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Notes on UK Ontology Network 2013
Transcript of Notes on UK Ontology Network 2013
How to Promote Open Data
Resistances to Open Data Publishing:
Fear of misinterpretation
They're mine! I want to publish over them!
a variant of: I want to make profit on them!
Distributing Data costs a lot
Difficulty in managing attribution, provenance
RExplore, Enrico Motta
[The main purpose of Rexplore is to provide a new tool for supporting users in exploring information about research...]
[…understanding of the
dynamics of research
areas (e.g., what are the main trends, what new topics are emerging, what significant research 'shifts' are happening,
how authors can be ranked,
compared and grouped together according to a variety of
ranking and similarity criteria,
how can fine-grained research topics be automatically identified and structured…]
UK Ontology Network 2013
Claudia Pagliarini, Importance of Ontologies in Healthcare
In epidemiology in particular, which allows for Integration of data sources
Jeff Pan, Tractable Ontological Stream Reasoning
Stream reasoning, i.e., about reasoning over dynamically changing data, in a tractable way
A reasoner based on TrOWL (http://trowl.eu/about)
which makes reasoning tractable via approximations
Notes by Marco Brandizi
He also presented:
"Empirical Knowledge Representation"
They did a user study to design the best ontology for an application domain (as it already happens for software engineering)
For instance, several options about representing time, proposed to the users and then choice was made based on their feedback
Endorsed by major search engines
By formatting your web pages with schema.org (via RDFa), you help search engines finding you and identifying contents/semantics in your pages (see slides)
A high focus on simplicity
Embarrassingly simple... little to do with ontologies in traditional Knowledge Engineering
We're living in an era of Mainframe Internet
We should aim at more democracy, as it is happening in Wikipedia
Including debates over what/how to publish, who can make changes etc
Three types of motivations for eHealth ontologies:
building terminology (eg, MESH)
building applications (eg, HL7)
focusing on biology and patient (eg GO, OBO)
On a similar topic: Janice Watson, Harnessing clinical coding in NHS Scotland