Atom Feed
May 7, 2009
My interview with Stephen Wolfram about WolframAlpha is now available. Some other me-based resources:
The unedited version weighs in at a full 55 minutes. The edited version will spare you some of my throat-clearing, and some dumb questions.
A post about what I think the significance of WolframAlpha will be.
Live blog of Wolfram’s presentation at Harvard.
Wolfram’s presentation at Harvard.
May 4, 2009
The Independent calls WolframAlpha “An invention that could change the Internet forever.” It concludes: “Wolfram Alpha has the potential to become one of the biggest names on the planet.”
Nova Spivak, a smart Semantic Web guy, says it could be as important as Google.
Ton Zijlstra, on the other hand, who knows a thing or two about knowledge and knowledge management, feels like it’s been overhyped. After seeing the video of Wolfram talking at Harvard, Ton writes:
No crawling? Centralized database, adding data from partners? Manual updating? Adding is tricky? Manually adding metadata (curating)? For all its coolness on the front of WolframAlpha, on the back end this sounds like it’s the mechanical turk of the semantic web.
(“The mechanical turk of the semantic web.” Great phrase. And while I’m in parentheses, ReadWriteWeb has useful screenshots of WolframAlpha, and here’s my unedited 55-minute interview with Wolfram.)
I am somewhere in between, definitely over in the Enthusiastic half of the field. I think WolframAlpha [WA] will become a standard part of the Internet’s tool set, but is not transformative.
WA works because it’s curated. Real human beings decide what topics to include (geography but not 6 Degrees of Courtney Love), which data to ingest, what metadata is worth capturing, how that metadata is interrelated (= an ontology), which correlations to present to the user when she queries it (daily tonnage of fish captured by the French compared to daily production of garbage in NYC), and how that information should be presented. Wolfram insists that an expert be present in each data stream to ensure the quality of the data. Given all that human intervention, WA then performs its algorithmic computations … which are themselves curated. WA is as curated as an almanac.
Curation is a source of its strength. It increases the reliability of the information, it enables the computations, and it lets the results pages present interesting and relevant information far beyond the simple factual answer to the question. The richness of those pages will be big factor in the site’s success.
Curation is also WA’s limitation. If it stays purely curated, without areas in which the Big Anyone can contribute, it won’t be able to grow at Internet speeds. Someone with a good idea — provide info on meds and interactions, or add recipes so ingredients can be mashed up with nutritional and ecological info — will have to suggest it to WolframAlpha, Inc. and hope they take it up. (You could to this sorta kinda through the API, but not get the scaling effects of actually adding data to the system.) And WA will suffer from the perspectival problems inevitable in all curated systems: WA reflects Stephen Wolfram’s interests and perspective. It covers what he thinks is interesting. It covers it from his point of view. It will have to make decisions on topics for which there are no good answers: Is Pluto a planet? Does Scientology go on the list of religions? Does the page on rabbits include nutritional information about rabbit meat? (That, by the way, was Wolfram’s example in my interview of him. If you look at the site from Europe, a “rabbit” query does include the nutritional info, but not if you log in from a US IP address.) But WA doesn’t have to scale up to Internet Supersize to be supersized useful.
So, given those strengths and limitations, how important is WA?
Once people figure out what types of questions it’s good at, I think it will become a standard part of our tools, and for some areas of inquiry, it may be indispensable. I don’t know those areas well enough to give an example that will hold up, but I can imagine WA becoming the first place geneticists go when they have a question about a gene sequence or chemists who want to know about a molecule. I think it is likely to be so useful within particular fields that it becomes the standard place to look first…Like IMDB.com for movies, except for broad, multiple fields, with the ability to cross-compute.
But more broadly, is WA the next Google? Does it transform the Internet?
I don’t think so. Its computational abilities mean it does something not currently done (or not done well enough for a crowd of users), and the aesthetics of its responses make it quite accessible. But how many computational questions do you have a day? If you want to know how many tons of fish France catches, WA will work as an almanac. But that’s not transformational. If you want to know how many tons divided by the average weight of a French person, WA is for you. But the computational uses that are distinctive of WA and for which WA will frequently be an astounding tool are not frequent enough for WA to be transformational on the order of a Google or Wikipedia.
There are at least two other ways it could be transformational, however.
