Watson: An attempt to scale up
the knowledge level
Using the knowledge level...
To make large scale
information and data
levels more exploitable
Example: The MK Data Hub
Data Infrastructure for the city of Milton
Keynes, enabling sharing and consuming
varied and diverse city scale data.
But… a large number of datasets for a large number of applications
MK Data Hub
Data cataloging needs to do more...
Data cataloging component to index data
based on their provenance, categories,
format, existing use, etc.
But needs to do more to answer questions
such as :
- Can I use those data for a commercial
application? Do I need to attribute
somebody? Even after processing?
- What can this data do? What kind of
things I can apply on it?
Ontological approach to data policies
Explicit, semantic representation
of the licences attached to data
As well as the data flows through which
they are processed.
Automatic propagation of policies through dataflows
Understanding what data can answer
Example of using formal concept
analysis to extract relevant
questions from an RDF (graph)
Ongoing work on generating interactive interface to ontology-based data
Tree is 4096
What is the
Towards populating ontologies based on dialog
Thanks! I don’t know
“great”, is it better or
worse than “OK”? ...
Alexa, tell moody that I’m
Towards the automatic exploitation of data
Example, in autonomous agents, using an ontology that provides a typology of
datasets and of data analytics techniques, making them better able to
automatically exploit the data they come across.
Knowledge representation and ontology
engineering have gone a long way from top down,
closed, domain centric knowledge-based systems.
From encoding expert knowledge to dealing with
scale, variety and diversity.
Now, becoming central in the necessary automation
of information processing, making data analytics
and mining more directly accessible, with fewer