Phil Desenne begins with a brief history of annotation tools at Harvard. There are a lot, for annotating from everything to texts to scrolls to music scores to video. Most of them are collaborative tools. The collaborative tool has gone from Adobe AIR to Harvard iSites, to open source HTML 5. “It’s been a wonderful experience.” It’s been picked up by groups in Mexico, South America and Europe.

Phil works on edX. “We’re beginning to introduce annotation into edX.” It’s being used to encourage close reading. “It’s the beginning of a new way of thinking about teaching and assessing students.” Students tag the text, which “is the beginning of a semantic tagging system…Eventually we want to create a semantic ontology.”

What are the implications for the “MOOC Generation”? MOOC students are out finding information anywhere they can. They stick within a single learning management system (LMS). LMS’s usually have commentary tools “but none of them talk with one another . Even within the same LMS you don’t have cross-referencing of the content.” We should have an interoperable layer that rides on top of the LMS’s.

Within edX, there are discussions within classes, courses, tutorials, etc. These should be aggregated so that the conversations can reach across the entire space, and, of course, outside of it. edX is now working on annotation systems that will do this. E.g., imagine being able to discuss a particular image or fragments of videos, and being able to insert images into streams of commentary. Plus analytics of these interations. Heatmaps of activity. And a student should be able to aggregate all her notes, journal-like, so they can be exported, saved, and commented on, “We’re talking about a persistent annotation layer with API access.” “We want to go there.”

For this we need stable repositories. They’ll use URNs.

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Diana Kimball [twitter:dianakimball] is giving a Berkman lunchtime talk on coding as a liberal art. She’s a Berkman Fellow and at the Harvard Business School. (Here are some of her posts on this topic.)

She says that she’s loved computers since she was a kid. But when she went to Harvard as an undergrad she decided to study history, in part because there’s a natural specialization that happens in college: the students who come in as coders are fantastic at coding, whereas Diana had greater strengths as a writer of prose. She found HTML and programming intimidating. But in her third year, she got interested in coding and Internet culture. She was one of the founders of ROFLcon [yay!]. She got hired by Microsoft after college, as a technical product manager with the Powerpoint team in Silicon Valley. “This was culture shock in the best possible way.”

When she graduated in 2009, she and some friends started found the SnarkMarket blog that considers what the new liberal arts might be (inspired by Kottke). She wrote an essay that’s a proposal for coding and decoding. She reads it. (It’s short.) An excerpt:

Coding and Decoding is about all modes of communication, and all are in its view. But it is built with particular attention to the future, and what that future will be like. Technological experts can seem like magicians, conjuring effects wordlessly. By approaching that magic as a collection of component parts instead of an indivisible miracle, we can learn to see through these sleights of typing hands. In seeing through, we will learn to perform them ourselves; and think, as magicians, about the worlds we will build.

Language, now, is about more than communication. It is the architecture behind much of what we experience. Understanding that architecture will allow us to experience more.

Her boyfriend taught her how to code. They spent a lot of time on it. “He picked up on something I’d said and took it seriously.” After two years at Microsoft, she was enthusiastic, but still a beginner. It wasn’t until she started at Harvard Business School that coding really took off for her. The entrepreneurial atmosphere encouraged her to just do it. Plus, she was more of a geek than most of the other students. “This was great for my identity, and for my confidence.” She also found it a social refuge. “It takes a lot of time to get over the hump.” She refers to Ellen Ullman’s “Close to the Machine” that talks about the utility of being arrogant enough to obsess over a project, cycling back to humility.

She decided to code up her own site for a project for school, even though the team had been given the money to hire devs for the task. Last fall she took the famous CS50 course [Harry Lewis, who created the course in about 1981, is sitting next to me.] CS50 teaches C, targeted at people who are either taking only that one class, or are going to take many more. For her final project, she did a project that used multiple APIs that she was very proud of. She’s also proud of her Ruby projects folder. Each project is something she was trying to teach herself. She’s more proud of the list than the finished products.

“Learning to code means reclaiming patience and persistence and making them your stubborn own.” [nice]

Ideally, everyone should be exposed to programming, starting at 5 yrs old, or even earlier, Diana says. Seymore Papert’s “Mind-Storms” has greatly influenced her thinking about how coding fits into education and citizenship. At a university, it ought to be taken as a liberal art. She quotes Wikipedia’s definition. And if “grammar, rhetoric, and logic were the core of the liberal arts,” then that’s sound like coding. [Hmm.] What the law was to the liberal arts, programming ought to be, i.e., that which you try if you don’t know what else to do with your liberal arts degree.

Why isn’t it seen that way? When computer scientists teach you, they teach they way they learned: at school. But many of the best programmers are self-taught. CS50 does give a variety of assignments, but it’d be better if students solved their own problems much earlier.

But the number one problem is the academic attitude, she says. Students get fixated on the grade, even when it doesn’t matter. Coding is critical for children because debugging is part of it, as Papert says. But grades are based on the endpoints. Coding is much more like life: You’re never done, you can always make it better.

Diana has a proposal. Suppose coding classes were taught like creative writing workshops. Take it whenever you’re ready. Taught by hackers, esepcially autodidacts. It’d vary in substance — algorithms, apis, etc. — and you’d get to choose. You’d get to see something on screen that you’d never seen before And you’d be evaluated on ingenuity and persistence, rather than only on how well your code runs.

She says what her syllabus would look like:

• Robin Sloan’s novel “Mr. Penumbra’s 24-Hour Bookstore.”

• Critical study of selected Github pull requests — how open source projects work, how to rise in the community

• Bring in an API evangelist from an interesting company, maybe bring in two and let

• Neal Stephenson’s “In the Beginning Was the Command Line“

“Coding should be taught in the same breath as expository writing… Everyone deserves to be exposed to it.” She’s not sure if it should be required.