First, its biggest effect may be on metadata. If WA takes off, as I suspect it will, people and organizations will want to get their data into it. But to contribute their data, they will have to put it into WA’s metadata schema. Those schema then become a standard way we organize data. WA could be the killer app of the Semantic Web … the app that gives people both a motive for putting their data into ontologies and a standardized set of ontologies that makes it easy to do so.
Second, a robust computational engine with access to a very wide array of data is a new idea on the Internet. (Ok, nothing is new. But WA is going to bring this idea to mainstream awareness.) That transforms our expectations, just as Wikipedia is important not just because it’s a great encyclopedia but because it proved the power of collaborative crowds. But, WA’s lesson — there’s more that can be computed than we ever imagined — isn’t as counter-intuitive as Wikipedia’s, so it is not as apple-cart-upsetting, so it’s not as transformational. Our cultural reaction to Wikipedia is to be amazed by what we’ve done. With WA, we are likely to be amazed by what Wolfram has done.
That is the final reason why I think WA is not likely to be as big a deal as Google or Wikipedia, and I say this while being enthusiastic — wowed, even — about WA. WA’s big benefit is that it answers questions authoritatively. WA nails facts down. (Please take the discussion about facts in a postmodern age into the comments section. Thank you.) It thus ends conversation. Google and Wikipedia aim at continuing and even provoking conversation. They are rich with links and pointers. Even as Wikipedia provides a narrative that it hopes is reliable, it takes every opportunity to get you to go to a new page. WA does have links — including links to Wikipedia — but most are hidden one click below the surface. So, the distinction I’m drawing is far from absolute. Nevertheless, it seems right to me: WA is designed to get you out of a state of doubt by showing you a simple, accurate, reliable, true answer to your question. That’s an important service, but answers can be dead-ends on the Web: you get your answer and get off. WA as question-answerer bookends WA’s curated creation process: A relatively (not totally) closed process that has a great deal of value, but keeps it from the participatory model that generally has had the biggest effects on the Net.
Providing solid, reliable answers to difficult questions is hugely valuable. WolframAlpha’s approach is ambitious and brilliant. WolframAlpha is a genius. But that’s not enough to fundamentally alter the Net.
Nevertheless, I am wowed.
May 2, 2009
C-SPAN’s monumentally, overwhelmingly, epically popular series, BookTV, this week is broadcasting the Berkman session with Andrew Lih on his The Wikipedia Revolution that I moderated. Andrew speaks for a few minutes, then I interview him, then the audience asks questions. I thought Andrew’s presentation was terrific, and the audience asked good questions. It’s on Sunday, May 3, at 12:30 AM, Sunday, May 24, at 4:30 PM and — for those for whom twice isn’t enough — at Monday, May 25, at 4:30 AM.
Remember how the media leapt on the study that showed that being on Facebook lowered your grades in school? The study was, shall we say, flawed. But it was a media-seeking rocket. Now, 2.5 weeks later, Josh Pasek, eian more, and Eszter Hargittai have published “Facebook and academic performance: Reconciling a media sensation with data” at First Monday, a peer-reviewed site.
Here’s the abstract:
A recent draft manuscript suggested that Facebook use might be related to lower academic achievement in college and graduate school (Karpinski, 2009). The report quickly became a media sensation and was picked up by hundreds of news outlets in a matter of days. However, the results were based on correlational data in a draft manuscript that had not been published, or even considered for publication. This paper attempts to replicate the results reported in the press release using three data sets: one with a large sample of undergraduate students from the University of Illinois at Chicago, another with a nationally representative cross sectional sample of American 14– to 22–year–olds, as well as a longitudinal panel of American youth aged 14–23. In none of the samples do we find a robust negative relationship between Facebook use and grades. Indeed, if anything, Facebook use is more common among individuals with higher grades. We also examined how changes in academic performance in the nationally representative sample related to Facebook use and found that Facebook users were no different from non–users.v
And what are the chances that the media are going to trumpet these results that are based on actual data and careful analysis?
