This presentation was delivered by Stratos Kontopoulos and Panos Mitzias from PERICLES project partner CERTH/ITI at the interactive workshop ‘Eye of the Storm: Preserving Digital Content in an Ever-Changing World’ (Wellcome Collection Conference Centre, London, 2 December 2016). This full-day event aimed at introducing and experimenting with the PERICLES model-driven approach demonstrating its usefulness for managing change in evolving digital ecosystems. http://pericles-project.eu/

1. GRANT AGREEMENT: 601138 | SCHEME FP7 ICT 2011.4.3
Promoting and Enhancing Reuse of Information throughout the Content Lifecycle taking account of Evolving
Semantics [Digital Preservation]
“This project has received funding from the European Union’s
Seventh Framework Programme for research, technological
development and demonstration under grant agreement no601138”.
Stratos Kontopoulos, Panos Mitzias
(CERTH/ITI)

2. “... a formal, explicit specification of a shared
conceptualization...” [Studer et al., 1998]
Upper ontology: A model of the common objects that are generally
applicable across multiple knowledge domains.
Domain ontology: A model of concepts that belong to a specific
domain or part of the world.
machine readable
with computational
semantics
unambiguous
concepts,
properties,
functions, axioms
definition
commonly
accepted
consensual
knowledge
abstract,
simplified model
of a domain
[Studer et al., 1998] Studer, R., Benjamins, V.R. and Fensel, D. (1998), Knowledge engineering: Principles and methods.
Data & Knowledge Engineering, Elsevier Ltd, Vol. 25, Issues 1-2, pp. 161-197

3. ◦ Classes (concepts)
Superclass/subclass
relationship
◦ Properties (relationships)
Subject → Predicate → Object
◦ Axioms, restrictions and
constraints
◦ Individuals (instances)
OWL - the Web Ontology
Language

4. Pros:
◦ Variety of existing tools for representation,
consistency checking, reasoning, risk assessment etc.
◦ Great fit for model-driven DP → queries & rules.
Cons:
◦ Not fully mature technologies yet.
◦ Significant expertise & effort needed.

5. ▶ LRM -
ontology for
modelling
linked
resources
▶ DEM –
formalism for
digital
ecosystems
▶ Domain
ontologies

6. ◦ Ontology editor developed by Stanford
University
◦ Free and open-source
◦ Version 4.3 will be used in the examples
◦ Current version: 5.1.0
◦ Also available as a web application

12. Video
CodecContainer
container1
video
1
codec
1
hasCodechasContainer
hasDuratio
n
video
2
codec2
Integer
(e.g. 120)

13. Tasks:
1. Open Protégé.
2. Create classes Video, Codec and Container.
3. Create object properties hasCodec and hasContainer.
4. Create datatype property hasDuration.
5. Create instances for each class (e.g. video1, codec1, etc.).
6. Set the duration for each video.
7. Connect instances using object properties.

14. ◦ Why start from scratch? There is almost always an
available third-party ontology that provides a useful
starting point for our own ontology.
◦ What do I gain?
◦ Save the effort and time.
◦ Use validated and well-established ontologies.
◦ Take advantage of others’ domain expertise.
◦ Interact with the tools that use other ontologies

15. ◦ What to reuse?
◦ Domain-specific ontologies
◦ Upper-level ontologies
◦ Ontology libraries
◦ Other resources
◦ How is it done? Let’s go to exercise 2!

16. Tasks:
1.Open Protégé and create a new ontology.
2.Import the Digital Video ontology design
pattern from
http://mklab.iti.gr/pericles/DigitalVideo_ODP.
owl
3.Add a subclass of DigitalVideo called
AnimationVideo.

17. ◦ What is a reasoner? A piece of software able to infer
logical consequences.
◦ What does it do?
◦ Derives implicit information from explicitly
asserted knowledge.
◦ Performs consistency checking and validates the
ontology schema and content.
◦ Known reasoners: HermiT, Pellet, FaCT++, Drools

18. Tasks:
1.Run HermiT reasoner and check the inferred
information for class AnimationVideo.
2.Stop the reasoner.
3.Create instances for classes AnimationVideo and
VideoStream (e.g. shrek and videostream1).
4.Connect these two instances with property
hasAudioStream.
5.Run HermiT reasoner and check results.
6.Stop the reasoner and try to correct the errors!

19. ◦ Common inconsistencies
◦ Incompatible domain and range definitions for
transitive, symmetric, or inverse properties.
◦ Cardinality properties
◦ Requirements on property values can conflict with
domain and range restrictions.
◦ Solution: Specialized software (e.g. OOPS! -
OntOlogy Pitfall Scanner!)

20. Tasks:
1.Visit oops.linkeddata.es
2.Scan the Digital Video ontology with URI
http://mklab.iti.gr/pericles/DigitalVideo_ODP.
owl
3.Check inconsistencies

21. ◦ Linked Data: The concept of Semantic Web to create
links between datasets.
◦ DBpedia:
◦ Linked Data source with structured information
from Wikipedia.
◦ Available for querying via SPARQL language.
◦ Allows interlinking of the DBpedia dataset with
other datasets on the web.

22. Tasks:
1.Locate the instance of Shrek that we created.
2.Add the seeAlso annotation to
http://dbpedia.org/resource/Shrek