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.

[Tags: social_media social_networks academics universities scholarship expertise ]

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Academia.edu lets you add yourself to its gigantic Tree of University Departments. It’s a slick, slidey, Ajaxy UI, and there seem to be only benefits to adding your name to it, even though it will forever be incomplete.

The question is whether it’s easier and more beneficial to count on participants to centralize their contact info at Academia.edu or to hope that universities somehow might agree on a metadata standard — a microformat — for how they list faculty members on their own sites. Since the latter isn’t happening, the former becomes appealing. (Thanks to John Palfrey for the link.)

[Tags: academics universities taxonomy folksonomy everything_is_miscellaneous ]

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Session description:

By lowering or bridging barriers, cyberinfrastructure can bring different institutional, enterprise, and policy models into unaccustomed proximity. The result may be powerful complementarities – or it may be competition or conflict. Since the separation between institutional and public policy also blurs, what kind of stewardship should the academy provide for advancing knowledge infrastructure? When should it take the lead in developing standards? How should it account for industry and sector differences? How should voluntaristic and cooperative models fit with market-based models? How should universities navigate/mediate between open and controlled models of knowledge?

Kaye Husbands-Fealing (U of Minn) leads the discussion. [I’m live-blogging which means I’m being sloppy, hasty, uneven, and erroneous.]

Arti Rai (Duke) reports on her study of how U’s have patented software through the 1980s and 1990s. The percentage of sw patents have been increasing, especially since the legal decisions making it easier to patent sw. [Unfortunately, I can’t keep my blogging up with her. Lots of info, and I don’t know the jargon well enough. Sorry! Here‘s a paper by her on the topic.]

Eliot Maxwell (Committee for Economic Dev.) Think about openness in terms of access and responsiveness. Responsiveness means people can contribute, distribute, etc. In the continuum of open to closed, the appropriate degree of openness is context sensitive. E.g., you don’t want medical records to be totally open. It’s not about IT but about the ability to get contributions from very different sources. It’s not always just the experts. It’s an attitude as much as it’s an instantiation in the infrastructure. What matters is adopting an ethos of sharing and collaboration, Eliot says. Instead of being the best and the only, the U should think about collaboration as a way out of the zero sum goal. The U should change the tenure system so getting info out onto the Web counts. Maybe U’s — including small liberal arts colleges and community colleges — should study how collaboration works and doesn’t work. We need to make info available, findable, searchable, interchangeable. Also, we need an attribution system since that’s the incentive. We have a technology to doing that, but we don’t always design it into our systems. In 15 yrs, U’s won’t be as associated with a place, about 4 continuous years, or about producing paper.

Brian Kahin (U of Mich) says we’ve been discussing different parts of the cyberinfastructure. We are seeing a rapidly expanding ecology of knowledge. How do you present this to industry, to the board of trustees, to legislators, to prospective students, etc.? Are U’s aligned with their own researchers on the nature and role of knowledge? None that Brian knows, he says. Open access is a paradigm for transformational effect. I don’t see the same thing on the tech side. I see very little interaction between legal scholars on patents and the U’s administration of patents. And this brings up the question of stewardship. What credibility does the U have to speak for public policy? And, we need to think about collaboration science, Brian says. We don’t have a lot of good info. We also ought to be working on strategies for developing standards. How do we have innovation policy when we have so many different models of innovation? Finally, is collaboration the be-all and end-all? On the Net we also see complementarity; that’s part of the Internet and probably should be considered part of the ecology of the cyber infrastructure. [Sorry this is so choppy.]

Q: (Kaye) Eco-innovation looks at the well-being indices and considers how innovation affects the end-users. How can we use the cyberinfrastructure to take the pulse all the way to the end user?
Arti: Erich Von Hippel has done a lot of work on distributed innovation. Users are innovators. Feedback to the researchers would be very helpful.
Eliot: Openness is consistent with that type of feedback. On the Internet, if you make a crappy product, everyone knows it’s a dog.

