Cliff – 20th anniversary of CNI. How to observe? Focus on the future. Going to putntogehter an ebook – the next 20 years – analytic and prescriptive, but not scenarios. Look at where we’re likely to go in the next 20 years in higher ed, scholarship, etc. Have to also talk about larger forces in society.
Why 20 years? Predicting the future is hard – failures of imagination and failures of nerve (Arthur Clark). Long enough to see change, but not be science fiction. Going to invite anyone who wants to respond to an opening essay that Cliff will write. Will reach out to some specific people. Will package up a selection of the essays in the ebook plus a print on demand option by end of CY 2011. Provide an offset to the short term focus of the last couple of years. When you look at some of the abrupt changes, the have long-term ramifications that need to be thought through.
It is a good time to think about the long term. Things that have happened in the last year worth mentioning. Some quite incredible things.
Cyberinfrastructure and e-science. Can already see big steps happening in changing of scholarship. Emergence of plan for next gen networks coming out of NLR an I2 – provisioning 10gb lambdas for researchers. Emergence of sensor networks – example of high speed trading, where the speed of light makes a difference. Area of greatest interest here -data curation. Big announce,net is NSF data plan requirement. Major step because it brings researchers face to face with questions about data. What’s important? Where can I get help? Good to get the conversation going across a wide range of disciplines. We’ll see other finders follow suit. Getting services in place for researchers is a non-trivial issue. Guidance for researchers is vague. Review panels could use some guidance. This is a great collective experiment. Would be good to have a database of successful data management plans, use that as a way to get a grip on what we should do going forward. We don’t have a good understanding of data life cycles. Not hearing words lime “forever” in is context. Hearing things like “a few years after the grant” That’s good – we’re good at keeping data for 5 or 6 years.
Open data movement. The idea that Data should be open and shared gaining inexorable traction in some areas. . Not paying enough attention yo software. Erosion of reproducibility makes it difficult. The idea from people like Ian Foster, where everybody should be able to inspect and run the model. Entering an age of simulations and models.seeing things like a proposal out of eth asking for a billion euros to build simulation of social data incorporating input from 70 databases. New kinds of simulation, multiple-input agents.
Getting to be strange world of artifacts. Digital preservation. Trying to get to a shared standard of what constitutes the historical record. Think of the change in news. Community journalism – a form of social network. If you look at how much time people spend I. Social media, you come to the conclusion that we should be preserving and archiving – LC getting the Twitter archive. Not only important retroactively, but turning out that some of the social media are predictive. A whole series of papers from folks like Hal Varian – things like twitter or search streams are good for predicting things like movie box office. Google has been working with CDC to predict disease archives by looking at queries about symptoms combined with geo-location. Interstingnhow difficult iti is to look at these in academic social science because of human subject issues.
Wikileaks – enormous dumps of data on the net that presumably have some historical value. Some libraries starting to amass data documenting human rights violations – the kind of puzzles we’ll be dealing with. The viciousness of responses is interesting. The network is getting to be a vicious place in ways that it didn’t used to be – e.g. The stutznet worm. A very complicated and sophisticated thing with some very specific targets. Lots of implications for what documentation of the social record looks like and our confidence in its integrity.
Rise of new scale phenomena – David Rosenthal has done some fine work. In a big enough system things are always broken, so you have to be able to design around that. The probability that you can read an entire disk is becoming a problem – need different ways of thinking. Resilient system design.
Mobile computing – not just about laptops or cell phones. Seeing devices in the middle, or image sensors, digital capture, overlays on the world. Old news – putting a camera in every pocket has had all sorts of social ramifications. Before the web, we used to have a zoo full of one-off apps, that wanted to be silos. Now we’re seeing that come back in the mobile world. Hundreds of apps, each talks to one specific info resource. Need to think hard about this as we think about integration of mobile. The potential to re-license content we already own is large.
Teaching and learning – seeing a maturation of LMS market. Being extended into collaboration suites. Also seeing a resurgence of other reads where computing gets involved – Intelligent tutoring, e.g. – actual teaching done with statistical models and machine intelligence. Long history of this that never gained traction in higher Ed, though it did in some niche markets commercially. This might be a direction for textbook evolution.
Been a lot of interest unleashing space – want to engage students at a deeper level, and have them take responsibility for their learning. Worry about saturation – engagement exhaustion. The problem is one of local optimization, at the level of the course. Need to think above the course – degree, certificate, etc. Will intersect with discussions of retention and time to degree.
We are busily building systems that collect data on students. Now want to exploit it – retention, student progress, etc. Need to use them wisely and transparently. If we’re not clear with students about data collection, we may lose the ability to make use of data streams. In consumer markets we are seeing the wheels of regulation move, which will complicate things while maybe not solving them.
Special collections entering a new golden age as they become digital. Fascinating things going on with individual personal collections. The public interest in private records is a frontier policy area.
Many services migrating out to the network level – software as a service. Lots we don’t u derstand. What do databases look like – linked data, trust, authoritative data, issues. Croppingnup in discussions of bibliographic control. We’ll also see it with names how does that connect to databases of things like grant proposals, biography, family history. The example of mathematical genealogy – your children are the people you advised on their thesis.
Will see lots of development with the relation between what campuses are doing and what’s going on nationally.
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