1. Ontologies and foreign data models
Paul Millar

2. Contents What is an ontology? What is it useful for?
More on ontologies
Foreign data models
Consensus approach
When consensus breaks down
How to use others' results.
6/19/2018
Talk Title

3. What's an ontology?
“a formal, explicit description of concepts in a domain of discourse” -- huh?
Lots of things exist in our world:
events, files, datasets, users, physics groups, roles, collaborations, sites, storage elements, ...
We group these things into different classes
We can define/add properties for classes
Also add restrictions(facets) to properties
With specific instances(data), this is a knowledge base

4. What's it useful for?
To share common understanding of structure of information amongst people or software agents
To enable reuse of domain knowledge
To make domain assumptions explicit
To separate domain knowledge from the operational knowledge
To analyse domain knowledge
Taken from Ontology Development 101: A guide to creating your first ontology; Noy & McGuinness

5. Dataset hierarchy
The most important property of a class is the taxomic relation (“is-a”).
Multiple inheritance is expected.
Some examples
Production dataset is-a/is-a-kind-of Dataset
Analysis dataset is-a Dataset
Reco-source is-a Dataset
RDO dataset is-a Reco-source dataset
RDO dataset is-a Monte Carlo dataset
TDAQ dataset is-a Reco-source dataset

7. Decomposition A item is made up of one (or more) components
Limited by cardinality
Examples
File is-part-of a Dataset
Event is-part-of a File
Production Grid Job is-part-of a task
Task is-part-of a transformation chain
Tier-n is-part-of a geographic region
Site is-part-of a Tier-2
CE is-part-of a Tier-n

8. Explicit “other” links
Other links (properties/slots) are possible:
Analysis dataset is-created-by a user
Production dataset is-result-of a physics group
File1 is-replica-of File2
Job is-requested-by a User
User is-member-of a physics group (or more than one)

10. Foreign data models
Two (groups of) users might have different understanding (ontology) about a particular environment
Particle Physics is mostly about annotating datasets (private Tags)
There will be no standard dictionary.
No way to know that number X (by Physicist A) represents the same concept as Physicist B represents with number Y.

11. Consensus
So, “easy” solution, build up a dictionary of well-defined words.
No so easy:
should be unambiguous
should be complete
should be well adhered to
should be static

12. Consensus breaks down
We imagine that no one can (or has the time to) make the consensus model.
Each physicist does his/her own work and information is passed via peer-reviewed publications
This is probably “good enough”, but can we do better?

13. An ontological solution
Being able to bridge ontologies by specifying links between the two ontologies.
If the links are sufficient and the ontologies are compatible, then it might be possible to reason about relationships between components in different ontologies.
Speculative work is subject to a research proposal ... hopefully more news soon!

14. Summary
A quick introduction to ontologies and how they might be useful.
A introduction to the foreign data model problem (is it a problem?)
A possible solution, using ontologies.