April 28, 2009
Stephen Wolfram is giving at talk at Harvard/Berkman about his WolframAlpha site, which will launch in May. Aim: “Find a way to make computable the systematic knowledge we’ve accumulated.” The two big projects he’s worked on have made this possible. Mathematica (he’s worked on it for 23 yrs) makes it possible to do complex math and symbolic language manipulation. A New Kind of Science (NKS) has made it possible that it’s possible to understand much about the world computationally, often with very simple rules. So, WA uses NKS principles and the Mathematica engine. He says he’s in this project for the long term.
|
NOTE: Live-blogging.Posted without re-reading 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. |
You type in a question and you get back in answers. You can type in math and get back plots, etc. Type in “gdp france” and get back the answer, a graph of the history of the shows histogram of GDP.
“GDP of france / italy”: The GDP of France divided by the GDP of Italy
“internet users in europe” shows histogram, list of highest and lowers, etc.
“Weather in Lexington, MA” “Weather lexington,ma 11/17/92” “Weather lexington, MA moscow” shows comparison of weather and location.
“5 miles/sec” returns useful conversions and comparisons.
“$17/hr” converts to per week, per month, etc., plus conversion to other currencies.
“4000 words” gives a list of typical typing speeds, the length in characters, etc.
“333 gm gold” gives the mass, the commodity price, the heat capacity, etc.
“H2S04” gives an illustration of the molecule, as well as the expected info about mass, etc.
“Caffeine mol wt/ water” gives a result of moelcular weights divided.
“decane 2 atm 50 C” shows what decane is like at two atmospheres and at 50 C, e.g., phase, density, boiling point, etc.
“LDL 180”: Where your cholesterol level is against the rest of the population.
“life expctancy male age 40 italy”: distribution of survival curve, history of that life expectancy over time. Add “1933” and adds specificity.
“5’8″ 160 lbs”: Where in the distribution of body mass index
“ATTGTATACTAA”: Where that sequence matches the human genome
“MSFT”: Real time Microsoft quote and other financial performance info. “MSFT sun” assumes that “sun” refers to stock info about Sun Microsystems.
“ARM 20 yr mortgage”: payment of monthly tables, etc. Let’s you input the loan amount.
“D# minor”: Musical notation, plays the D# minor scale
“red + yellow”: Color swatch, html notation
“www.apple.com”: Info about Apple, history of page views
“lawyers”: Number employed, average wage
“France fish production”: How many metric tons produced, pounds per second, which is 1/5 the rate trash is produced in NYC
“france fish production vs. poland”: charts and diagrams
“2 c orange juice”: nutritional info
“2 c orange juice + 1 slice cheddar cheese”: nutritional label
“a__a__n”: English words that match
“alan turing kurt godel”: Table of info about them
“weather princeton, day when kurt godel died”: the answer
“uncle’s uncle’s grandson’s grandson”: family tree, probabiilty of those two sharing genetic material
“5th largest country in europe”
“gdp vs. railway length in europe”:
“hurricane andrew”: Data, map
“andrew”: Popularity of the name, diagrammed.
“president of brazil in 1922”
“tide NYC 11/5/2015”
“ten flips 4 heads”: probability
“3,7,15,31,63…”: Figures out and plots next in the sequence and possible generating function
“4,1 knot”: diagram of knot
“next total solar eclipse chicago”: Next one visible in Chicago
“ISS”: International Space Station info and map
It lets you select alternatives in case of ambiguities.
“We’re trying to compute things.” We have tools that let us find things. But when you have a particular question, it’s unlikely that you’ll find that specific answer written down. WA therefore tries to compute answers. “The objective is to reach expert level knowledge across a very wide range of domains.”
Four big pieces to WA:
1. Data curation. WA has trillions of people of curated data. It gets it from free data or licensed data. Partially human partially automated system cleans it up and tries to correlate it. “A lot can be done automatically…At some point, you need a human domain expert in the middle of it.” There are people inside the company and a network of others who do the curation.
2. The algorithms. Take equations, etc., from all over. “There are finite numbers of methods that have been discovered in the history of science.” There are 5-6 millions lines of Mathematica code at work.
3. Linguistic analysis to understand the inputs. “There’s no manual, no documentation. You get to interact it with just how you think about things.” They’re doing the opposite of natural language processing which usually tries to understand millions of pages. WA’s problem is mapping a relatively small set of short human inputs to what the system knows about. NKS helps with this. It turns out that ambiguity is not nearly as big a problem as we thought.
