizo. Or both.

I am today at the beginning of a three week trip, during which I will be spending a fair bit of time alone. My inner narrator has already kicked in, and here’s the thing: It’s now Mike and Tom Eat Snacks.

I have to say it’s a little disconcerting having two of them. Not for me it isn’t. But it is for me. I’ll tell you exactly why: It’s because your inner Mike and Tom include an internalized Mike and Tom, so you have a little fractal regression thing going on that’s got to be a little upsetting. Yes, that’s true; it’s because I’m a people person. Whereas I’m just a person person. Exactly right.

DPLA West meeting online

The sessions from the DPLA Plenary meeting on April 27 in SF are now online. Here’s the official announcement:

…all media and work outputs from the two day-long events that made up DPLA West–the DPLA workstream meetings held on April 26, 2012 at the San Francisco Public Library, and the public plenary held on April 27, 2012 at the Internet Archive in San Francisco, CA–are now available online on the “DPLA West: Media and Outputs” page:http://dp.la/get-involved/events/dplawest/dpla-west-media-and-outputs/.

There you will find:

Key takeaways from the April 26, 2012 workstream meetings;

Notes from the April 27, 2012 Steering Committee meeting;

Complete video of the April 27, 2012 public plenary;

Photographs and graphic notes from the public plenary;

Video interviews with DPLA West participants;

And audio interviews with DPLA West scholarship recipients.

More information about DPLA West can be found online at http://dp.la/get-involved/events/dplawest/.

Folks from the Harvard Library Innovation Lab and the Berkman Center worked long and hard to create a prototype software platform for the DPLA in time for this event. The platform is up and gives live access to about 20M books and thousands of images and other items from various online collections. The session at which we introduced, explained, and demo’ed it is now available for your viewing pleasure. (I was interim head of the project.)

Why is knowledge so funny?

…at least on the web it tends to be. That in any case is the contention of my latest column in KMworld.

Bake sale for NASA

More than a dozen universities are holding bake sales for NASA. The aim is to raise awareness, not money.

To me, NASA is a bit like a public library: No matter what, you want your town and your country to visibly declare their commitment to the value of human curiosity.

 

In other science news, attempts to replicate the faster-than-light neutrino results have confirmed that the spunky little buggers obey the universal traffic limit.

The system works! Even if you don’t screw in the optical cables tightly.

[2b2k] The Internet, Science, and Transformations of Knowledge

[Note that this is cross posted at the new Digital Scholarship at Harvard blog.]

Ralph Schroeder and Eric Meyer of the Oxford Internet Institute are giving a talk sponsored by the Harvard Library on Internet, Science, and Transformations of knowledge.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Ralph begins by defining e-research as “Research using digital tools and digital data for the distributed and collaborative production of knowledge.” He points to knowledge as the contentious term. “But we’re going to take a crack at why computational methods are such an important part of knowledge.” They’re going to start with theory and then move to cases.

Over the past couple of decades, we’ve moved from talking about supercomputing to the grid to Web 2.0 to clouds and now Big Data, Ralph says. There is continuity, however: it’s all e-research, and to have a theory of how e-research works, you need a few components: 1. Computational manipulability (mathematization) and 2. The social-technical forces that drive that.

Computational manipulability. This is important because mathematics enables consensus and thus collaboration. “High consensus, rapid discovery.”

Research technologies and driving forces. The key to driving knowledge is research technologies, he says. I.e., machines. You also need an organizational component.

Then you need to look at how that plays out in history, physics, astronomy, etc. Not all fields are organized in the same way.

Eric now talks, beginning with a quote from a scholar who says he now has more information then he needs, all without rooting around in libraries. But others complain that we are not asking new enough questions.

He begins with the Large Hadron Collider. It takes lots of people to build it and then to deal with the data it generates. Physics is usually cited as the epitome of e-research. It is the exemplar of how to do big collaboration, he says.