Q: What is the governance procedure for sunsetting data? Who decides how much data to store?
A: As organically as possible.

Q: Do we really want all projects to be sustainable? Shouldn’t some of them just die when they’re done? And some of them need non-open control of IP
Eliot: Yes, the openness should be appropriate to the project.

Q: It’s easy when talking about data to simply say that it’s a community issue and each community will develop its own ways of sorting these things out. But re-use and recombination of data for purposes far away from their original purpose is very exciting.
Arti: Great point.
Eliot: Maybe funders can help.

Do we really want funders to decide what’s sustainable? Shouldn’t it be a Darwinian process?
Eliot: Not decide. Funders should make applicants think hard about sustainability from the beginning.

Q: We still don’t know what we mean by “cyberinfrastructure.” Are we any closer to agreeing on it? How do we show its value if we can’t agree on what it means?
Brian: We can think of it as an asset (something you’ve already invested in) or as a prospect (where things are going). Those two questions come out in different ways. The asset vision is the Internet. The prospect points to semantics and ontologies that let you do more things with knowledge.
Eliot: I’m less interested in defining what cyberinf is that in what we’re trying to get from it, i.e., to be more collaborative and open.

Q: In my view, cyberinf is not just ICT. We should think of the infrastucture as being collaborative.
Brian: Part of what you’re talking about is virtual organization.

Q: A group of research U CIOs have been meeting to talk about what they can to shape the growth of a national cyberinfrastructure.

Q: We need to be able to talk about this simply and clearly.

[Too fried to blog. Sorry.] [Tags: cyberinf education standards universities patents ]

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Linda Katehi (U of Illinois) asks how we can design an infrastructure that enables and sustain collaborative work. [Standard live-blogging disclaimer holds: hasty, error-free, subjective, unworthy.]

John Wilbanks of Science Commons talks about the cultural infrastructure that enables content to move so rapidly and easily around the Net. He’s posted his comments on his blog. [Thank you!] “We are swimming in cultural infrastructure for content, but not for knowledge.” He is going to argue against having an end goal for the Network. “The end goal is to create a world we cannot imagine.” We shouldn’t even be talking about “papers,” etc. on the Net. We should be talking about namespaces, not just ontologies. “If we can’t use the same names for things, we can’t have knowledge.” Intermediate goals: End to End. We should make it easy to get answers to difficult questions. And we need to build human capacity. We should focus on getting greater throughput so data turns into knowledge and innovation. [Read his remarks on his blog.]

Mackenzie Smith from MIT Libraries asks what a knowledge infrastructure is. Now that John has given us the why, she’s going to talk about the “what.” There are seven layers, she suggests:

1: Repositories.

2 : Data management.

3. Linking (interoperable semantics). We need namespaces and identifiers, and encoding standards (e.g., RDF), and ontologies like Object Reuse and Exchange.

4. Discovery. Finding data on the Web.

5. Delivery.

6. Social.

7. Business models. Policies.

The IT view, Mackenzie says, is what you can plug into the layers. She talks about some of the various tools available.

The organizational view: Different areas of the U are responsible for the various layers. The one layer generally no one is addressing is the business layer.

Chris Mackie (Mellon Foundation) wonders how many infrastructure “successes” are really just “steaming piles of integration.” What’s the right way to do design? Bottom up? Top down? Knowledge needs to emerge and for that it has to be bottom up and open. But that won’t get us where we need to be. We also need it to be top down; we need global optimization. How do we pull these things together?

We cannot allow our cyberinfrastructure to be so top-heavy that it flattens all other organizations, including community colleges, etc. We need the diversity of the educational ecology, Chris says.

Sara Kiesler (CMU) has been studying collaborative research projects. About a third are successful, but about a third are failures, and a third struggle. What surprised her was that the problems in collaborating were not due to differences in how different disciplines approach their work. The biggest problems were inter-institutional. The two institutions have different bureaucratic procedures, regulations and cultures. No one in the institutions watches out for the welfare of inter-institution collaborations. And they don’t like it if the budget goes to the other institution.

