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PERICLES Domain Specific Modelling - ‘Eye of the Storm: Preserving Digital Content in an Ever-Changing World’

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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/

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PERICLES Domain Specific Modelling - ‘Eye of the Storm: Preserving Digital Content in an Ever-Changing World’

  1. 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. 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. 3. ◦ Classes (concepts) Superclass/subclass relationship ◦ Properties (relationships) Subject → Predicate → Object ◦ Axioms, restrictions and constraints ◦ Individuals (instances) OWL - the Web Ontology Language
  4. 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. 5. ▶ LRM - ontology for modelling linked resources ▶ DEM – formalism for digital ecosystems ▶ Domain ontologies
  6. 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
  7. 7. Video CodecContainer container1 video 1 codec 1 hasCodechasContainer hasDuratio n video 2 codec2 Integer (e.g. 120)
  8. 8. 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.
  9. 9. ◦ 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
  10. 10. ◦ What to reuse? ◦ Domain-specific ontologies ◦ Upper-level ontologies ◦ Ontology libraries ◦ Other resources ◦ How is it done? Let’s go to exercise 2!
  11. 11. 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.
  12. 12. ◦ 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
  13. 13. 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!
  14. 14. ◦ 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!)
  15. 15. 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
  16. 16. ◦ 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.
  17. 17. Tasks: 1.Locate the instance of Shrek that we created. 2.Add the seeAlso annotation to http://dbpedia.org/resource/Shrek

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