She quotes Papert: “…the most powerful idea of all is the idea of powerful ideas.” There’s no better example of this, she says, than open source software. And David Foster Wallace’s commencement address: “Learning how to think really means learning to exercise some control over how and what you think…If you cannot exercise this sort of choice in adult life, you will be totally hosed.” Diana says that’s her. She was wrapped up in writing from an early age. She has a running internal commentary. [Join the club!] Coding swaps in a different monologue, one in which she’s inventing thing. That’s the greatest gift: her internal monologue is much more useful and interesting. “If you wanted to be a novelist in 1900, you’d want to be a programmer today.” The experience of creating something that people use is so motivating.

Q&A

Q: Would you be willing to webcast yourself programming and let people join in? I do this all the time when at hackathons. I think, OMG, there must be 10,000 kids in India who want to be here. And so here they are. “Hackers at Berkeley” does this really well.

A: That’s awesome. I want more people to have more access to that experience of sharing.

Q: Are you familiar with RailsBridge — non-computer scientists who are teaching themselves how to code via weekend workshops.

A: RailsBridge is extraordinary. It’s great to see this happening outside of the university context.

A: [me] Great talk, and I’m a humanities major who spends most of his hobby time programming. But aren’t you recommending the thing that you happen to love? And programming as opposed to traditional logic is an arbitrary set of rules…

Q: Yes, but it would be really useful if more people loved it. We could frame it in a way that is exciting for humanities majors. I’m proposing an idea rather than making an airtight argument. “You’re basically right but I don’t really care” (she says laughing :).

Q: I like your idea of teaching it like a writers workshop so that it doesn’t turn into just another course. But I’m not sure that colleges are the best at doing that.

A: not everyone loves programming.

Q: [harry lewis] I take responsibility for eliminating the Harvard requirement for a programming course. Also, take a look at code.org. Third, the academic world treats computer science the way it does because of our disciplinary specialization. That label — computer science — came about in the context of fields like political science, and arose when computers were used not for posting web sites but for putting people on the Moon where a bug could kill someone. The fact that CompSci exists in academic departments will make it very difficult for your vision of computing to exist, just as creative writing is often an uneasy fit into English curricula.

A: That’s very fair. I know it’d be hard. RIT has separate depts for CompSci and coding.

Q: There’s an emergent exploration of coding in Arts schools, with a much more nimble, plug and play approach, very similar to the one you describe. My question: What do the liberal arts have to offer coding? Much of coding is quite new, e.g., open source. These could be understood within a historical context. Maybe these need to be nurtured, explored, broken. Does seeing coding as a liberal art have something to offer sw development?

A: ITP is maybe the best example of artists working with coders. Liberal Arts can teach programmers so much!

Q: Can we celebrate failure? That’d be a crucial part of any coding workshop.

A: Yes! Maybe “find the most interesting bug” and reward introspection about where you’ve gone wrong. But it’s hard in a class like CS50 where you’re evaluating results.

Q: This is known as egoless programming. It’s 40 years old, from Weinberger [no relation].

Q: You’re making a deeper point, which is not just about coding. The important thing is not the knowledge you get, but the way you get there. Being self-reflective about you came about how you learn. You can do this with code but with anything.

A: You’re so right. Introspection about the meta-level of learning is not naturally part of a course. But Ruby is an introspective language: you can ask any object what it is, and it will tell you. This is a great mirror for trying to know yourself better.

Q: What would you pick to teach?

A: I love Ruby. It would be a good choice because there’s a supportive community so students can learn on their own afterwards, and it’s an introspective language. And the lack of ornament in Ruby (no curly braces and little punctuation) makes it much more like English. The logic is much more visible. (My preference is Sinatra, not Rails.)

Q: What sort of time commitment the average person would have to put in to have a basic grasp of a programming language? Adults vs. children learning it?

A: I’d love to see research on this. [Audience: Rottmeyers, CMU (?)] A friend of mine reported he spent 20 hours. The learning curve is very halting at first. It’s hard to teach yourself. It helps to have a supportive in-person environment. CS50 is a 10-20 hour commitment/week and who has that sort of time except for fulltime students? To teach yourself, start out a few hours a time.

Q: How about where the MOOCs are going? Can you do a massively online course in compSci that would capture some of what you’re talking about?

A: The field is so focused on efficiency that MOOCs seem like an obvious idea. I think that a small workshop is the right way to start. CS50 requires so much fear of failure and resilience that it wouldn’t have been a good way for me to start. At CS50, you can’t let others read your code.

Q: We shouldn’t put together Computer Science and programming. Programming is just a layer of expression on top of computer science. You don’t need compSci to become a programmer. And the Net is the new computer; we’re gluing together services from across the Net. That will change how people think about programming because eveyrone will be able to do it. The first language everyone should learn is ifttt.com

Q: I’m a NY Times journalist. I love languages. And I love the analogy you draw. I’m 30. Do you think coding is really essential? Would it open my eyes as a journalist?

A: It’s never too late. If you keep asking the question, you should probably do it. You don’t have to be good at it to get a lot out of it. It’s so cool that your children are learning multiple languages including coding. Learn alongside them.

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Molly Sauter [twitter:oddletters] (from Berkman and the Center for Civic Media at MIT) is giving a lunchtime Berkman talk. She’s going to focus on Operation Payback, the Dec. 2010 action by Anonymous against those financial services that cut off Wikileaks after Wikileaks made available a massive leak of State Dept. cables. Operation Avenge Assange tried to bring down the sites of those services. Molly sees this as an evolution in media activism, expanding on the use of DDOS tactics by groups in the 1990s; [DDOS = distributed denial of service: flooding a site beyond its capacity to respond, and doing so from multiple sites.]