4. Automated presentation. What do yo show people so they can cognitively grasp it? “Algorithmic presentation technology … tries to pick out what is important.” Mathematica has worked on “computational aesthetics” for years.
He says that have at least a reasonable start on about 90% of the shelves in a typical reference library.
Q: (andy orem) What do you do about the inconsistencies of data? We don’t know how inconsistent it was and what algorithms you used.
A: We give source info. “We’re trying to create an authoritative source for data.” We know about ranges of values; we’ll make that information available. “But by the time you have a lot of footnotes on a number, there’s not a lot you can do with that number.” “We do try to give footnotes.”
Q: How do you keep current?
A: Lots of people want to make their data available. We hope to make a streamlined, formalized way for people to contribute the data. We want to curate it so we can stand by it.
Q: [me] Openness? Of API, of metadata, of contributions of interesting comparisons, etc.
A: We’ll do a variety of levels of API. First: presentation level: put output on their pages. Second, XML-level so people can mash it up. Third level: individual results from the databases and from the computations. [He shows a first draft of the api] You can get as the symbolic expressions that Mathematica is based on. We hope to have a personalizable version. Metadata: When we open up our data repository mechanisms so people can contribute, some of our ontology will be exposed.
How about in areas where people disagree? If a new universe model comes out from Stanford, does someone at WolframAlpha have to say yes and put it in?
A: Yes
Q: How many people?
A: It’s been 150 for a long time. Now it’s 250. It’s probably going to be a thousand people.
Q: Who is this for?
A: It’s for expert knowledge for anyone who needs it.
Q: Business model?
A: The site will be free. Corporate sponsors will put ads on the side. We’re trying to figure out how to ingest vendor info when it’s relevant, and how to present it on the site. There will also be a professional version for people who are doing a lot of computation, want to put in their own data…
Q: Can you define the medical and population databases to get the total mass of people in England.
A: We could integrate those databases, but we don’t have that now. We’re working on “splat pages” you get when it doesn’t work. It should tell you what it does know.
Q: What happens when there is no answer, e.g., 55th largest state in the US?
A: It says it doesn’t know.
Q: [eszter] For some data, there are agreed-upon sources. For some there aren’t. How do you choose sources?
A: That’s a key problem in doing data curation. “How do we do it? We try to do the best job we can.” Use experts. Assess. Compare. [This is a bigger issue than Wolfram apparently thinks where data models are political. E.g., Eszter Hargittai, who is sitting next to me, points out “How many Internet users are there?” is a highly controversial question.] We give info about what our sources are.
Q: Technologically, where do you want to focus in the future?
A: All 4 areas need to be pushed forward.
Q: How does this compare to the Semantic Web?
A: Had the Web already had been semantically tagged, this product would have been far far easier, although keep in mind that much of the data in WA comes from private databases. We have a sophisticated ontology. We didn’t create the ontology top-down. It’s mostly bottom-up. We have domains. We have ontologies for them. We merge them together. “I hope as we expose some of our data repository methods, it will make it easier to do some Semantic Web kind of things. People will be able to line data up.”
Q: When can we look at the formal specifications of these ontologies? When can we inject our own?
A: It’s all represented in clean Mathematica code. Knitting new knowledge into the system is tricky because our UI is natural language, which is messy. E.g., “There’s a chap who goes by the name Fifty Cent.” You have to be careful.
Q: What reference source tells you if Palestine exists…?
A: In cases like this, we say “Assuming Case A or B.” There are holes in the data. I’m hoping people will be motivated to fill them in. Then there’s the question of the extent to which we can build expert communities. We don’t know the best way to do this. Lots of interesting ideas.
How about pop culture?
A: Pop culture info is much shallower computationally. (“Britney Spears” just gets her name, birthdate, and birthplace. No music, no photos, nothing about her genre, etc.) (“Meaning of life” does answer “42”)
Q: Compare with CYC? (A common sense reasoning system)
A: CYC deals with human reasoning. That’s not the best method for figuring out physics, etc. “We can do the non-human parts of reasoning really well.”
Q: [couldn’t hear the question]
A: The best way to debug it is not necessarily to inspect the code but to inspect the results. People reading code is less efficient than automated systems.
Q: Will it be integrated into Mathematica?
