Then this evening I ran across this, by the incomparable Dorothea Salo:

I heard yesterday that one such corpus, while of impressive quality and very highly regarded in the discipline, was all but invisible on its home campus, according to the corpus’s own staff. Basically, these projects are what I have previously called fiefdoms. (If you don’t like that word, you may wish to substitute “research lab.” Most of what I’ll say applies to them as well.)

Sustainability is the crucial flaw in any sort of fiefdom model for data management. Most fiefdoms get the ball rolling with grant money. This may commit the institution to a certain amount of financial or in-kind support (depending on what the grant spells out), or it may not. If it does, that institutional support lasts only as long as the grant does. No one in this cycle—not the researchers in the fiefdom, not the institution, not the grant agency, no one—takes responsibility for the post-grant existence of anything the fiefdom produces.

Sustainability: the institutional fiefdom

any suggestions for libraries for demonstration projects?
– most common place to start is a thesis/dissertation IR; above that, more generally for scholarly works by faculty
– beyond that, far less standardized: storing data for faculty, e-science projects
– where are you at as an institution, do you have the resources in the library to support more ambitious efforts?
– danger is “if we build it, they will come” doesn’t work (ref Dorothea Salo: formerly here, now there)
– look at the software tools and staff resources, then look at faculty interests on campus

what are some ways in which rapid change can be encouraged?
– rapid, transformative change almost always comes from outside the organization
– simply let people use technology in unexpected ways
– can lower the resistance by providing the rights and the infrastructure to do interesting stuff
– training for librarians: semantic web camps, data linking camps etc – standards are still being built, aren’t many experts; in the short term, simply being a part of this conversation is a step
– pay attention, get training, build collaborations with faculty: change will come from users, not institutions

what might be strategies for realigning fiscal imperatives?
– open question
– institutions and funders are part of the same system
– can begin to make change by looking at past successes; e.g. of genomics and proteomics: funders have created a standardized data library through NLM, requirements that publications reflect data in same standardized ways
– when we fund the creation of data, it needs to live somewhere on the internet, with standard identifiers, in ways that others can access it
– yet to be decided who will do this, and how; but important role for libraries to provide storage facilities, naming standards

with respect to involving faculty, how can librarians most effectively bring faculty onside?
– faculty aren’t standardized
– try to find people who already agree with us, rather than expend the energy to convince people we’re right
– build understanding of what their role is, what they can achieve by working with librarians, will be different how to do this with different faculty

are IRs generally under the library?
– yes, don’t know of cases where it’s not

what are your hopes for Open Access Week?
– good way to get general knowledge built
– outside the open access movement, most people are completely unaware
– students get involved, librarians reach out to faculty, we’re all in this together: broader understanding that we can change in the way we communicate knowledge; get the message out beyond the niche

genome project mechanisms?
– big, international project
– data went into NLM site, by default entered public domain legally; raw facts, not creative works, so from a publication perspective they were public domain from the outset
– in practice, the process was slower, many of the sequencing labs held on to their data waiting for publication: US government met with the scientists and developed a process to drop all sequencing data into the website within 24 hours, but retain the right to first publication on the sequences they had included
– also required all publication on genomics to reference database identifiers to sequences being used: became habitual that everyone simply started depositing all their sequencing in the database, and open data access became normal: a set of interlocking initiatives that created the ecosystem for open data

how might librarians acquire necessary skills?
– technologies are relatively difficult to pick up, but there are semantic web conferences, get-togethers, mailing lists: lots of chatter on the web where standards are being developed
– best way to get involved is volunteer and get going
– begin looking at your library’s metadata and see whether there are pieces that can be exposed, make your stuff usable and findable

do other institutions play a similar role to libraries?
– libraries are important infrastructure to the data network: stability over the long term is difficult for institutions to achieve, libraries/universities tend to stick around longer.
– libraries providing storage infrastructure, metadata
– researchers must see a value in marking up their data, in reaching out to the library
– lastly, companies will come to see these open data sources as resources for creating value-added services that might be profitable
– libraries need to create the most usable, open layer; think of your content as a web 2.0 platform on which others can build applications

interoperability best practices and norms?
– differ widely, difficult to make a general statement
– even within the life sciences, very different between those who deal with people and those who don’t (privacy, etc.)
– need data that can be reused, funders should require reusable data
– universities need to look beyond the impact factor of journals towards the accessibility of data/informaton when evaluating faculty
– creators need to be rewarded for interoperable and reusable data