Distributed computation is a way of engaging citizens in science, he says. E.g. Galaxy Zoo, which engages citizens in classifying galaxies. Citizens have also found new types of galaxies (“green peas”), etc. there. Another example: the Genetic Association Information Network is trying to find the cause of bipolarism. It has now grown into a worldwide collaboration. Another: Structure of Populations, Levels of Abundance, and Status of Humpbacks (SPLASH), a project that requires human brains to match humpback tails. By collaboratively working on data from 500 scientists around the Pacific Rim, patterns of migration have emerged, and it was possible to come up with a count of humpbacks (about 15-17K). We may even be able to find out how long humpbacks live. (It’s a least 120 years because a harpoon head was found in one from a company that went out of business that long ago.)

Ralph looks at e-research in Sweden as an example. They have a major initiative under way trying to combine health data with population data. The Swedes have been doing this for a long time. Each Swede has a unique ID; this requires the trust of the population. The social component that engenders this trust is worth exploring, he says. He points to cases where IP rights have had to be negotiated. He also points to the Pynchon Wiki where experts and the crowd annotate Pynchon’s works. Also, Google Books is a source of research data.

Eric: Has Google taken over scholarly research? 70% of scholars use Google and 66% use Google Scholar. But in the humanities, 59% go to the library. 95% consult peers and experts — they ask people they trust. It’s true in the physical sciences too, he says, although the numbers vary some.

Eric says the digital is still considered a bit dirty as a research tool. If you have too many URLS in your footnotes it looks like you didn’t do any real work, or so people fear.

Ralph: Is e-research old wine in new bottles? Underlying all the different sorts of knowledge is mathematization: a shared symbolic language with which you can do things. You have a physical core that consists of computers around which lots of different scholars can gather. That core has changed over time, but all offer types of computational manipulability. The Pynchon Wiki just needs a server. The LHC needs to be distributed globally across sites with huge computing power. The machines at the core are constantly being refined. Different fields use this power differently, and focus their efforts on using those differences to drive their fields forward. This is true in literature and language as well. These research technologies have become so important since they enable researchers to work across domains. They are like passports across fields.

A scholar who uses this tech may gain social traction. But you also get resistance: “What are these guys doing with computing and Shakespeare?”

What can we do with this knowledge about how knowledge is changing? 1. We can inform funding decisions: What’s been happening in different fields, how they affected by social organizations, etc. 2. We need a multidisciplinary way of understanding e-research as a whole. We need more than case studies, Ralph says. We need to be aiming at developing a shared platform for understanding what’s going on. 3. Every time you use these techniques, you are either disintermediating data (e.g., Galaxy Zoo) or intermediating (biomedicine). 4. Given that it’s all digital, we as outsiders have tremendous opportunities to study it. We can analyze it. Which fields are moving where? Where are projects being funded and how are they being organized? You can map science better than ever. One project took a large chunk of academic journals and looked in real time at who is reading what, in what domain.

This lets us understand knowledge better, so we can work together better across departments and around the globe.

Q&A

Q: Sometimes you have to take a humanities approach to knowledge. Maybe you need to use some of the old systems investigations tools. Maybe link Twitter to systems thinking.

A: Good point. But caution: I haven’t seen much research on how the next generation is doing research and is learning. We don’t have the good sociology yet to see what difference that makes. Does it fragment their attention? Or is this a good thing?

Q: It’d be useful to know who borrows what books, etc., but there are restrictions in the US. How about in Great Britain?

A: If anything, it’s more restrictive in the UK. In the UK a library can’t even archive a web site without permission.

A: The example I gave of real time tracking was of articles, not books. Maybe someone will track usage at Google Books.

Q: Can you talk about what happens to the experience of interpreting a text when you have so much computer-generated data?

A: In the best cases, it’s both/and. E.g., you can’t read all the 19th century digitized newspapers, but you can compute against it. But you still need to approach it with a thought process about how to interpret it. You need both sets of skills.

A: If someone comes along and says it’s all statistics, the reply is that no one wants to read pure stats. They want to read stats put into words.

Q: There’s a science reader that lets you keep track of which papers are being read.

A: E.g., Mendeley. But it’s a self-selected group who use these tools.

Q: In the physical sciences, the more info that’s out there, it’s hard to tell what’s important.