John: We need both top down and bottom up. The key is to make sure they use the same standards. Standardize around names and transactions. You want to make it easy to stitch them all together.

Q: This is the first time the full range of institutions has been brought up, probably because the attendees come from major research institutions. So, good to have acknowledged there are other types of educational institutions.

Q: Physicists are used to collaborating. And the funding agencies drove the senior scientists to collaborate. Don’t underestimate the role of the funding agencies.

In the context of U’s, are there any warnings the panel has for us?
Chris: The challenges to collaboration are getting more real all the time. E.g., IP issues prevent some collaborations.
A: There’s the centralize-everything clique, the decentralize clique. Any preferences?
Linda: The totally centralized one doesn’t work in the US.
John: You can’t order people to innovate. You have to build systems that enable explosive innovation, based on standards. Making control the default doesn’t work. Harvard’s Open Access policy switches the default to sharing, with an opt-out. I think that’s the right way, but we don’t have the evidence yet.
Mackenzie: The decentralized model is a little more maintainable.

Sara: The collaborations that succeed tend to be the ones that have some practice doing it.

Q: Collaborative technology is still bad. And IP gets in the way. Also, U-industry collaboration seems to work best when the academic wants to have an effect in the real world.
John: The standard contracts for the life sciences depends on your tax status. Every collaboration with a commercial entity, even at a very early stage, gets complex very quickly. A simple design decision has made this hard.

Q: How do you align interests for collaboration?
Sara: Interdependence.

Q: The right question isn’t decentralized or centralized. It’s what you’re going to do that’s between those two, because neither of those will work.
Mackenzie: Dropping a governance onto a project at the beginning can kill it. There are many approaches.

[I’ve begun to fade — didn’t get much sleep last night, and live-blogging is really tiring… [Tags: cyberinf education standards universities ]

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Peter Freeman of the Washington Advisory Group introduces the first panel, on “Cyber-Enabled Knowledge”, by asking how the infrastructure can support the university’s essence as the creator, transmitter and preserver of knowledge. [As always, I’m paraphrasing, typing quickly, and undoubtedly getting things wrong.]

Guru Parulkar of Stanford says that we must build the cyberinf on the right foundation. That’s one that enables many layers. It requires supporting the end-to-end principle because that facilitates innovation. We should make the infrastructure programmable so that providers can give users empowering services. [Seems non end-to-end to me. But I think he’s talking about university infrastructure providers enabling experimental services, not having, say, Comcast build services.] It’s not enough to deploy vendors’ infrastructure on campuses. The CIO and researchers ought to get together on this.

Simon Porter, eScholarship Research Center, U of Melbourne, wonders what the world looks like when we can find about all the research going on in our university. We could manage portfolios of research under an overall university agenda. [Hmm. Possibly scary.] They could develop a data research plan. The university could plan its storage needs. The way the research is represented to the public will change: it won’t be left to the researchers to be the lead communicator about the project. There will be a single portal — like Amazon or eBay, perhaps — where you can find out about research. We will be able to evaluate research by the effect it has on other projects. Researchers will be able to cooperate more, especially if there are standards. Crystallographers have software that lets people annotate online models; this is promising.

Q: Simon and Guru both pointed to gaps between network engineering folks and the CIO. What’s blocking progress here?
Simon: It’s not a natural progression. You have to take a leap.
Guru: The infrastructure is so complex, there’s a reluctance to “muck it up.” But at Stanford there’s a lot of openness.
Peter: Market forces will bring about the healing of the gap.