Molly begins with a simple explanation of DDOS. The flooding can come from a single computer (unlikely), via a volunteer botnet, or botnets that infect other computers; the botnets communicate with a central computer, pounding on the target until it can’t handle the traffic.

Old school activists think of DDOS as a form of censorship, and thus it is not acceptable. For many digitally-enabled activists (e.g., Electronic Disturbance Theater) DDOS is a form of disobedience. For EDT, DDOS is an auxiliary form of activism: “DDOS is something you do when you’re out on the streets so your computer can be at home protesting.” DDOS is sometimes seen as a type of sit-in, although Molly thinks this is inapt. For some, DDOS is a direct form of protest, and in others, it’s an indirect and symbolic action. Anonymous melds these approaches: influence via technology + influence via media + direct action disruption.

Electronic Disturbance Theater [EDT] used Flood Net, a tool that “hurls bits” but that also lets you send a message to show up in the target computer’s error log. Cleverly, if your issue is human rights, the log might read “Human rights is not found on this server.” But, Molly says, these logs are only read by the admin, so it’s really a way for the activist to yell something for the sake of yelling. The EDT restricted targets of Flood Net and set scheduled times. EDT open sourced it in 1999. The language on the Floor Net site is comprehensible only to people who already know about the issues, e.g., Mexican Neo-Liberalism. It is intimidating for those outside of the circle. It is also very tied to a view of activism that ties actions to individuals â?? anonymous individuals, but using Flood Net requires the action of a person.

LOIC — low orbit ion cannon— was developed maybe around 2006, and forked in 2008. By Dec. 2010, versions could run on just about anything — Windows, Mac, on mobiles, within a browser… Molly goes through the differences in the different versions of it. They let you type in a URL, set some options that are set to defaults, and then you press a button. Done! (LOIC is the boss weapon from the game Command & Conquer). The button you press in the abatishchev version is labeled “IMMA CHARGIN MAH LAZER,” a popular meme. It has the same messaging functionality as Flood Net. The default message derives from a 4chan bestiality rape meme that Molly urges us not to google. This version “is focused on the 4chan Anonymous culture set.”

She then compares this to the NewEraCracker version. Very similar. Same “Imma chargin mah lazer” meme, but the rape meme is gone. Instead, it says “u done goofed,” the popular Jessi Slaughter meme. Jessie pissed off Anonymous, so Anonymous sent lots of pizza to her house. Her father posted a defensive video that wasn’t very smart about the Net, which got widely distributed, and which contained the line “you done goofed.” This message is more confrontational than the other version which the recipient would be unlikely to understand at all. This version of LOIC also has a “fucking hive mind mode” that lets you automate the process entirely by plugging it into an IRC server to use volunteer computers [I think].

These tools, especially the second, created a community of activists, especially in hive mind mode. There are many LOIC tutorial videos on YouTube. This reaches out to new people to join, unlike EDT’s use of language that appeals only to those already in the know. Because anyone can use it, it helps Anonymous become a community of trust.

Anonymous has also pushed DDOS as a media manipulation tactic, and used media for recruitment. Molly doesn’t know if it was a conscious decision, but DDOS ended up as a recruitment tactic.

During the four days of Operation Payback, the media coverage was very confused. For example the media weren’t sure that DDOS is illegal. (It is.) Even Gizmodo got wrong how risky DDOS is for the attacker; it wrongly claimed that the target’s log files don’t record the incoming connections during DDOS. Experienced users know to anonymize their packets, but those who came in new and used this easy-to-use tool often did not protect themselves. The Paypal 16 now under indictment were caught because PayPal stored the top 1000 IP addresses. Much of the coverage just quoted Anonymous at length. “Anonymous is a very horizontal org and there’s no press person to talk to,” but, Molly says, there was a “press IRC channel” but the media didn’t know how to use it. Some mainstream articles linked to download sites for LOIC, which may have encouraged people to download it without understanding the legality of using it.

Conclusions: “Operation Payback’s success was due to a confluence of tech, community, and news media factors. Anonymous’ use of DDOS represent an innovation in participant population and tool design. And Anonymous pushes the reframing of DDOS as a tool of media manipulation and biographical impact [how the participants think about themselves], not direct action.”

Q&A

Q: Is the paypal list public?

A: Nope.

Q: Can you bring your research up to date?

A: I’m writing my thesis now. So, no.

Q: How does being identified play into the historical mindset?

A: I got into this topic because I wanted to do my thesis on activism and anonymity. Anonymous challenges the assumption that if you’re anonymous, you’re not serious about your activism. The cultural preference for identified activism comes from the 1960s civil disobedience movement, which in turns comes from Thoreau: you break the law and accept punishment for it. But that privileges those who won’t lose their house and their family if arrested. This puts activism on the shoulders of a particular class. Anonymous disagrees. It says you can engage in civil disobedience without personal consequence.

Q: The Federalist Papers were anonymous because it implicitly was saying that the ideas are important enough not to need names attached. Anonymous not only escapes punishment, it makes it effortless â?? the amount of effort you put in is indistinguishable from that of someone whose computer was infected by a bot.

A: This is the slacktivism argument. Slacktivism challenges the expectations about what activism does. One version says you’re supposed to change something or have a solution. But slacktivism (or clicktivism) is valuable for the biographical impact.

A: Studies have looked into whether eating organic food affects your self image so that you do more, or that you merely congratulate yourself.

A: The ladder of engagement says that the big step is getting on the first rung. My view of slacktivism is that it’s widened that run. Pressing the LOIC button gets people started, and I’m in favor of people starting somewhere, when it is in a considered and useful way.

Q: How about The Jester?