A: One way to address it is to think about it as a cycle: as a field gets overwhelmed with info, you get tools to concentrate the information. But if you only look at a small piece of knowledge, what are you losing? In some areas, e.g., areas within physics, everyone knows everyone else and what everyone else is doing. Earth sciences is a much broader community.

[Interesting talk. It's orthogonal to my own interests in how knowledge is becoming something that "lives" at the network level, and is thus being redefined. It's interesting to me to see how this look when sliced through at a different angle.]

1,000 downloads

I learned yesterday from Robin Wendler (who worked mightily on the project) that Harvard’s library catalog dataset of 12.3M records has been bulk downloaded a thousand times, excluding the Web spiderings. That seems like an awful lot to me, and makes me happy.

The library catalog dataset comprises bibliographic records of almost all of Harvard Library’s gigantic collection. It’s available under a CC 0 public domain license for bulk download, and can be accessed through an API via the DPLA’s prototype platform. More info here.

Remixing the President

Aaron Shaw has a very interesting post on what sure looks like contradictory instructions from the White House about whether we’re free to remix photos that have been released under a maximally permissive U.S. Government license. Aaron checked in with a Berkman mailing list where two theories are floated: It’s due to a PR reflex, or it’s an attempt to impose a contractual limitation on the work. There have been lots of other attempts to impose such limitations on reuse, so that “august” works don’t end up being repurposed by hate groups and pornographers; I don’t know if such limitations have any legal bite.

Dan Jones places himself clearly on the side of remixing. Here’s the White House original:

And here’s Dan’s gentle remix:

Hey look out Mr. President! A supposedly unauthorized derivative work is headed right toward you!! (alert: @aaronshaw) twitter.com/blanket/status…

— Daniel Dennis Jones (@blanket) June 4, 2012

Bring it, Holder! :)

Distribution models that work. Are we finally getting it (them) right?

Is it just me, or are we in a period when new distribution models are burgeoning? For example:

1. Kickstarter, of course, but not just for startups trying to kickstart their business. For example, Amanda Palmer joined the Louis CK club a couple of days ago by raising more than a million bucks there for her new album. (She got my $5 :) As AFP has explained, she is able to get this type of support from her fans because she treats her fans honestly, frankly, with respect, and most of all, with trust.

2. At VODO, you can get your indie movie distributed via bittorrent. If it starts taking off, VODO may feature it. VODO also works with sponsors to support you. From my point of view as a user, I torrented “E11,” a movie about rock climbing, for free, or I could have paid $5 to stream it for 10 days with the ability to share the deal with two other people. VODO may be thinking that bittorrenting is scary enough to many people that they’ll prefer to get it the easy way by paying $5. VODO tells you where your money is going (70% goes to the artist), and treats us with respect and trust.

3. I love Humble Bundle as a way of distributing indie games. Periodically the site offers a bundled set of five games for as much as you want to pay. When you check out, you’re given sliders so you can divvy up the amount as you want among the game developers, including sending some or all to two designated charities. If you pay more than the average (currently $7.82), you get a sixth game. Each Bundle is available for two weeks. They’ve sold 331,000 bundles in the past three days, which Mr. Calculator says comes to $2,588,420. All the games are all un-copy-protected and run on PCs and Macs. Buying a Humble Bundle is a great experience. You’re treated with respect. You are trusted. You have an opportunity to do some good by buying these games. And that’s very cool, since usually sites trying to sell you stuff act as if buying that stuff is the most important thing in the world.

4. I’m hardly the first to notice that Steam has what may be the best distribution system around for mass market entertainment. They’re getting users to pay for $60 games that they otherwise might have pirated by making it so easy to buy them, and by seeming to be on the customer’s side. You buy your PC game at their site, download it from them, and start it up from there. They frequently run crazy sales on popular games for a couple of days, and the game makers report that there is enough price elasticity that they make out well. If I were Valve (the owners of Steam), I’d be branching out into the delivery of mainstream movies.

There’s of course much much more going on. But that’s my point: We seem to be figuring out how to manage digital distribution in new and successful ways. The common threads seem to be: Treat your customers with respect. Trust them. Make it easy for them to do what they want to do with the content. Have a sense of perspective about what you’re doing. Let the artists and the fans communicate. Be on your customers’ side.