Q: The infrastructure didn’t arrive on a gold cloud all at once. It’s built on standards. In a recent survey, only 30 universities (G7) had courses on standards. Standards aren’t taught or shared at universities.
Guru: I disagree with you completely. Universities should be doing research much before people think about standards.
A [we’ve been asked not to identify speakers without asking permission :( ]: The U’s are incredibly creative now. I believe the next thing will come primarily out of U’s. Things bubble up, and the standards follow after that.
Simon: Standards are fundamentally important for development of cyberinf.

Q: How do we change the research processes to take advantage of the new cyberinfrastructure. This is not a decision for the CIOs but for the college presidents, etc.
Peter: By acclamation, we agree.

Q: [me] Knowledge currently reflects the old infrastructure: You get published or not. Knowledge is binary, fenced in and managed. How will the new infrastructure change the nature of knowledge itself?
Simon: Especially with shared standards, research can be more open.
Peter: Simon has proposed a specific way to make available info about current reseach projects. That’s key to enabling cooperation and the development of standards.
Guru: The cyberinfs we deploy on our campuses should allow experimentation in networking, cooperation, etc. That type of infrastructure doesn’t exist because we haven’t been asking for that leel of programmability and flexibility.

Q (John Wilbanks): When we try to move from network standards to knowledge standards, we get into semantics. It’s hard to have enduring semantics because they change as research happens. We could have project-based standards and allow people to share what they mean about something, not just sharing the content. So we have to change the idea of standards. [Go John!

Q: Is it the U’s role to fund research into infrastructure? You can’t make a case to the provost unless you show some dollars coming from somewhere.
Guru: Yes, someone has to pay for it. Maybe vendor partnerships will help.
Simon: If it’s strategically important to the U, the U ought to do it.

A: I’m in bioinformatics. BTW, my U doesn’t teach any of the standards. Anyway, industry folks tell us we’re training students to be like you, not to be what we in industry need. E.g., not team players. How can we make more industry-academic partnerships?

A: There is something big going on that we don’t understand. We’re good at big networks, etc., but we don’t understand how to solve problems for small groups of collaborating domain scientists. Universities don’t just store, transfer and develop knowledge…

I direct one of the portals where project-based info can be shared. People keep asking what the incentive is for professors. Right now the reward structures are not geared towards publishing on the Internet. What can be done to fix the incentive system?
Simon: Making info available is always going to be a chore to researchers. But Facebook makes it possible for marketers to find info based on participation by users. We need something equivalent for researchers, surfacing info about projects without requiring additional work by the researchers.
Guru: If it’s a problem of aggregation? People are very eager to make their work public. Where is the disconnection?
Peter: It largely depends on the field.

A: I develop provenance metadata in my field. There are problems. Ontologies don’t exist yet. They require expertise in RDF as well as domain expertise, and that’s hard to find in the same person. The ontologies have to be developed internationally.

A: Maybe there are some Web 1.0 opportunities that haven’t been take advantage of yet. E.g., we could make available to any NSF researcher a Web page at the NSF site. That would also provide some authentication.
Simon: It’s not a web page. Every researcher needs a persistent identifier. [researcher or proejct??

A: Standards that have followed research experimentation and productization have been the most successful. E.g., Internet, LANs, the Web. The most spectacular standards failure was the OSI in the 1980s because they did it before they had the sw and the experiments.

A: At my [hardware infrastructure] company, we do a lot of rolling out of products internally that are not quite ready. We are probably more willing to risk failure than universities are. And we are seeing more demand for programmable infrastructure hardware.

I urge us to adopt a more expansive, active and empirically-grounded notion of infrastructure. We shouldn’t think of infrastructure as being primarily hardware. 1. The layer model encourages thinking of the hardware as the “real” stuff. 2. We need to be teaching our students the practices by which interoperability is made possible. The standards in ten years will be different, but the tensions and dynamics will stay roughly the same. 3. We should learn from previous attempts to build infrastructure.

A: Infrastructure is extremely important but that occurs in a multicultural environment that we should bear in mind. Second, it all comes down to open access. [Tags: cyberinf research science universities ]

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