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New Audiences for Ontologies: Dealing with Complexity in Business Processes
Published on Jul 05, 20124012 Views
Today, governments and businesses have to deal with high degrees of complexity: The products they offer are highly individualized, there are many regulations they must comply with and all this has to
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Chapter list
New Audiences for Ontologies00:00
Safe Harbor Statement02:21
be informed02:33
Be Informed’s Ontology driven Business Processes02:43
Picture (1)03:23
Picture (2)04:12
Picture (3)05:24
Dealing with Complexity05:52
Traditional Approach06:32
Traditional Approach: Manually Consolidate Up Front07:21
Traditional Approach: Results08:24
Business Users express their own definitions & constraints, computers infer the process09:41
Ontology driven processes (1)10:39
Ontology driven processes (2)11:47
The actual process is derived from the constraints in the Ontology13:03
Flexible Goal Oriented Processes13:20
Selling Semantic Technologies15:07
Dutch Immigration Office (1)15:33
Dutch Immigration Office (2)17:06
Tax Office Dutch Caribbean (1)18:53
Tax Office Dutch Caribbean (2)20:08
EPO20:32
How we sell semantic technology?20:51
Actually, we don’t…21:20
What do we do? (1)21:32
What do we do? (2)23:08
Audiences across the Policy Lifecycle24:10
Chart (1)24:31
Chart (2)24:44
Chart (3)25:14
Policy lifecycle25:19
International Audiences26:08
Use cases for Multilingual Ontologies26:10
Dutch government immigration website 27:43
Labels in Legal Ontologies28:16
Labels in End User Dialog28:59
Monnet: Lexically rich representation of labels29:34
Monnet: Contextual Translation of Ontologies29:59
Monnet: Dialog Variant Generation30:41
Evaluation at Be Informed’s Clientbase31:16
Audiences New to Ontologies32:25
Who will be modelling?32:57
More Important: Who will be using the models?33:29
Grant application34:35
The web full circle?34:52
Self Documenting Models35:30
Generated documentation35:40
Explain what has been done36:16
And why other things can not (yet) be done36:41
Generated communication36:59
Verbalization in Be Informed37:42
Challenges in Verbalization38:40
Intermediate results from Molto Project39:11
Research Interest40:18
Workplaces40:36
fast validation42:14
Verbalization for Validation43:41
Correctness vs. Consensus45:18
Gamification45:59
Game46:02
A/B testing46:13
A/B testing at work47:07
Work with us48:37
Academic license50:09
Contacts50:44