Semantic technology as an informetric instrumentStudying hybrid networks

Raf Gunsraf.guns@ua.ac.be

NORSLIS PhD course Informetrics - 2

“Semantic Web”?

NORSLIS PhD course Informetrics - 3

Central concept in the network

1950 Network is central↓

Pre-Internet networks

1965 Computers are central↓

Internet

1990 Documents are central↓

WWW

2010? Data are central ‘Semantic’ Web,web of data

NORSLIS PhD course Informetrics - 4

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

NORSLIS PhD course Informetrics - 5

RDF example

NORSLIS PhD course Informetrics - 6

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)

NORSLIS PhD course Informetrics - 7

Key point

• RDF: easy way to- talk about different kinds of things- express different kinds of relations between thingshybrid 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

NORSLIS PhD course Informetrics - 8

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?

NORSLIS PhD course Informetrics - 9

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

NORSLIS PhD course Informetrics - 10

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?

NORSLIS PhD course Informetrics - 11

Preliminary methodology

1. Get data into RDF2. Divide into time slices3. Determine interesting occurrences4. Examine network evolution

• in general• in ‘neighbourhood’ of occurrences

5. Try to relate properties of step 5 (network) to step 4 (real world)

NORSLIS PhD course Informetrics - 12

Issues

• Focus• Methodology