Do it on your own - From 3 to 5 Star Linked Open Data with RMLio
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The document discusses generating high quality Linked Open Data using the RDF Mapping Language (RML). RML allows for the uniform and declarative generation of RDF from heterogeneous data sources through mapping rules. It supports assessing mapping quality to identify issues before data is generated. Metadata can also be automatically generated from the mappings. The document emphasizes that non-technical data specialists should be able to easily edit the mappings over time.
Do it on your own - From 3 to 5 Star Linked Open Data with RMLio
- 1. RML.io Generating High Quality Linked Open Data from Open or Not Data Anastasia Dimou Data Science Lab, Ghent University - iMinds anastasia.dimou@ugent.be @natadimou
- 2. What is the Semantic Web?
- 3. The Semantic Web is the extension of the World Wide Web
- 4. Are you the owner of your data? OR is the application that hosts your data?
- 5. The Semantic Web is the extension of the World Wide Web enables sharing content beyond the boundaries of applications & websites
- 6. The Web for humans, thanks to HTML, is understandable & constant BUT is the Web for machines too?
- 7. The Semantic Web is the extension of the World Wide Web enables sharing content beyond the boundaries of applications & websites allows machines to understand the meaning of hyperlinked information
- 8. Semantic Web enabled applications rely on data represented as Linked Data
- 9. What is Linked (Open) Data?
- 10. Linked (Open) Data a standardized way of expressing the relationships between data semantically annotated the data with different vocabularies or ontologies describe domain-level knowledge understandable by humans & machines
- 11. How is Linked Data published?
- 12. Linked (Open) Data published in the form of RDF datasets
- 13. Resource Description Framework (RDF) is the prevalent data model for describing Linked (Open) Data driven by unique identifiers (URIs) allows establishing a shared meaning predicate subject object
- 14. How is Linked Data derived from (semi-)structured data?
- 15. How is Linked Data derived from (semi-)structured data? id firstname lastname lab city 1 Anastasia Dimou DSLab Ghent 2 Ruben Verborgh DSLab Ghent 3 Erik Mannens DSLab Ghent
- 16. Person 1 Data Science Labworks “Anastasia Dimou” locatedDataScience Lab Ghent Person 2 Data Science Labworks “Ruben Verborgh” Person 3 DataScience Labworks “Erik Mannens”
- 17. Person {id} {lab} Assign unique identifiers (URIs) “{firstname} {surname}” http:://ex. com{id} http://ex.com {lab} “{firstname} {surname}”
- 18. Annotate data relationships with ontologies http:://ex. com{id} http://ex.com {lab} “{firstname} {surname}” http:://ex. com{id} http://ex.com {lab} “{firstname} {surname}”
- 19. ex:1 ex:DSLabex:works “Anastasia Dimou” ex:locatedex:DSLab ex:Ghent ex:2 ex:DSLabex:works “Ruben Verborgh” ex:3 ex:DSLabex:works “Erik Mannens”
- 20. ex:{id} ex:{lab} ex:located ex:{lab} ex:{city} sets of triples of a dataset have repetitive patterns “{firstname} {surname}”
- 21. ex:{id} ex:{lab} sets of triples of a dataset have repetitive patterns “{firstname} {surname}” RDF dataset generation tools rely their implementation on repetitively applying those patterns to input data ex:located ex:{lab} ex:{city}
- 22. What are the different Linked Data Generation approaches?
- 23. Linked Data generation approaches case-specific solutions OR format and source specific
- 24. R2RML mappings R2RML processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF RDF RDF
- 25. RDF Terms (focusing on IRIs) are… generated independently disregarding their possible prior definitions manually replicated by reconstructing the same URIs (if possible) manually aligned afterwards links with other datasets are defined after the RDF terms are published
- 26. Why not a uniform approach?