how to manage conflict between collaboration and competition?
– some people just like to share, others don’t
– by promoting to people who do like to share, over time universities who provide sharing tools will out-compete universities who don’t provide that platform
– expects a new set of impact factors that will reward scientists whose data leads to more data and more publications
– institutions who are ready with that platform will be in a position to recruit the best faculty: your job is not just to harvest data for publication, but to promote reuse in a web context, and we can support that better

are open access economic models useful for open data?
– big differences
– legally, it’s universally accepted that copyright applies to journal articles, copyright is comparatively harmonized internationally re articles; don’t have that with data: public domain in US, in UK there’s a “sweat of the brow” protection, crown copyright applies to govt data in commonwealth
– economically, without the harmonious legal framework, there are disincentives to overcome the issues of data accessibility: data needs to be processed to be understood, so it’s not just about publishing and dealing with copyrights, there’s an enormous cost to formatting data for human or machine reading
– no established industry of data promulgation: no entrenched industry fighting change, but also no established ways of doing things; have to bootstrap a data publishing system: registration, certification, dissemination, preservation
– no peer review system for certification, difficult to disseminate, how do we decided what to preserve and for how long….
– add additional layers specific to data, and it becomes really hard to envision open data

how to get large, commercial non-profit journals to switch to open access?
– easiest way to make this transition is for journal to allow authors to retain copyright
– economic issue is bigger, because commercial non-profit journals rely on subscription fees
– education around support fees, etc.
– a lot depends on the sector, the journal, the finances
– key is to remember that it’s usually an economic rather than a legal problem

some of the more successful approaches to encouraging researchers to follow good data management principles?
– astronomy; open, standardized system where experts and non-experts can post and share data
– incredible number of standards developed by the discipline
– model we should be looking to
– the people who cared about sharing data put in the time and effort to make their data open and interoperable
– researchers are motivated by solving problems they have: must work to create a culture in which the solution to your problem is an open solution
– incentive is to publish; must develop an infrastructure that makes shared data usable, useful, and valued; there is no scholarly punishment for bad data management

[missed one question, but the gist was that the web becomes the infrastructure for humanities and social science applications as well
– the expertise will get paid for in the sciences before it gets into the humanities

how to address learning curve for researchers?
– starting to have more skills, rapid web prototyping changing the game
– outreach and training should be the universities job: wouldn’t it be nice if everytime some did powerpoint, instead they could run a simple demo program?
– waiting: generational changes
– 15 years ago writing web pages was an arcane exercise
– today, prototyping systems make it easier for people to write code that acts on data

neurocommons project?
– initial focus in neuroscience, but it has forked into these three things:
1. a distribution of integrated, public domain data which will soon have a name, becomes the nucleus for distributing data in a package model similar to linux distros
2. standards development effort: web ontology not far enough along
3. problem with persistent web identifiers: proposed semantically empty URLs that are persistent and allow mapping of names, binding them under unique identifiers; shared names can’t be taken private or changed, the community owns the names and the people who use the names are in charge of them
– future goals: RDF distribution adopted as standard communication protocol for data
– need to get more people involved and engaged
– really want shared name thing to become equivalent to DNS for data, prefer to have discussions around that in the community rather than just in Science Commons

A set of services offered by a university or group of universities to members of its community for the management and dissemination of scholarly materials in digital format created by the institution and its community members, such as e-prints, technical reports, theses and dissertations, data sets, and teaching materials. Stewardship of such materials entails their organization in a cumulative, openly accessible database and a commitment to long-term preservation when appropriate. Some IRs are also used as electronic presses to publish e-journals and e-books. An institutional repository is distinguished from a subject-based repository by its institutionally defined scope. IRs are part of a growing effort to reform scholarly communication and break the monopoly of journal publishers by reasserting institutional control over the results of scholarship. An IR may also serve as an indicator of the scope and extent of the university’s research activities. (institutional repository (IR))

Wikipedia:

An Institutional Repository is an online locus for collecting, preserving, and disseminating — in digital form — the intellectual output of an institution, particularly a research institution.