Put them all together and what do you have? Treat us like people who care about the works we’re buying, the artists who made them, about one another, and about the world beyond the sale.

Interop: The Book

John Palfrey and Urs Gasser are giving a book talk at Harvard about their new book, Interop. (It’s really good. Broad, thoughtful, engaging. Not at all focused on geeky tech issues.) NOTE: Posted without re-reading

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

JP says the topic of interop seems on the face of it like it should be “very geeky and very dull.” He says the book started out fairly confined, about the effect of interop on innovation. But as they worked on it, it got broader. E.g., the Facebook IPO has been spun about the stock price’s ups and downs. But from an interop perspective, the story is about why FB was worth $100B or more when its revenues don’t indicate any such thing. It’s because FB’s interop in our lives make it hard to extract. But from this also come problems, which is why the subtitle of the book Interop talks about its peril.

Likewise, the Flame virus shows that viral outbreaks cannot be isolated easily. We need fire breaks to prevent malware from spreading.

In the book, JP and Urs look at how railroad systems became interoperable. Currency is like that, too: currencies vary but we are able to trade across borders. This has been great for the global economy, but it make problems. E.g., the Greek economic meltdown shows the interdependencies of economies.

The book gives a concise def of interop: “The ability to transfer and render userul data and other information across systems (including organizations), applications or components.” But that is insufficient. The book sees interop more broadly as “The art and science of working together.” The book talks about interop in terms of four levels: data, tech, humans, and institutions.

They view the book as an inquiry, some of which is expressed in a series of case studies and papers.

Urs takes the floor. He’s going to talk about a few case studies.

First, how can we make our cities smarter using tech? (Urs shows an IBM video that illustrates how dependent we are on sharing information.) He draws some observations:

Solutions to big societal problems increasingly depend on interoperability — from health care to climate change.

Interop is not black or white. Many degrees. E.g., power plugs are not interoperable around the world, but there are converters. Or, international air travel requires a lot of interop among the airlines.

Interop is a design challenge. In fact, once you’ve messed up with interop, it’s hard to make it right. E.g., it took a long time to fix air traffic control systems because there was a strongly embedded legacy system.

There are important benefits, including systems efficiency, user choice, and economic growth.

Urs points to their four-layer model. To make a smart city, the tech the firefighters and police use need to interop, as do their data. But at the human layer, the language used to vary among branches; e.g., “333″ might code one thing for EMTs and another for the police. At the institutional layer, the laws for privacy might not be interoperable, making it hard for businesses to work globally.

Second example: When Facebook opened its APIs so that other apps could communicate with FB, there was a spike in innovation; 4k apps were made by non-FB devs that plug into FB. FB’s decision to become more interoperable led to innovation. Likewise for Twitter. “Much of the story behind Twitter is an interop question.”

Likewise for Ushahidi; after the Haitian earthquake, it made a powerful platform that enabled people to share and accumulate info, mapping it, across apps and devices. This involved all layers of the interop stack, from data to institutions such as the UN pitching in. (Urs also points to safe2pee.org :)

Observations:

There’s a cycle of interop, competition, and innovation.

There are theories of innovation, including generativity (Zittrain), user-driven innovation (Von Hippel) and small-step innocations (Christensen).

Caveat: More interop isn’t always good. A highly interop business can take over the market, creating a de facto monopoly, and suppressing innovation.

Interop also can help diffuse adoption. E.g., the transition to high def tv: it only took off once the tvs were were able to interoperate between analog and digital signals.

Example 3: Credit cards are highly interoperable: whatever your buying opportunity is, you can use a selection of cards that work with just about any bank. Very convenient.

Observations:

this level of interop comes with costs and risks: identity thefts, security problems, etc.

The benefits outweigh the risks

This is a design problem

More interop creates more problems because it means there are more connection points.

Example 4: Cell phone chargers. Traditionally phones had their own chargers. Why? Europe addressed this by the “Sword of Damocles” approach that said that if the phone makers didn’t get their act together, the EC would regulate them into it. The micro-USB charger is now standard in Europe.

Observations:

It can take a long time, because of the many actors, legacy problems, and complexity.