A: He’s an Army veteran who explicitly aligns his morals with pro-US, anti-jihadist, anti-Anonymous DDOS. He claims to be working by himself. I don’t think his actions are ethical because they’re about silencing content. [Molly tells us that she has a presentation on DDOS ethics.]

Q: Why is “fuckng hive mind mode” a community? People are donating bandwidth. But the manual mode, where people actively decide to participate in something, is much more like people being in a community. The participants in FHHM don’t necessarily view themselves as joining in a community, although the federal govt is claiming that they are.

A: I agree. My point with FHHM was that it opens up ways of accessing that community in ways that were not possible before.

Q: LOIC is hosted at github and sourceforge, and tutorials at YouTube. Any attempts to remove?

A: LOIC and tools like it are listed as “stress-testing” tools. And it can be used that way if you aim it at your own server. It’s like a head shop selling a pipe for tobacco. During the four days of the operation, Twitter did try to shut down the Anonymous twitter account.

Q: You seem to be saying that Anonymous is becoming more respectful, shifting out of the “otherized” world of 4chan. Is there quantitative data supporting this?

A: Biella Coleman has done the most research on this. That’s where I’ve gotten my data.

Q: How many people participated?

A: It’s been downloaded hundreds of thousands of times.

Q: When an org provides a press contact, a journalist can always orient around that, bounce off of it. But Anonymous doesn’t work that way. How does Anonymous’ play affect coverage?

A: The media doesn’t know how to deal with orgs like Anon and Occupy. They just speak with random people, none of who speak for the org (because no one does). The opening of the press IRC channel was great, for those who found it. It let the press engage at length. But Anon is usefully weird, and thus hard for the media.

Q: [me] So, will LOIC tear us apart? Civil disobedients accept consequences in part to raise the bar so that people don’t too easily break the law. LOIC lowers that bar. If Anon were attacking services that you like, would you be as sanguine?

LOIC isn’t much used now because it’s dangerous, and there are new tools. It’s hard to take down a site.

Q: As the tools get better?

A: Permanent arms race.

Q: Arrest of Sabu?

A: It won’t kill Anonymous.

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At SCS13, Clay Shirky says that “Why do comments suck so bad?” is one of the questions that is perpetually asked in public discussions. So, what’s the answer?

Clay points to YouTube as the “basement” of conversation, even in comments on innocuous videos, but there are sites discussing contentious issues that are quite civil and useful. And Google owns YouTube, and they have lots of money and an Internet sensibility, but still YouTube comments suck.

Explanation #1: The world is filled with trolls. But in fact, some sites with good commenting sections moderate comments, thinking about the commenters as a community, not as individuals asserting “First Amendment” rights.

Explanation #2: “Good. Big. Cheap. Pick two.” YouTube’s scale is “an attractive nuiscance.” If you have a publishing frame, then you want to let as many people in. If you have a community view, you are ok with limiting page views. E.g., Gawker uses an algorithm that features comments based on the richness of the thread. (The lower-ranked comments are still there.)

Explanation #3: “What do you want the users to do?” Publishing sites actually want people to forward the article to a million friends and then read another article. They often relegate the comments to the bottom of the page. E.g., the NYT says “Share your thoughts,” which is incredibly generic. No guidance is given. The result are responses that read like letters to the editor, without interaction or conversation. The NYT gives you actionable info for shows, but not for candidates: no links to their sites, no way to donate, etc. “The NYT is much better at helping consumers plug into markets than citizens to plug into politics.”

Explanation #4. “Institutions dodnot have the full range of either social technical solutions available to them culturally.” They can’t think of their commenters as a community instead of as a way of generating low-cost page views.

Q&A

Clay would like newspapers to have a dashboard of options they can use when constructing commenting sections, each customized to the article.

Q: [Anil Dash] Why ascribe this to ignorance instead of malice. Many of this institutions are served by making their readers look stupid.

Clay: That’s one of my a priori assumptions. I don’t think the individuals making choices are purposefully trying to keep the comments shallow and to prevent collective action. Rather, “letters to the editor” is a comfortable place for them.

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Gary Price from Infodocket is moderating a panel on what’s new in search. It’s a panel of vendors

The first speaker is from Blekko.com, which he says “is thought of as the third search engine” in the US market. It features info from authoritative sources. “You don’t want your health information to come from some blog.” When you search for “kate spade” you get authenticated Kate Spade fashion stuff. Slashtags let you facet within a topic, based on expert curation. Users can create their own slashtags. At /webgrep you can ask questions about the corpus that if upvoted the techies at Blekko will answer.

Weblib.com describes itself on its site as “Natural Language Processing Tools and Customizable Knowledge Bases for Semantic Search and Discovery Applications.” Thomas talks about OntoFind and semantic search, which is a search that produces “meaningful results even when the retrieved pages” contain none of the search terms [latent semantic search!]. He points to Google’s Freebase, which has info about 500M entities and their relationships. In a week you’ll be able to try OntoFind at ezu.com, I believe. Searching for big brother and privacy first asks you to disambiguate and then pulls together results.

ScienceScape.com is designed to help scientists follow science. It diagrams publications on a topic, and applies article-level metrics. It’s focused on the undergrad and graduate research markets. It integrates genomic knowledge plus much more. It lets you see the history of science top down, and browse e.g. by date. You can share what you’ve found.

[I couldn’t hear the Q&A well enough to blog it.]

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I’m at the Semantic Technology & Business conference in NYC. Matthew Degel, Senior Vice President and Chief Architect at Viacom Media Networks is talking about “Modeling Media and the Content Supply Chain Using Semantic Technologies.” [NOTE: Liveblogging. Getting things wrong. Mangling words. Missing points. Over- and under-emphasizing the wrong things. Not running a spellpchecker. You are warned!]