For a university, this would include materials such as research journal articles, before (preprints) and after (postprints) undergoing peer review, and digital versions of theses and dissertations, but it might also include other digital assets generated by normal academic life, such as administrative documents, course notes, or learning objects. (Institutional repository)

CARL:

An institutional repository (IR) is a digital collection of an institution’s intellectual output. IRs are a key infrastructure component in the digital environment because they provide better access to our digital assets and they ensure that digital objects are managed appropriately. (Canadian Institutional Repositories)

For the record. . . .

But the position does come with some expectations, and one of these is to guide the development of our institutional repositories. The problem is, I’ve always been a little skeptical that libraries should dedicate resources to archiving copies of the published work of their faculty. Essentially, you end up with a large collection of disparate materials united only by the fact that at least one of their authors was affiliated with a specific institution. And nobody asks themselves, “Gee, I wonder what people at University X are doing in my discipline?” One of the reasons why academic journals exist is to collate research output by discipline, and if I want to stay on top of things in my field, I read those journals.

Not to say there aren’t useful things we can do under the rubric of institutional repositories. For institution, at Leddy we’ve been working on locally mounting digitized copies of UWindsor dissertations and theses. But generally, I don’t think creating additional copies of already published works and “exposing” their metadata is a particularly useful contribution to scholarship.

Now, it’s not like I haven’t read anything about this in the past, but I need to do a bit more focused reading over the next little while. And since I’m going to talk about it here, I figured it wouldn’t hurt to expose my prejudices first.

Legal system provides poor tools for resolving disputes over technical mediation of access to information: e.g. DMCA limits on tinkering with music/video formats and players; iPhone tinkering that can result in bricking. Unsatisfactory to give Apple final decision on whether tinkering activities are lawful. Categories are unsuited to technological convergence: iPhone is media player, software, and consumer equipment. Underlying conceptual frameworks do not address consumer’s freedom to tinker with an owned device

e-voting software is proprietary and copyright claims have been used to keep potential problems with e-voting secret. Government profiling: what algorithms get a name on the no-fly list? Where does the data come from?

Search engines and social networking: ability to identify users from search histories, Facebook problems involving new, mandatory features that consumers don’t want. Privacy issue with gmail using contents of email to generate ads–what then happens with the data? Algorithms and data use become trade secrets.

Legal tools don’t address the issues of accessibility to information and more importantly to the technical rules that govern and shape the networked environment. The legal framework operates to obscure technical rules.

Lessig, Code and Other Laws of Cyberspace (1999): Code is law. Intended metaphorically. Some take this literally, but of course states have no role. Others resist this idea, code is regulated by the market, therefore not law but “market ordering”. However, tools used to evaluate market ordering don’t square well with code, which can be developed to constrain market choice. Network emerges at conversion of public and private interest.

Others argue code is a form of regulation unique in human history: uniquely plastic ex ante and uniquely inflexible ex post, therefore new ideological problems. Based in a thoroughly discredited theory of technological determinism that fails to take into account aspects of social interaction and the evolution of code.

Too easy to understand law, code, market, as distinct Newtonian vectors, overlooking synergies among them and the fact they are strategies deployed by actors to serve self-interested goals.

Consider the larger context in which coded structures emerge. Legal frameworks to regulate access to systems are extended to impact ToS agreements and set parameters for marketplace behaviours. “Technical systems intended to police copyrights. . . represent one prong of a more diversified portfolio of strategies for controlling the shape of the digital media environment” (approx 20 min). Privacy, security, and technical systems for profiling increasingly linked to strategies for monitoring personal mobility and communications traffic. New systems of social ordering emerge where industry and government interests overlap.

How does code regulate? New structures establish prohibitions, but also new political economies around authorization of access to spaces, websites, information, resources, databases, transactional privileges. Governance of access to systems initially conceived of as protecting self-contained systems from malicious attack, not regulating market behaviours. If desire to use copyright to control access to digital files is legitimate, where digital files are widely distributed, controls must be as well, as must processes of authorization. “The figure of the hacker now coexists uneasily with the idea that the real locus of our distrust is the ordinary user” (24.30ish). Finally, privacy/security controls are inverted: authentication controls are all around us, and we become outsiders who need to identify ourselves to have access.

Freedom of speech/information is a central organizing philosophy in our culture, but much of the political economy of the networked information society is organized around secrets. Authorization and authentication become objects of desire, commodities, inducing us to reveal more and more of our personal data. Our trust in the market has allowed what are fundamentally governance decisions to be regulated by technical standards often developed in secrecy.

