1. Universities and Colleges in the Giant Global Graph

2. Structure of the Session Introductory presentations – concepts and examples Introductions. Who are we all, what is our knowledge and background in this area, why are we here? Focus 1 – management of T&L Focus 2 – delivery/activities of T&L

3. Why Are We Here? 1. Because the meme of Linked Data has clarified where there is “traction” with the Semantic Web. More clear now: What is likely in practice through a bottom-up and minimalist approach riding on a tide of adoption vs What is possible in principle with a consistent stack of semantic web technologies 2. A background movement to open up public data

4. Bio2RDF – atlas of post-genomic knowledge

5. Linking Open Data cloud diagram by Chris Bizer But some of these are scraped or use Natural Language Processing

6. Principles of Linked Data Tim Berners-Lee Four Rules Assign URIs to things Use “http:” URIS so people can look them up Return information using standards (e.g. RDF, well-known ontologies) Link to other things Non-Rules to consider Don’t worry too much about the “semantic” word Think “things” and representations of them (information) not “documents” Distinguish information resources from non-information resources. E.g. the Eiffel Tower and an information resource about it were created at different times and by different people.

7. A Quote – Tim Berners-Lee “We started off with the Semantic Web roadmap, which had lots of languages that we wanted to create. The community got a bit distracted from the idea that actually the most important piece is the interoperability of the data. The fact that things are identified by URIs is the key thing. The Semantic Web and Linked Data connect because when we’ve got the web of linked data, there are already lots of technologies that exist to do fancy things with it. But its time now to concentrate on getting the web of linked data out there.” From ReadWriteWeb (via Talis Nodalities)

8. Future Directions Unimaginable things? Visualisation  And user interfaces generic and specialised Web of things  Devices  Sensors

9. Introductions and Interests

10. Questions to lead our discussion What information is available but locked up in documents or web pages (e.g. National Student Survey raw data) ? What information is locked up in university, college and other sector agency databases that could be exposed (e.g. anonymised library borrowing data) ? What new opportunities or knowledge arise from making this data available and joining it up? … anything more?

11. Focus Ideas 1 – Management of T&L Quality Enhancement and Assurance Accountability Business Intelligence Management Information Benchmarking Transparency Graduate employment

12. Focus Ideas 2 – Teaching and Learning Resource discovery Knowledge structures, cow-paths, further disintermediation of the teacher Sense-making of distributed discourse Learner as researcher – new information literacy, asking questions, testing hypothesis, visualisation. Social sciences? Physical sciences? Assessment Personal tutoring, pastoral care Some of these may venture more deeply into “proper” semantic technologies, to AI. How deep is too deep; at what point would we stray from the believable to dreamland? Or should we not worry and just consider the potential value of data for people to do unanticipated things with.

13. Process Discuss the focus – generate shared understanding of the scope Break-out to groups  Who are the stakeholders (broad categorisation)  What information is available but only as documents or web pages  What information is locked up in university, college and other sector agency databases  What new opportunities or knowledge arise from making this data available and joining it up Report back  One or more scenarios to motivate progress  A “to-be” fragment of the “Linked Data Cloud”  Who are holders of key data sources that CETIS/JISC should work with to make these sources open and linkable, and  Blockers and enablers