A: A future version will let you type WA data into Mathematica.
Q: How much work do you have to do on the NLP sound? Your searches used a special lexicon…
A: We don’t know. We have a daily splat call to see what types of queries have failed. We’re pretty good at removing linguistic fluff. People drop the fluff pretty quickly after they’ve been using WA for a while.
Q: (free software foundation) How does this change the landscape for open access? There’s info in commercial journals…
A: When there’s a proprietary database, the challenge is making the right deals. People will not be able to take out of our system all the data that we put into it. We have yet to learn all of the issues that will come up.
Q: Privacy?
A: We’re dealing with public data. We could do people search, but, personally, I don’t want to.
Q: What would you think of a more Wikipedia-like model? Do you worry about a competitor making a wiki data that is completely open and grows faster?
A: That’d be great. Making WA is hard. It’s not just a matter of shoveling data in. Wikipedia is fantastic and I use it all the time, but it’s gone in particular directions. When you’re looking for systematic data there, even if people put in systematic data — e.g., 300 pages about chemicals — over the course of time, the data gets dirty. You can’t compute from it.
Q: How about if Google starts presenting your results in response to queries?
A: We’re looking for synergies But we’re generating these on the fly; it won’t get indexed.
Q: I wonder how universities will find a place for this.
A: Very interesting question. Generating hard data is hard and useful, although universities often prefer higher levels of synthesis and opinion. [Loose paraphrase!] Leibniz had this nailed: Take any human argument and find a way to mechanically compute it.
April 27, 2009
Here’s a list of free college courses available online, much of it open courseware. It’s a loooong list, I’m happy to say. Here’s a related post.
April 22, 2009
Doug Kaye keeps on polishing SpokenWord.org, a free site that collects spoken word podcasts (well, it only collects pointers to them) and lets you find, rate, discuss, and hear them. You can also add ones links to ones you like to the collection (i.e., share them). SpokenWord is getting quite useful and usable. Give it a try. (Disclosure: I’m on its board of directors; it’s a non-profit.)
April 17, 2009
|
NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Over-emphasizing small points. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are hereby warned. |
John Horrigan of Pew Internet and American Life, gives a “non-Koolaid” presentation. He says that about 12% of Internet users have a blog. The percentage of people doing some form of content sharing is not increasing much at all. The demographics says that 18-24 do the most sharing, and then it goes down in pretty much a straight line. The change over time is not distributed evenly across age groups. Younger adults are turning away from the 6 core UGC behaviors, the 24-35s are increasing. The rest: not much change.
But people are increasingly going to social networkingIf UGC is migrating to rules-based environments, is it a good bargain? On the one hand, good governance can build sustainable mechanisms. OTOH, bad governance is a risk, so you want an open Internet.
Q: A decrease in activity among younger folk? Because they were so heavily involved initially?
John: They’re going to social networking sites instead of maintaining their own sites. But UGC is still an important activity to them.
Q: The changing behaviors as people age and how that will effect UGC?
John: Impossible to answer because we don’t know how the tech will change.
Mainak Mazumdar of The Nieslen Company begins by looking at blogging topics. It’s quite diverse he says. Next: size. Wikipedia has many more topics than Britannica. Also, social networking is very big: Member communities are #4 on most visited lists, after search, portals, and software manufacturers. #5 is email. Social media is big everywhere. (Biggest: 80% of Brazil. 67% in US.) The US is showing comparatively slower growth in “active reach of member communities.” Time spent in CGM has been increasing. So is the time spent on social networking. 35-49 years are the fastest growing audience for social networking sites. Teen consumption of SNS is going down, because they’re going more and more mobile. Mobile will be huge. TV will be big. People are watching more TV. Big media companies are doing well. “Becoming a mother is a dramatic inflectin point and drives women to the Web in search of advice and a desire to connect with others in her shoes” (from the slide).
Is the Net a game-changer for research companies? He compares it to scanner data in the 90s and online surveys in 1990s. In 2000s, perhaps [perhaps??] social networking will once again change the game. Reasons to think the Net is a game-changer overall [i.e., exceptionalism] : Pervasive, sticky, generational.
Q: Is TV watching growing on all screens or just on the living room screen?
Mainak: Time spent watching TV content on a TV.
