1. Semantic technology as an informetric instrument Studying hybrid networks Raf Guns raf.guns@ua.ac.be

2. NORSLIS PhD course Informetrics - 1 “Semantic Web”?

3. NORSLIS PhD course Informetrics - 2 Central concept in the network 1950Network is central ↓ Pre-Internet networks 1965 Computers are central ↓ Internet 1990 Documents are central ↓ WWW 2010? Data are central ‘ Semantic ’ Web, web of data

4. NORSLIS PhD course Informetrics - 3 Technical matters “The semantic web is: a webby way to link data. That is all.” Basis: RDF -= graph-based data model -≠ syntax (like XML) Higher layers: optional

5. NORSLIS PhD course Informetrics - 4 RDF example

6. NORSLIS PhD course Informetrics - 5 Reality check Universal agreement? Evolutionary steps towards a web of data -microformats -OpenID -data interchange Peaceful co-existence of web of documents and web of data ‘Lower-case’ semantic web(s)

7. NORSLIS PhD course Informetrics - 6 Key point RDF: easy way to -talk about different kinds of things -express different kinds of relations between things  hybrid network Informetrics: typically occupied with -social data -‘informational’ data  Use RDF to connect all these data together and see what we can get out of it

8. NORSLIS PhD course Informetrics - 7 Research question 1.What (combination of) network structure features reflect changes/occurrences in the real world? 2.Can (combination of) network structure features predict changes/occurrences in the real world?

9. NORSLIS PhD course Informetrics - 8 Case studies 1.Scientometric data: publication, citation, collaboration… -Academic Bibliography University of Antwerp 2.Informetric (but non-scientometric) data -Agrippa: database with information about socio- cultural actors and archival materials created

10. NORSLIS PhD course Informetrics - 9 Derived networks Simple networks can be derived from hybrid Hypothesis: changes and occurrences are -reflected in more than one derived network -sometimes only ‘visible’ when considering multiple derived networks at once Open question: if hypothesis is confirmed, these are also present in primary network, but (how) can it be ‘seen’ in there?

11. NORSLIS PhD course Informetrics - 10 Preliminary methodology 1.Get data into RDF 2.Divide into time slices 3.Determine interesting occurrences 4.Examine network evolution in general in ‘neighbourhood’ of occurrences 5.Try to relate properties of step 5 (network) to step 4 (real world)

12. NORSLIS PhD course Informetrics - 11 Issues Focus Methodology