Matthew says that the problem is that we’re “drowning in data but starved for information” Tere is a “thirst for asset-centric views.” And of course, Viacom needs to “more deeply integrate how property rights attach to assets.” And everything has to be natively local, all around the world.

Viacom has to model the content supply chain in a holistic way. So, how to structure the data? To answer, they need to know what the questions are. Data always has some structure. The question is how volatile those structures are. [I missed about 5 mins m– had to duck out.]

He shows an asset tree, “relating things that are different yet the same,” with SpongeBob as his example: TV series, characters, the talent, the movie, consumer products, etc. Stations are not allowed to air a commercial with the voice actor behind Spoongey, Tom Kenney, during the showing of the SpongeBob show, so they need to intersect those datasets. Likewise, the video clip you see on your setup box’s guide is separate from, but related to, the original. For doing all this, Viacom is relying on inferences: A prime time version of a Jersey Shore episode, which has had the bad language censored out of it, is a version of the full episode, which is part of the series which has licensing contracts within various geographies, etc. From this Viacom can infer that the censored episode is shown in some geography under some licensing agreements, etc.

“We’ve tried to take a realistic approach to this.” As excited as they are about the promise, “we haven’t dived in with a huge amount of resources.” They’re solving immediate problems. They began by making diagrams of all of the apps and technologies. It was a mess. So, they extracted and encoded into a triplestore all the info in the diagram. Then they overlaid the DR data. [I don’t know what DR stands for. I’m guessing the D stands for Digital, and the R might be Resource]] Further mapping showed that some apps that they weren’t paying much attention to were actually critical to multiple systems. They did an ontology graph as a London Underground map. [By the way, Gombrich has a wonderful history and appreciation of those maps in Art and Representation, I believe.]

What’s worked? They’re focusing on where they’re going, not where they’ve been. This has let them “jettison a lot of intellectual baggage” so that they can model business processes “in a much cleaner and effective way.” Also, OWL has provided a rich modeling language for expressing their Enterprise Information Model.

What hasn’t worked?

• “The toolsets really aren’t quite there yet.” He says that based on the conversations he’s had to today, he doesn’t think anyone disagrees with him.

• Also, the modeling tools presume you already know the technology and the approach. Also, the query tools presume you have a user at a keyboard rather than as a backend of a Web service capable of handling sufficient volume. For example, he’d like “Crystal Reports for SPARQL,” as an example of a usable tool.

• Visualization tools are focused on interactive use. You pick a class and see the relationships, etc. But if you want to see a traditional ERD diagram, you can’t.

• Also, the modeling tools present a “forward-bias.” E.g., there are tools for turning schemas into ontologies, but not for turning ontologies into a reference model for schema.

Matthew makes some predictions:

• They will develop into robust tools

• Semantic tech will enable queries such as “Show me all Madonna interviews where she sings, where the footage has not been previously shown, and where we have the license to distribute it on the Web in Australia in Dec.”

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It’s the end of the workstream day of the DPLA Midwest meeting. Each of the three workstream meetings is reporting back to the general group.

Emily Gore from the Content stream: What kind of guidance should we develop for interested content providers? The group wants to have a strategic collection development plan draft by the end of December. “What is our role with regard to advocacy” for content currently under copyright? Also, the group talked about the hub pilot project. Various participants in that pilot were in the room.

SJ Klein from the Technical workstream: There was a lively discussion this afternoon, primarily about the design of the front end. How to make the frontend experience help people become contributors? They also talked about the Chatanooga hackathon Nov. 8-9. Tools for making working with metadata easier. Packaging tools that match potential contributors with a hub. Metadata purgatory for metadata that has been contributed but doesn’t meet the standards.

Maureen Sullivan and John Palfrey report on the Governance group: The next steps are to take the barebone by-laws and flesh them out. There were many discussions about whether DPLA the 501(c)(3) should be a membership organization, but the general consensus is no. (Paul Courant made the point that many institutions shy away from becoming members because that makes them liable.) Rather, it would be good to have participation from groups and people with specific areas of expertise. There was a lot of energy about expanding on the statement of principles, including adding an explicit commitment to accessibility. There was strong support for continuing to see the DPLA as a public/private enterprise. John Bracken made the point that DPLA should view itself as a network, not as a heavyweight organization.

Maureen points out that the workstreams have converged. She says that “contributor” seems to be a better word than “member.” We need to be flexible about how people will come together to do the work that’s required. And we should be thinking of ourselves as advocates, a force for change to improve the lives of people in this country and around the world.

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Andrew Keen is speaking. (I liveblogged him this spring when he talked at a Sogeti conference.) His talk’s title: “How today’s online social revolution is dividing, diminishing, and disorienting us.” [Note: Posted without rereading because I’m about to talk. I may go back and do some cleanup.]

Andrew opens with an anecdote. He grew up as a Jew in Britain. His siblings were split between becoming lawyers or doctors. But his mother asked him if he’d like to be the anti-Christ. So, now he’s grown up to become the anti-Christ of Silicon Valley.

“I’m not usually into intimacy,” but look at each other. How much do we know about each other? Not much. One of the great joys is getting to know one another. By 2017 there will 15x more data flowing over the network. Billions of intelligent devices. “The world we are going into is one in which 2o-25 years…you strangers will show up in a big city in London and you’ll know everything about each other.” You’ll know one another’s histories, interests…

“My argument is that we’re all stuck in Digital Vertigo. We’re all participants in a digital noir.” He shows a clip from Vertigo. “In the future these kinds of scenes won’t be possible. There won’t be private detectives…So this movie about the unfolding of understanding between strangers won’t happen.” What happens to policing. “Will we be guilty if we don’t carry our devices.” [SPOILERS] The blonde in this movie doesn’t exist. She’s a brunette shopgirl from Kansas. “The movie is about a deception…A classic Hitchcock narrative of falling in love with something that doesn’t exist. A good Catholic narrative…It’s a warning about falling in love with something that is too good to be true.” That’s what we’re doing with social media nd big data. We’re told big data brings us together. They tell us the Net gives us the opportunity for human beings to come together, to realize themselves as social beings. Big data allows us to become human.