Q: Maybe SNS have surpassed email because email was used to listserves to serve the social function.
Mainak: We’re talking about how long you spend in Outlook + Web mail. We install monitors that report on how long you spend in each application.
Russ Neuman: Be careful of projecting out from the current tech. It can be disrupted easily.
Q: Older people are entering SNSs. I call them “parents.” To what extent will that change what started out as a youth movement? Is the move to mobile a move out of the SNS as they become mom and dad’s spots? [Oprah is on twitter.]
A: Yes. Some younger teens are going straight to mobile and circumventing the Internet.
Eszter Hargittai talks about the role of skill in Internet use. Yes, young people use digital media and spend a lot of time online, but it’s true that they engage in lots of online activities or that they’re particularly savvy about the Net and Web tools. So, the idea of “digital natives” is often misguided.
She’s particularly interested in the skills people have and need. Her methodology: Paper and pencil surveys to avoid biasing towards those comfortable with using Web tools. 1,060 first year students at U of Illinois. Most of the data comes from 2007, although she has some pre-pub data from 2009. The question is: What explains variation in skill? Gender, education and income predict skill. “The Web offers lots of opportunities but those who can take advantage of them are those who are already privileged.”
This has an effect on how we intervene to equalize matters. You can’t change socio-economic status. And it turns out that motivation doesn’t seem to make much of an effect. You can only be motivated to do something that you already know is a possibility. She shows new data, not ready for blogging, that show that very small percentages of users have actually created content, voted on reviews, edited Wikipedia pages, etc. The number of teenagers who have heard of Twitter is quite low. [Sorry for the lack of numbers. I’m not sure I’m supposed to be reporting even these trends.]
Mainstream media remain strong. Eszter points to the media story about Facebook users having lower grades. Eszter looked at the study and finds it to be of poor quality. Yet it got huge mainstream play. Eszter tweeted about it. She blogged about it. The tweet led to a co-authored paper. Even so, the mainstream probably won’t care, and most of the tweets are still simply retweeting the bad data. The Net is a huge opportunity, but it’s not evenly distributed.
Q: A study found that people online are lonely. It was picked up by the media. The researcher revised to say that it’s the other way around. It wasn’t picked up. The media pick up on the dystopic.
Q: Your data reflects my experience with my students. They don’t blog, they don’t tweet. There’s a class component to this.
Eszter: We measure socio-economic status. Why does it correlate? We’re exploring this. We now ask about parental support of technology use, rules at home about tech use, etc. So far we’re finding (tentatively!) that lower-educated parents tend to have more rules for their kids.
Q: What happens when there’s universal wireline connection?
Eszter: As the tech changes, the skill sets change. The privileged stay ahead, according to my 8 years of studies.
Q: What skills should we be teaching?
A: Complicated. Crucial issue: The evaluation of the credibility of sources. There’s an extreme amount of trust in search engines. That’s one place we need to do more work. And librarians are highly relevant here.
Q: How do people use the Net to learn informally, e.g., WebMD?
Eszter: There are lots of ways and types to do this. But, first you need to know what’s on the Web. You need good search skills, good credibility-evaluation skills.
Cliff Lampe talks about how Mich State U students use Facebook. He presents a study just completed yesterday, so the data isn’t yet perfect. 97% of his sample are FB users (although Cliff expresses some discomfort with this number). Mean average of 441 friends; median = 381. Ninety percent of these they consider to be “actual” friends. 73% only accept friend requests from people they know in real life. Most spend just a little time (under 30mins) at FB per day. About half lets their friends (but not everyone in their network) to see everything in their profile. Almost everyone puts a photo of themselves up. Vast majority have a photo album. About a third think their parents are looking at their page. Overall they think they’re posting for their college and high school friends.
He talks about Everything2.com, a user-generated encyclopedia/compendium that is 11 years old. Why have people exited? Research shows they left because other sites came along that do the same thing better. Also, changes in life circumstances. Also, conflict with administration of the site. There’s a corporitization of some of the UGC sites. He also has looked into why new users don’t stick: They don’t glom onto the norms of the site.
Q: Are reasons for exiting a negative network effect? More than 150 and the network deteriorates?
Cliff: We see that in Usenet. But not so much at Facebook where you’re just dealing with your friends.
Q: Any sites that have tried to drive away new users?