Everyday experience of the network: most users are not coders, bloggers, contributors to Wikipedia, etc. nor are they security experts or hackers. People generally interact with the network for mundane purposes, finding directions, ordering stuff, communication; to a lesser extent community building. When everyday user innovation comes into conflict with authorization regime, that’s at odds with how innovation historically occurs. More importantly, authorization regime seeks to instill a culture of permission-seeking in a predictable network environment in which independence of mind and action ceases to be valued. May also remake conditions of subjectivity and social identity.

Law and policy making must address these things comprehensively. Law should mitigate rather than reinforce structural problems arising from political economies of authorization. Best done through legislation, rather than waiting for courts to figure it out based on existing, inadequate frameworks. Regulations mandating greater transparency around closed systems, codes, data retention policies would help. However, transparency is retrospective, policy makers should recognize that users have interests to assert. May want to consider imposing obligations within standards processes.

via Boing Boing

In a rapidly changing technological environment, it is never enough to teach people to use these tools; the education process must enable students to adapt to new tools on an ongoing basis, and even to create their own tools. This certainly requires basic technological knowledge, but since much of what you can teach in a two-year master’s degree program will be out of date by the time a graduate has joined the workforce, the post important educational function is the inculcation of a disposition toward technological innovation and a critical sense of how technology can serve and advance an organization’s mission.

For all these changes, we must avoid the simple view of technological innovation and diffusion as one-directional. Technological shifts can operate in a refining manner, one that is not only revolutionary but that also returns us to the essentials of our craft. Librarianship is intellectual work, and the best practitioner’s role is never determined solely by the technology (though generations of workers might have acted otherwise). Consequently, though media and forms of information might shift, the professional’s role may thus be enhanced, especially where the shifts enable a new focus on the mission of the larger organization. Again, if our goal is to enable discovery, the emerging information infrastructure can place information professionals who fulfill this role at the center of activity. (55)

Dillon, Andrew. “Accelerating Learning and Discovery: Refining the Role of Academic Librarians.” No Brief Candle: Reconceiving Research Libraries for the 21st Century (PDF), 51-57.

In its local role, the library will be optimized to meet the needs of its campus community. The library is likely to provide repository infrastructure for stewardship of university-based information assets. Most of those assets will support pedagogy, administration, student life, alumni affairs, and other things vital to the school. A much smaller portion of them will support research. Research will be a far more global phenomenon than local institutions can support on their own.

In its networked role, the library will be able to support research and dissemination to the extent that it is tightly networked into the increasing cluster of inter-institutional collaborations that enable the creation and use of scholarly content. These collaborations will be key elements of research cyberinfrastructure, an infrastructure that will be a research-and-dissemination platform. In the magic phrase of the digital era, it “will scale,” be ubiquitous, and support a variety of scholarly domains, from astronomy to nanobiology, archaeology to urban design. The next-generation research library must be firmly embedded in that infrastructure, because that will be the platform to which scholars will gain access on their laptop library. (18-19)

But here are some interesting bits. I was hoping to cite only those that avoid the passive, but that just isn’t always possible.

1. “ . . . develop a rigorous research agenda. . . .” For me, the emphasis should be on “rigorous”.

2. “The research library should be redefined as a multi-institutional entity.” This is happening quickly in some areas, more slowly in others. We have an agreement in Ontario that effectively functions as a province-wide policy for print serials holdings for the 20 member libraries of OCUL, but we’re nowhere near consideration of the strategies itemized in this document, which if implemented here would effectively lead to a single provincial library.

3. “Greater collaboration among librarians, information technology specialists, and faculty on research project design and execution should be strongly supported.” I cite this recommendation with interest because what they’re talking about in the context of collaboration are the core elements of a new position I have recently taken on: scholarly publishing, institutional repository development, data curation, and digital resource development. The emphasis here is on faculty research.

Finally, 4. “More funds should be allocated for experimental projects and new approaches,” which dovetails nicely with 8. “Institutions should use studio and design experiences as the basis of a new library school curriculum.” I’d like to bend recommendation 8, though, and apply it to the notion of pursuing experimentation embedded in recommendation 4. Libraries are a built environment physically, virtually, and conceptually. The librarian-as-designer gets to experiment with and ultimately decide how to build (and renovate, and tear down, and rebuild). Exciting!

Incidentally, Part II of No Brief Candle consists of eight essays by conference participants.