Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

of

OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 1 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 2 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 3 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 4 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 5 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 6 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 7 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 8 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 9 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 10 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 11 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 12 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 13 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 14 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 15 OpenHPI 2.7 - How Much Semantics is there in RDF(S)? Slide 16
Upcoming SlideShare
OpenHPI 1.6 - The Vision of the Semantic Web - Part 2
Next
Download to read offline and view in fullscreen.

2 Likes

Share

Download to read offline

OpenHPI 2.7 - How Much Semantics is there in RDF(S)?

Download to read offline

Related Books

Free with a 30 day trial from Scribd

See all

Related Audiobooks

Free with a 30 day trial from Scribd

See all

OpenHPI 2.7 - How Much Semantics is there in RDF(S)?

  1. 1. Semantic Web Technologies Lecture 2: Semantic Web - Basic Architecture I 07: How Much Semantics Is There in RDF(S)? Dr. Harald Sack Hasso Plattner Institute for IT Systems Engineering University of Potsdam Spring 2013 This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0)
  2. 2. 2 Lecture 2: Semantic Web - Basic Architecture I Open HPI - Course: Semantic Web Technologies Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  3. 3. 07 How much semantics is there in RDF(S) Open HPI - Course: SemanticHarald Sack, Hasso-Plattner-Institut, Universität Potsdam Semantic Web Technologies , Dr. Web Technologies - Lecture 2: Semantic Web Basic Architecture I
  4. 4. How much knowledge (semantics) has RDF(S) rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdf:type rdf:type exv:SemanticWebTechnologies exv:takes Place exv:hasRoom exv:hasName HS3 Semantic Web Technologies exv:hasDate Tue 13.30-15.00 Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  5. 5. How much knowledge (semantics) has RDF(S) rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdf:type rdf:type exv:SemanticWebTechnologies exv:takes Place exv:hasRoom exv:hasName HS3 Semantic Web Technologies exv:hasDate Tue 13.30-15.00 Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  6. 6. How much knowledge (semantics) has RDF(S) rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdf:type rdf:type exv:SemanticWebTechnologies exv:takes Place exv:hasRoom exv:hasName HS3 Semantic Web Technologies exv:hasDate Tue 13.30-15.00 • The semantics of a term from an RDF(S) ontology is given in terms of its properties and its values (instances) Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  7. 7. an we ion sc Co nclus F(S )? Wh at ith RD ed uc ew d Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  8. 8. What conclusions can we deduce with RDF(S)? rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range exv:SemanticWebTechnologies exv:takes place Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  9. 9. What conclusions can we deduce with RDF(S)? rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range rdf:type exv:SemanticWebTechnologies exv:takes place • Deduction of entity class membership from the domain of one of its properties Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  10. 10. What conclusions can we deduce with RDF(S)? rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range rdf:type exv:SemanticWebTechnologies exv:takes place Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  11. 11. What conclusions can we deduce with RDF(S)? rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range rdf:type rdf:type exv:SemanticWebTechnologies exv:takes place • Deduction of entity class membership from the range of one of its properties Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  12. 12. What conclusions can we deduce with RDF(S)? rdfs:Class exv:Course rdfs:subClassOf rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range rdf:type rdf:type exv:SemanticWebTechnologies exv:takesPlace Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  13. 13. What conclusions can we deduce with RDF(S)? rdfs:Class exv:Course rdfs:subClassOf rdf:type rdfs:Class rdfs:Class rdf:Property exv:Lecture exv:takesPlace exv:Event rdfs:domain rdfs:range rdf:type rdf:type exv:SemanticWebTechnologies exv:takesPlace • Deduction of entity superclass membership from a class hierarchy. Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  14. 14. What conclusions can we deduce with RDF(S)? rdfs:Class rdfs:Class rdfs:domain rdf:Property rdfs:range exv:Person exv:isParentOf exv:Person rdfs:subPropertyOf rdfs:Class rdfs:Class rdf:Property exv:Person exv:isMotherOf exv:Person rdfs:domain rdfs:range rdf:type rdf:type exv:Alice exv:Bob exv:isMotherOf Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  15. 15. What conclusions can we deduce with RDF(S)? rdfs:Class rdf:Property exv:Person exv:isParentOf exv:Person rdfs:subPropertyOf rdf:Property exv:Person exv:isMotherOf exv:Person rdfs:Class rdfs:Class rdf:type rdf:type exv:Alice exv:Bob exv:isMotherOf exv:Alice exv:Bob exv:isParentOf • Deduction of new facts from subproperty relationships Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  16. 16. cie nt for (S) s uffi tat ion Is R DF pre sen ge Re b? o wl ed ntic We Kn ma Se ? - SPARQL in the 08 How to query RDF(S) Open HPI - Course: SemanticHarald Sack, Hasso-Plattner-Institut, Universität Potsdam Semantic Web Technologies , Dr. Web Technologies - Lecture 2: Semantic Web Basic Architecture I
  • KhalilBouramtane

    Nov. 17, 2019
  • musebrarian

    Feb. 10, 2013

Views

Total views

1,161

On Slideshare

0

From embeds

0

Number of embeds

2

Actions

Downloads

172

Shares

0

Comments

0

Likes

2

×