Conference:
ECER 2009
Format:
Round Table
Session Information
12 SES 6.5, Cross-Network Roundtable
Crossnetwork Roundtable
Time:
2009-09-29
13:30-15:00
Room:
NIG, HS 3D
Chair:
Alexander Botte
Contribution
Currently, technically based infrastructures to support scholary work, cooperation and communication are debated very much; only a few applications have been fully developed and are offered to the scientific communities. The development of such facilities, mostly named ‘e-science’ or ‘e-research’ – depend on intensive interaction between information specialists and scientists in the different disciplines. The session will be focused on ways of improving scientific cooperation, exchange of information and publishing. Thus it will support central objectives of EERA. As, unfortunately, the debate about e-science takes place mostly in the circles of information specialists and librarians the session will also be a necessary step to involve the discipline of educational sciences with these new opportunities.
Peter Halfpenny, Exec. Dir. With the National Centre for e-Social Science at the Univ. of Manchester, will talk about ICTs enabled advances in social research. In his presentation he will explain and exemplary illustrate what is e-science and what is e-social science. By way of pointing at manifold projects in different areas of social sciences, including examples from educational sciences, the talk will demonstrate how new applications of ICT can support the progress of scholarly work.
Michael Granitzer, Division Manager wtih the Know-Center at the University of Graz, will talk about
Social Semantic Web Technologies for e-Science. In his presentation, success factors of the Web – focusing on the social and the semantic Web – will be analyzed and applied to the problem of e-science. The talk focuses on semantic technologies like RDF/OWL for e-science and explains the basic principles behind. In particular it tries to answer what can and what cannot be expected from semantic technologies to solve particular e-science problems. Methods for automatically extracting semantics from unstructured or semi-structured information will be shown to give ideas on how to bootstrap semantic technologies for particular application domains.
Method
Expected Outcomes
References
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