Cliff: Metafilter has a bit of that. Slashdot has a “earn your bullshit” tagline.
Q: Are your students alone or with others when they are online? Are they aware of the technology?
Cliff: The rise of the netbook has had an effect. Most of my students experience social media as a group activity. But a lot of them are not that savvy. They generally don’t know how Wikipedia operates.
April 13, 2009
The University of Maine has approved new guidelines for tenuring and promoting academics [later:] in the New Media program (although see the comments for a complexification of this). The new guidelines allow crediting an academic for contributing to social media.
This the right thing to do not only because it is a more realistic assessment of an academic’s worth. It’s also the right thing to do because it helps to build the value of the network. If knowledge and expertise are becoming properties of the network, it is the social responsibility of our institutions to encourage the enhancement of that network.
February 26, 2009
Peter Suber, Research Prof. of Philosophy at Earlham College, a visiting fellow at Yale Law’s Information Society Project, and blogger of open access news, is giving a full-house lecture at Harvard, sponsored by the Berkman Center. [Note: I’m live blogging, making mistakes, leaving things out, paraphrasing ineptly, etc. POSTED WITHOUT PROOFING or even with a basic re-reading. Speed over accuracy. Welcome to the Web :(]
Peter says he’s going to assume that we know what open access is, etc. But he does want to define Green Open Access (= open access through a repository) and Gold OA (= OA through a journal). There’s also Gratis OA (free of charge but may be licensing restrictions) and Libre OA (free of charge and free of licensing restrictions).
Peter says he doesn’t know the future of OA. He likes Alan Kaye’s comment that the future is easier to make than predict. He’s going to talk about 12 cross-over points in OA, in rough order of when they might occur:
1. For-pay journals allow green OA. About 63% of these journals already do this.
2. OA books:: When there are more gratis OA books online than in the average university library. We crossed this a couple of years ago. “The permission problem is harder than digitization.” The next cross over point here is getting more libre OA books online, which we are quite a distance from.
3. Funder policies: “When most publicly-funded research is subject to OA mandates.” This seems to be spreading, Peter says. Today, 32 public funders and more than 3 private funders have OA mandates.
4. Green OA deposits: “When most new peer-reviewed manuscripts are self-archived when accepted for publication.” In particle physics, this happens routinely. If 20% of researchers publish 80% of the articles, we could reach cross-over fairly quickly in some fields.
5. Author understanding: “When most publishing researchers have an accurate understanding of OA.” This is happening, but notvery quickly.
6. University repositories: “When most universities have institutional repositories,” individually or as part of a consortium. This is happening slowly. In the absence of a universal repository, every university ought to have one. Universities will get to this point more slowly than funders because they move more slowly than funders. And we ought to ask why. Aren’t universities interests in line with OA?
Libre gold OA: “When most OA journals are libre OA.” Most OA journals are still merely gratis, but curb copying to drive traffic to their site. This crossover could happen overnight if the journals understood the issues. They’d lose a little traffic, but nothing else. There are grounds for optimism: Open Access Scholarly Publishers Association is an assoc of OA journal publishers and it requires libre gold OA. The SPARC Europe program sets standards for what a good OA journal is, and it recommends CreativeCommons attribution licenses. These two orgs are helpful because there’s no topdown org defining OA, so we rely on bottom up orgs like these two to set the standards.
8. Journal backfiles: “When most TA journals have OA backfiles.” This is expensive to do. Google will do it, but Google’s terms are difficult: They don’t give the journal a copy of the digital files. (Libraries do get copies of the files of the books they let Google scan.) The OCA focuses on public domain literature. “Once digitized, the benefits of increased visibility and citations should outweigh the trickle of revenue.” Journals make most of their money from new issues, so having greater presence should help. In physics, almost 100% of articles are available OA but the publishers can’t see any dip in subscriptions.
9. Author addenda: “When most new research is covered by author addenda” (i.e., additions that grant OA permission, tacked onto standard publisher-author contracts). Now there are few adopters. It’d be good to standardize these. The cross over will come when universities or funders require it. If enough journals allow green OA, that’d make addenda unnecessary.
10. University policies: “When most university research is subject to university-level OA mandates.” Today, 27 universities and 4 depts have these mandates. It’d help to have the largest/most productive universities move on this first.