This is about more than the Net. The revolution that Carlotta is talking about is one in which the Net becomes central in the way we live our lives. Fifteen years ago, Doc Searls, David W., and I would be marginal computer nerds, and now our books can be found in any book store. [Doc is in the audience also.]

He shows a clip from The Social Network: “We lived on farms. Now we’re going to live on the Internet.” It’s the platform of 21st century life. This is not a marginal or media issue. It is about the future of society. Many people this network will solve the core problems of life. We now have an ecosystem of apps in the business of eliminating loneliness. E.g., Highlight, “the darling of the recent SxSW show.” They say it’s “a fun way to learn more about people nearby.” Then he shows a clip from The Truman Show. His point: We’re all in our own Truman Shows. The destruction of privacy. No difference between public and private. We’re being authentic. We’re knowingly involving ourselves in this.

A quote: “Vertigo is the ultimate critics’ film because it is a dreamlike film about people who are not sure who they but who are busy econstructing themselves and each other to a f=kind of cinema ideal of the ideal soul mate.” Substitute social media for film. We’re losing what it means to be using. We’re destroying the complexity of our inner lives. We’re only able to live externally. [This is what happens when your conceptual two poles are public and private. It changes when we introduce the term “social.”]

Narcissism isn’t new. Digital narcissism has reached a climax. As we’re given personal broadcasting platforms, we’re increasingly deluded into thinking we’re interesting and important. Mostly it reveals our banality, our superficiality. [This is what you get when your conceptual poles are taken from broadcast media.]

It’s not just digital narcissism. “Visibility is a trap,” said Foucault. Hypervisibility is a hypertrap. Our data is central to Facebook and others becoming viable businesses. The issue is the business model. Data is oil, and it’s owned by the rich. Zuckerberg, Reed Hoffman, et al., are data barons. Read Susan Cain’s “Quiet”: introverts drive innovation. E.g., Steve Wozniak. Sharing is not good for innovation. Discourage your employees from talking with one another all the time. It makes them less thoughtful. It creates groupthink. If you want them to think for themselves, “take away their devices and put them in dark rooms.”

It’s also a trap when it comes to govt. Many govts are using the new tech to spy on their citizens. Cf. Bentham’s panopticon, which was corrupted into 1984 and industrial totalitarianism. We need to go back to the Industrial Age and JS Mill — Mill’s On Liberty is the best antidote to Bentham’s utilitarianism. [? I see more continuity than antidote.]

To build a civilized golden age: 1. There is a role for govt. The market needs regulation. 2. “I’m happy with the EU is working on this…and came out against FB facial recognition software. … We have a right to forget.” “It’s the most unhuman of things to remember everything.” “We shouldn’t idolize the never-forgetting nature of Big Data.” “To forget and forgive is the core essence of being human.” 3. We need better business models. We don’t want data to be the new oil. I want businesses that charge. “The free economy has been a catastrophe.”

He shows the end of The Truman Show. [SPOILER] As Truman enters reality, it’s a metaphor for our hope. We can only protect our humanness by retreating into dark, quiet places.

He finishes with a Vermeer that shows us a woman about which we know nothing. In our Age of Facebook, we need to build a world in which the woman in blue can read that letter, not reveal herself, not reveal her mystery…”

Q: You’re surprising optimistic today. In the movie Vertigo, there’s an inevitability. How about the inevitability of this social movement? Are you tilting at windmills.

Idealists tilt at windmills. People are coming to around to understanding that the world we’re collectively creating is not quite right. It’s making people uneasy. More and more books, articles, etc., that FB is deeply exploitative. We’re all like Jimmy Stewart in Vertigo. The majority of people in the world don’t want to give away their data. As more of the traditional world comes onto the Net, there will be more resistant to collapsing the private and the public. Our current path is not inevitable. Tech is religion. Tech is not autonomous, not a first mover. We created Big Data and need to reestablish our domination over it. I’m cautiously optimistic. But it could go wrong, especially in authoritarian regimes. In Silicon Valley people say privacy is dead, get over it. But privacy is essential. Once we live this public ideal, then who are we.

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I’m at Sogeti‘s annual executive conference, which brings together about 80 CEOs. I’m here with Doc Searls, Andrew Keen, and others. I’ve spoken at other Sogeti events, and I am impressed with their commitment to providing contrary points of view — including views at odds with their own corporate interests. (My one complaint: They expect all attendees to have an iPad or iPhone so that they can participate in on the realtime survey. Bad symbolism.) (Disclosure: They’re paying me to speak. They are not paying me to say something nice about them.)

Menno van Doorn begins by talking about the quantified self movement, claiming that they sometimes refer to themselves as “datasexuals” :) All part of Big Data, he says. To give us an idea of bigness, he relates the Legend of Sessa: “Give me grain, doubling the amount for each square on a chessboard.” Exponential growth meant that by the time you hit the second half of the chessboard, you’re in impossible numbers. Experts say that’s where we were in 2006 when it comes to data. But “there’s no such thing as too much data.” “Big Data is powering the next industrial revolution. Data is the new oil.”

Big Data is about (1) lots of data, (2) at high velocity, (3) using in a variety of ways. (“volume, velocity, variety.”) Michael Chui says that there’s billions in revenues to gain, including from efficiencies. But, Chui says, there are no best practices. The value comes from “human exhaust.” I.e., your digital footprint, what you leave behind in your movement through the Net. Menno thinks of this as “your recorded future.”

