ADLRR2010: US Govt Perspectives

Paul Jesukiewicz, ADL

Lot of tech, but not a lot of uptake. There are lots of approaches out there to take stock of. Administration: we still don't have good ways of finding content, across govt portals. Need systems that can work for everyone and for varied needs, which is difficult.
Previous administration, not a lot of inter-agency collaboration; that is now happening again.
White House wants to know where things are up to; lots of money for content development & assessment. "Why not Amazon/iTunes/Google experience?"
Technically more possible than policy side. Push to transparent government, so open. Must support both closed and open content.
Will have to have system of systems, each system dealing with different kind of requirements.

Karen Cator, Dept of Ed

National Edu Tech Plan. Move to digital content.
* Learning: largest area, creating engaging and ubiquitous content.
* Assessment: embedded, multiple kinds including simulations; needs context such as "what's next", discoverable, should be ultimately pushable to student.
* Teaching: how to make teachers more effective, making sure they're connected to data and experts.
* Infrastructure: broadband everywhere, mobile access.
* Productivity: cost efficiencies day to day. Personalised learning is very participatory.

States are collaborating on standards; this is a microcosm of what is possible.

Bonus section: R&D. What more needs to be invented? Textbooks addressing full range of standards, not just the easy to test ones. Content interoperability and aggregation.

Student Data interoperability others are working on, including data anonymisation; but content interop is expedient priority for them now.

Open Source: the world is using it so we have to.

Teacher portals are all ad hoc; priority to get content interop there. New business models can arise given interoperable content, but this needs open models.

Content will have to come from everywhere—globally.

Frank Olken, NSF

Works on: Knowledge integration, semantic web, data mining.
National Science Digital Library: longterm program. Now built on Fedora, over RDF, Mulgara triplestore.
RDF enables faceted search, because multiple hierarchies are possible over same resource.
Big vocabs (esp in medical field) are happening through description logics, OWL. NSF not currently using it. RDF has been maturing quickly; the description logic engines and the rule systems are less mature, but the most important part of all of them is the conceptual map.
Most work on semantic web is in Europe through EU support; some US work is being commercialised, but not much US support for logic based approaches.

Can user contribute to taxonomy (= folksonomy)? They are doing research on turning folksonomies into rigorous taxonomies: open research over past two years, but no smashing success so far. NSDL metadata registry project.
Mappings between taxonomies: needs order-preservation to keep hierarchies internally consistent, active research.

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