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Federated data stores using semantic web technology
The document discusses the use of semantic web technologies, particularly RDF and OWL, to enhance data interoperability across federated data stores. It outlines the advantages of these technologies, including simple representation as triples, self-describing models, ease of interrogation with SPARQL, and effective validation and interoperability. The author emphasizes that adopting semantic technology can reduce the costs associated with interoperability solutions.
Federated data stores using semantic web technology
- 1. Federated Data Storesusing Semantic Web Technology Steve Ray Distinguished Research Fellow Carnegie Mellon University
- 2. Interoperability is allabout DATA Three Technology Trends that could help* 1. Semantic Web technologies 2. Cloud 3. Natural Language Processing I will focus on semantic web technologies *Inspired by “Top Three Technologies to Tame the Big Data Beast,” Huffington Post, 11/22/2011 Steve Ray, Carnegie Mellon University
- 3. Representation Trends IBM CardFormat EDI XML Metadata Metamodels Meta-meta- models RDF/OWL XML Schema BPML/ BPEL CBA Semantic Mediation Web Services Protocols 40 25 7 6 5 0 2 4 3 1 SOA Legacy Current Practice Exploratory 18 Info Modeling FOL (Slide adapted from Donald Hall, Logistics Enterprise Services Office, DLA) Steve Ray, Carnegie Mellon University
- 4. Why Consider RDF& OWL Semantic Web Technology? RDF = Resource Description Framework OWL = Web Ontology Language 1. Simple representation – Everything is a triple: <subject – predicate – object> 2. Self-describing models – Schemas and data coexist in data stores 3. Easy to interrogate – SPARQL queries (over schema and data) 4. Easy to validate – Supports automated reasoning 5. Easy to interoperate – Natively supports distributed data stores Steve Ray, Carnegie Mellon University
- 5. Simple Representation Everything isstored as triples: <subject predicate object> Steve Ray, Carnegie Mellon University
- 6. Self-Describing Models • Theschema (model) and the data is stored in the same place • Schema: – Mammal subClassOf Animal – Human subClassOf Mammal • Data: – george is-a Human – george marriedTo lisa Steve Ray, Carnegie Mellon University
- 7. Easy to Interrogate SPARQL † languageto query an RDF database (Just matches against patterns of triples) SELECT ?x WHERE { george marriedTo ?x . } Returns a table: x lisa SELECT ?y WHERE { y? subClassOf Animal . } Returns a table: y Mammal † SPARQL = SPARQL Protocol and RDF Query LanguageSteve Ray, Carnegie Mellon University
- 8. Easy to Validate SPARQLcan be used for reasoning, not just interrogating In SPARQL: If George sonOf Fred and Fred siblingOf Mary Then George nephewOf Mary CONSTRUCT { ?a nephewOf ?c .} WHERE { ?a sonOf ?b ; ?b siblingOf ?c . } Steve Ray, Carnegie Mellon University
- 9. Easy to Interoperate •A single query can interact with more than one RDF database – Linked Movie Database contains movies, actors – DBPedia contains people and birthdates • Find the birthdates of all Star Trek actors – Answer does not exist in one source
- 10. Dbpedia is justone of many RDF data stores on the Web We are not alone
- 11. Implications • OWL/RDF providesa representation that can natively support transformations from other modeling languages and native formats for product and process models • The API is SPARQL • Storage can be local or web-based Steve Ray, Carnegie Mellon University
- 12. Take-away • Poor interoperabilityis expensive • Interoperability solutions can be expensive • Semantic technology can make interoperability solutions easier and cheaper to implement Steve Ray, Carnegie Mellon University