Three examples:

1. Menno points to Target, a company that can predict life-changing events among its customers. E.g., based on purchases of 25 products, they can predict which customers are pregnant and roughly when they are due. But, this led to Target sending promotional materials for pregnancy to young girls whose parents learned this way that their daughters were pregnant.

2. In SF, they send out police cars to neighborhoods based on 14-day predictions of where crime will occur, based on data about prior crime patterns.

3. Schufa, a German credit agency, announced they’d use social media to assess your credit worthiness. Immediately a German Minister said, “Schufa cannot become the Big Brother of the beusiness world.”

Two forces are in contention and will determine how much Big Data changes us. Today, the conference will look at the dawn of the age of big data, and then how disruptive it will be for society (the session Keen and I are in). Day 2: Bridging the gap to the new paradigm, Big Data’s fascinating future, and Decision Time: Taming Big Brother.

Carlota Perez, Prof. of Tech and Socio-Economic Development, from Venezuela speaks now.. She is a “neo-Schumpeterian.” She says her role in the conference is “locate the current crisis.” What is the real effect on innovation, and why are we only midways along in feeling the impact?

There have been 5 tech revolutions in the past 240 yeares: 1. 1771 Industrial rev. 1829. Age of steam, coal and railways. 3. 1875 Steel and heavy engineering (the first globalization). 4. Age of he automobile, oril, petrochem and mass production 5. 1971 Age of info tech and telecom. We’re only halfway through that last one. The next revolution queued up: age of biotech, bioelectronics, nanotech, and new materials. [I’m surprised she doesn’t count telegrapgh + radio + telephone, etc., as a comms rev. And I’d separate the Net as its own rev. But that’s me.]

Lifecycle of a tech rev: gestation, induction, deployment, exhaustion. The “big bang” tends to happen when the prior rev is reaching exhaustion. The structure of revs: new cheap inputs, new products, new processes. A new infrastructure arise. And a constellation of new dynamic industries that grow the world economy.

Why call these “revolutions”, she asks? Because they transform the whole economy. They bring new organizational principles and new best practice models. I.e. , a new “techno-economic paradigm.” E.g., we’ve gone from mass production to flexible production. Closed pyramids to open networks. Stable routines to continuous improvement. “Information technology finds change natural.” From human resources to human capital (from raw materials to value). Suppliers and clients to value network partners. Fixed plans to flexible strategies. Three-tier markets (big,medium,small) to hyper-segmented markets. Internationalization to globalization. Information as costly burden to info as asset. Together, these constitute a radical change in managerial common sense.

The diffusion process is broken in two: Bubble, followed by a crash, and then the Golden Age. During the bubble, financial capital forces diffusion. There is income and demand polarization. Then the crash. Then there is an institutional recomposition, leading to a golden age in which everyone benefits. Production capital takes over from financial capital (driven by the govt), and there is better distribution of income and demand.

She looks at the 5 revs, and finds the same historic pattern that she just sketched.

wo major differences between installation and deployment: 1. Bubbles vs. patient (= long-term) capital. 2. Concentrated innovation to modernize industries vs. innovation in all industries that use the new technologies. “Understanding this sequence is essential for strategic thinking.”

The structure of innovation in deployment: pa new coherent fabric of the economy emerges, leading to a golden age. Also, oligopolies emerge which means there’s less unhelpful competition. (?)

Example of prior rev: home electrical applicances: In the installation period, we had a bunch of electric utilities going into homes in the 1910s and 1930s. During the revision, we get a few more. But then in the 1950-70s. we get a surge of new applicances, including tape recorder, microwave, even the electric toothbrush. It’s enabled by universal electricity and driven by suburbinization. It’s the same pattern if you look at textile fibers, from rayon and acetate during instlation, to a huge number during deployment. E.g., structural and packaging plastics: installation brought bakelite, polystyrene and polyethylene, and then a flood of innovation during deployment. “The various systems of the ICT revolution will follow a similar sequence.” [Unless it follows the Tim Wu pattern of consolidation — e.g., everyone being required to use an iPad at a conference] During installation period, ICT was in constant supply push mode. Now must respond to demand pull. “The paradigm and its potential are now understood by all. Demand (in vol and nature) becomes the driving force.

This shifts the role of the CIO. To modernize a mature company, during installation you brought in an expert in modernization, articulating the hw and sw being pushed by the suppliers. During the deployment phase, a modern company that is innovating for strategic expansion, the CIO is an expert in strategy, specifying needs and working with suppliers. “The CIO is no longer staff. S/he must be directly involved in strategy.”

There are 3 main forces for innovation in the next 2-3 decades, as is true for all the revs. 1. Deepening and widening of the ICT tech rev, responding to user needs. 2. The users of ICT across all industries and activities. 3. The gestation of the next rev (probably bioteech, nanotech, and new materials).

Big Data is likely have a big role in each of those directions.

Q: Why are we only 50% of the way through?

A: Because the change after the recession is like opening a dam. Once you get to the point where you can have a comfortable innovation prospective, imagine the market possibilities.

Q: What can go wrong?

A: Governments. Unfettered free markets are indispensable for the installation process. Lightly guided markets are needed in the golden age. Free markets work when you need to force everyone to change. But now no longer: The state has to come in . But govts are drunk with free markets. Now finance is incompetent. “They don’t dare invest in real things.” Ideology is so strong and the understanding of history is so shallow that we’re not doing the right thing.”

Christopher Ahlberg speaks now. He’s the founder of Recorded Future. His topic: “Turning the Web into Predictive Signals.”