It’s useful to think about these issues in terms of a 2×2 of regulation/non-regulation, and collaborative-unilateral.

JP back up. He is going to talk about libraries and the preservation of knowledge as interop problems. Think about this as an issue of maintaining interop over time. E.g., try loading up one of your floppy disks. The printed version is much more useful over the long term. Libraries find themselves in a perverse situation: If you provide digital copies of books, you can provide much less than physical books. Five of the 6 major publishers won’t let libraries lend e versions. It’d make sense to have new books provided on an upon standard format. So, even if libraries could lend the books, people might not have the interoperable tech required to play it. Yet libraries are spending more on e-books, and less on physical. If libraries have digital copies and not physical copies, they are are vulnerable to tech changes. How do we insure that we can continuously update? The book makes a fairly detailed suggestion. But as it stands, as we switch from one format to another over time, we’re in worse shape than if we had physical books. We need to address this. “When it comes to climate change, or electronic health records, or preservation of knowledge, interop matters, both as a theory and as a practice.” We need to do this by design up front, deciding what the optimal interop is in each case.

Q&A

Q: [doc searls] Are there any places where you think we should just give up?

A: [jp] I’m a cockeyed optimist. We thought that electronic health records in the US is the hardest case we came across.

Q: How does the govt conduct consultations with experts from across the US. What would it take to create a network of experts?

A: [urs] Lots of expert networks that have emerged, enabled by tech that fosters from the bottom up human interoperability.

A: [jp] It’s not clear to me that we want that level of consultation. I don’t know that we could manage direct democracy enabled in that way.

Q: What are the limits you’d like to see emerge on interop. I.e., I’m thinking of problems of hyper-coherence in bio: a single species of rice or corn that may be more efficient can turn out to be with one blight to have been a big mistake. How do you build in systems of self-limit?

[urs] We try to address this somewhat in a chapter on diversity, which begins with biodiversity. When we talk about interop, we do not suggest merging or unifying systems. To the contrary, interop is a way to preserve diversity, and prevent fragmentation within diversity. It’s extremely difficult to find the optimums, which varies from case to case, and to decide on which speed bumps to put in place.

[jp] You’ve gone to the core of what we’re thinking about.

Q: Human autonomy, efficiency, and economic growth are three of the benefits you mention, but they can be in conflict with one another. How important are decentralized systems?

[urs] We’re not arguing in favor of a single system, e.g., that we have only one type of cell phone. That’s exactly not what we’re arguing for. You want to work toward the sweet spot of interop.

[jp] They are in tension, but there are some highly complex systems where they coexist. E.g., the Web.

Q: Yes, having a single cell phone charger is convenient. But there may be a performance tradeoff, where you can’t choose the optimum voltage if you standard on 5V. And an innovation deficit: you won’t get magnetic plugs, etc.

[urs] Yes. This is one of the potential downsides of interop. It may lock you in. When you get interop by choosing a standard, you freeze the standard for the future. So one of the additional challenge is: how can we incorporate mechanisms of learning into standards-setting?

Cell phone chargers don’t have a lot of layers on top of them, so the standardization doesn’t have quite the ripples through generativity. And that’s what the discussion should be about.

The virtue of self-restraint

Last night was the annual Berkman dinner. Lovely. It inevitably turned into a John Palfrey love fest, since he is leaving Harvard very soon, and he is much beloved.

People stood and spoke beautifully and insightfully about what John has meant to them. (Jonathan Zittrain and Ethan Zuckerman in addition were predictably hilarious.) But Terry Fisher gave us an insight that was so apt about John and so widely relevant that I’ll share it.

Terry listed some qualities of John’s. The last he talked about started out as John’s very occasional sarcasm; he can be bitingly perceptive about people, but always in private. So, said Terry, JP’s remarked-upon and remarkable niceness and kindness are not due to naivete. Rather, they arise in part from another of John’s virtues: self-restraint. And, from that, said Terry, comes much of the kindness that generally characterizes the Berkman Center.

That struck me not only as true of John, but as such an important quality for civic discourse. Self-restraint is an enabling virtue: its exercise results in a further qualities that make life on a crowded planet more fruitful and enjoyable.