11. OA journals: “When most peer-reviewed journals are OA.” “I don’t expect this for a long time.” Now 15% are OA. Progress is slow, but there is progress. High prestige journals are likely to hold out for a long time.
Libre green OA: “When most green OA is libre OA.” Today, only a small fraction is libre OA because most OA repositories depend on permission from publishers. UKPMC Funders Group demands green libre. We will reach the cross-over “when it’s safe.” Harvard has taken the lead on this, Peter says, and it will spread as another large university takes this step, then another one … “It becomes self-fulfilling leadership.”
Q: Are we stuck with the Sonny Bono copyright extension act?
A: Yes. All copyright reform in the past few decades have been in the wrong direction. And it’s very hard to roll back copyright terms. The only silver lining is that when we have a consenting partner, we can bypass copyright via contract. The problem is that they’re not the default.
Q: Under libre OA, how are our scholarly attributions protected?
A: It’s a range. One end is public domain, which does not preserve attribution. But all the CreativeCommons licenses preserve attribution. Most scholars don’t want public domain; they want CC-attribution.”Creative Commons attribution license provides everything a scholar could want.”
Q: [me] Conyers!
A: The Conyers bill would tell agencies not to require OA for works they fund. [I’ve put this badly.] The OA advocates are fighting it, but the agencies affected are not yet. I think Conyers is serious about it. I think he introduced it early because we don’t have a Sect’y of Health and Human Services or of NIH. Conyers may be fighting a turf battle. [Paraphrasing!] “He’s motivated primarily to protect the jurisdiction of his committee.” Peter thinks it won’t pass, but it might be introduced into another bill. “We’d like to spread the NIH policy to the rest of the government.”
Q: Is the economic downturn accelerating the adoption of OA?
A: The NIH just got $10B in the stimulus, which means there will be more and more OA articles. NSF also, but not as much because NSF requires OA for reports generated by those they fund [may not have gotten this right]. But, Peter thinks the downturn strengthens the case for OA. Libraries are going to be canceling subscriptions. And the Stimulus’ emphasis on green research will be more valuable if it’s OA. Open access to research amplifies its value.
Q: [jpalfrey] You’ve noticed there’s no OSF equivalent for OA. But I’d argue that the people in this room — librarians — are your OA OSF. What do you say to these librarians to advance our common cause?
A: Librarians are among the most important allies in the OA movement. But put all the allies together and you still don’t have OSF. Libraries should be sending letters against the Conyers bill. When you negotiate subscriptions you should negotiate the right to pur articles from your authors into an OA repository. Libraries are the only buyers of peer-reviewed journals. When you’re the only buyer, you can dictate your terms, subject to anti-trust. Obama says that we have the right to demand transformation from the banks we’re saving. Librarians can do the same thing for journals. Journals are not serving all of our interests and are acting against other interests. Use your bargaining power. Get the right of self-archive, and, when the time is right, get the right of libre self-archive. Network with one another when you launch repositories. And, btw, every school with an enlightened OA policy had librarians in the head of the charge.
Q: Can you give an example of an archive that works?
A: Universities that have mandatory language still have to supplement the language with incentives and education. As you go from unmandated to mandated, it goes from 15% toward 100%. (15% is the average for voluntary, spontaneous archives.) It works best in the Dutch universities that let the “cream” of the article rise to the top. Every week they feature good work in public. This gets academics to archive their work without a mandate.
Q: Might universities work with publishers collaboratively to create new business models?
A: Publishers differ in their attitudes toward OA. Some are experimenting in good faith. Some, in bad faith. Some who do OA are actively lobbying for the Conyers bill. Librarians understand the scholarly landscape better than publishers and could educate publishers. Society publishers [i.e., societies that publish] could be told that they’re threatened not by OA but by the “big deal” that brings in academic journals.
Q: Is Springer’s taking over of BioMed Central a good thing?
A: Yes. BMC is for-profit. BMC was the world’s largest OA publisher. Now Springer is. Springer says that OA http://arubatourism.com/assets/blog/index.php?=buy-viagra-through-paypal/ is a sustainable part of their bsiness. My reading is that Springer is preparing for an OA future.
Joho the Blog uses WordPress blogging software.
Thank you, WordPress!