We see events like Arab Spring and wonder if we could have predicted them. Three things are going on: 1. Moving from smaller to larger datasets. 2. From structured to unstructured data (from numbers to text). 3. From corporate data to Internet/Web.

There’s a “seismic shift in intelligence” “emporal indexing of the Web enables Web intelligence.” The Web is not organized for finding date; it’s about finding documents.” Can we create structure for the Web we can use for analysis? A lot of work has been done on this. Why is this possible now? Fast math, large, fast storage, web harvesting, and linguistic analysis progress.

His company looks for signals in human language. E.g., temporal signals. That can turn up competitive info. But human language is tough to deal with. But also when something happens — e.g., Haitian earthquake — there are patterns in when people show up: helpers, doctors, military, do-gooder actors, etc. There tends to be a flood of notifications immediately afterwards. The Recorded Data platform does the linguistic analysis.

He gives an example: What’s going to happen to Merck over the next 90 days. Some is predictable: There will be a quarterly financial conference all. A key drug is up for approval. Can we look into the public conversations about these events, and might this guide our stock purchases? And beyond Merck, we could look at everything from cyber attacks to sales opportunities.

Some examples. 1. Monitoring unrest. Last week there were protests against Foxconn in China. Analysis of Chinese media shows that most of those protests were inland, while corporate expansion is coming in coastal areas. Or look at protests against pharmaceuticals for animal testing.

Example 2: Analyzing cyber threats. Hackers often try out an approach on a small scale and then go larger. This can give us warning.

Example 3: Competitive intelligence. When is there a free space — announcement-free — when you can get some attention. Example 4: Lead generation. E.g., look for changes in management. (New marketing person might need a new PR agency.) Exasmple 5: Trading patterns. E.g., if there’s bad news but insiders are buying.

Conclusion: As we move from small to large datasets, structured to unstructured, and from inside to outside the company, we go from surprise to foresight.

Q: What is the question you cannot answer?

A: The situations that have low frequency. It’s important that there be an opportunity for follow-up questions.

Q: What if you don’t know what the right question is?

A: When it’s unknown unknowns, you can’t ask the right question. But the great thing about visualizaton is that it helps people ask questions.

Q: How to distinguish fact from opinion on Twitter, etc.?

A: Or NYT vs. Financial Post. There isn’t a simple answer. We’re working toward being able to judge sources based on known outcomes.

Q: Do your predictions get more accurate the more data you have?

A: Generally yes, but it’s not always that simple.

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A series of 5-min lightning talks.

Christie Moffatt of the National Library of Medicine talks about a project collecting blogs talking about health. It began in 2011. The aim is to understand Web archiving processes and how this could be expanded. Three examples: Wheelchair Kamikaze. Butter Compartment. Doctor David’s Blog. They were able to capture them pretty well, but with links to outside, outside of scope content, and content protected by passwords, there’s a question about what it means to “capture” a blog. The project has shown the importance of test crawls, and attending to the scope, crawling frequency and duration. The big question is which blogs they capture. Doctors who cook? Surgeons who quilt? Other issues: Permissions. Monitoring when the blogs end, change focus, or move to a new url. E.g., a doctor retired and his blog changed focus to about fishing.

Terry Plum from Simmons GSLIS talks about a digital curriculum lab. It was set up to pull in students and faculty around a few different areas. They maintain a collection of open source applications for archives, museums, and digital libraries. There are a variety of teaching aids. The DCL is built into a Cultural Heritage Informatics track at Simmons.

Daniel Krech of Library of Congress works at the Repository Development Center. The RDC works with people managing collections. The RDC works on human-machine interfaces. One project involves “sets” (collections). “We’ve come up with some new and interesting ways to think about data.” They use knot, set, and hyper theory, but they also sometimes use a physical instantiation of a set — it looks like knotted yarn — to help understand some very abstract ideas.

Kelsey [Keley?]Shepherd of Amherst represents the Five College Digital Task Force. (She begins by denying that the Scooby Gang was based on the five colleges.) They don’t share a digital library but want to collaborate on digital preservation. They are creating shared guidelines for preservation-ready digital objects. They are exploring models for funding and organizational structure. And they are collaborating on implementing a trusted digital perservation repository. But each develops its own digital preservation policy.

Jefferson Baily talks about Personal Digital Archiving at the Library of Congress. He talks about the source diary for The Widwife’s Tale. That diary sat on a shelf for 200 years before being discovered as an invaluable window on the past. Often these archives are the responsibility of the record creators. The LoC therefore wants to support community archives, enthusiasts, and citizen archivists. They are out and about, promoting this. See digitalpreservation.gov

Carol Minton Morris with DuraSpace and the NDSA (National Digital Stewardship Alliance) talks about funding archiving through “hip pocket resources.” They’re looking into Kickstarter.com. Technology and publishing projects at Kickstarter have only raised $9M out of the $100M raised there; most of it goes to the arts. She points to some other microfinance sites, including IndieGoGo and DonorsChoose.org. She encourages the audience to look into microfinancing.

Kristopher Nelson from LoC Office of Strategic Initiatives talks about the National Digitial Stewardship Residency, which aims at building a community of professionals who will advance digital archiving. It wants to bridge classroom education and professional experience, and some real world experience. It will start in June 2013 with 10 residents participating in the 9 month program.

Moryma Aydelott, program specialist at LoC talks about Tackling Tangible Metadata. The LoC’s digital data is on lots of media: 300T on everything from DVDs to DAT tapes and Zip disks. Her group provides a generic workflow for dealing with this stuff — any division, any medium. They have a wheeling cart for getting at this data. They make the data available “as is.” It can be hard to figure out what type of file it is, and what application is needed to read it. Right now, it’s about getting it on the server. They’ve done about 6.5T of material, 700-800 titles, so far. But the big step forward is in training and in documenting processes.

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