- 27. Uniform and declarative RDF generation from heterogeneous data sources mappings processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF
- 28. RDF Mapping Language (RML) generic scalable mapping language for generating and interlinking RDF data from heterogeneous resources in an integrable and interoperable fashion superset of the W3C standardized R2RML mapping language http://rml.io
- 29. Uniform and declarative RDF generation from heterogeneous data sources RML mappings processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF
- 30. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 31. Defining Mappings to generate RDF data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 32. RML describes how to generated RDF from structured data predicate subject object Predicate MapSubject Map Object Map <#TriplesMap>
- 33. rr:constant ex:located rr:template “http://ex.com/{lab}” rr:template “http://ex.com/{city}” rr:template “http://ex.com/{id}” rr:template “http://ex.com/{lab}” <#ResearcherMap> <#LabMap> rr:template “{firstname} {surname}” rr:termType rr:Literal RDF Mapping Language (RML)
- 34. Extraction Module Mapping Module RML Processor
- 35. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 36. Triples Map RDF Mapping Language (RML) Predicate Object Map Subject Map Predicate Map Object Map
- 37. RML describes rules to map any structured data to RDF RML supports any data independently of which structure and format they have where they originally reside how they are accessed & retrieved
- 38. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
- 39. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
- 40. Triples Map RDF Mapping Language (RML) Predicate Object Map Subject Map Predicate Map Object Map Logical Source
- 41. Support data in Heterogeneous Structures and Formats tabular-structured tables in DBs or CSV files … hierarchical-structured JSON or XML … (semi-)structured HTML … … … …
- 42. rr:template “http://ex.com/{id}” rr:template “http://ex.com/{lab}” <#ResearcherMap> rr:template “{firstname} {surname}” rr:termType rr:Literal id firstname surname lab 1 Anastasia Dimou DSLab 2 Ruben Verborgh DSLab 3 Erik Mannens DSLab tabular-structured data
- 43. rr:constant ex:located rr:template “http://ex.com/ {/labs/lab/short}” rr:template “http://ex.com/ {/labs/lab/location/city}” <#LabMap> <labs> <lab> <short>MMLab</short> <title>Multimedia Lab</title> <location> <city>Ghent</city> </location> </lab> <lab> …. </lab> … </labs> hierarchical-structured data
- 44. Triples Map RDF Mapping Language (RML) Predicate Object Map Subject Map Predicate Map Object Map Logical Source Reference Formulation
- 45. <labs> <lab> <short>MMLab</short> <title>Multimedia Lab</title> <location> <city>Ghent</city> </location> </lab> <lab> …. </lab> … </labs> <#Lab Logical Source> ql:XPath rr:constant ex:located rr:template “http://ex.com/ {/labs/lab/short}” rr:template “http://ex.com/ {/labs/lab/location/city}” <#LabMap>
- 46. Triples Map RDF Mapping Language (RML) Predicate Object Map Subject Map Predicate Map Object Map Logical Source Reference Formulation iterator
- 47. <labs> <lab> <short>MMLab</short> <title>Multimedia Lab</title> <location> <city>Ghent</city> </location> </lab> <lab> …. </lab> … </labs> <#Lab Logical Source> ql:XPath “/labs/lab” rr:constant ex:located rr:template “http://ex.com/ {/labs/lab/short}” rr:template “http://ex.com/ {/labs/lab/location/city}” <#LabMap>
- 48. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
- 51. Support different Locations and Access Interfaces Local File(s) Database connectivity D2RQ Web source(s) (Web API/service) DCAT, CSVW, Hydra, VOiD (Dataset) RDF source(s) VOiD (Endpoint), SPARQL-SD
- 52. Triples Map RDF Mapping Language (RML) Predicate Object Map Subject Map Predicate Map Object Map Logical Source Reference Formulation iterator Source
- 54. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 56. dbo:birthDate range xsd:date dbo:birthDate domain dbo:Person http://example.com/ Chuck_Bednarik dbo:Event "1925-05-01" xsd:gYear dbo:birthDate
- 57. Violations Most frequent violations are related to how vocabularies or ontologies are applied to the data dbo:birthDate range xsd:date dbo:birthDate domain dbo:Person http://example.com/ Chuck_Bednarik dbo:Event "1925-05-01" xsd:gYear dbo:birthDate
- 58. RDF DQA with RDFUnit test-driven data-debugging framework based on SPARQL-patterns dbo:birthDate http://example.com/ Chuck_Bednarik dbo:Event "1925-05-01" xsd:gYear http://rdfunit.aksw.org
- 59. DQA: Dataset Quality Assessment Adjustments to the dataset are manually but rarely applied but not at the root (hard to identify) are overwritten if a new version of the original data is mapped & published violations DQA
- 60. Instead of applying Quality Assessment to the already published RDF dataset as part of data consumption Apply Quality Assessment to the Mappings that generate the RDF dataset
- 61. MQA: Mapping Quality Assessment discover violations before they are even generated specify the origin of the violation easily apply structural adjustments to the mappings
- 62. sets of triples of a dataset have repetitive patterns dbo:birthDatehttp://example.com/ {Name}_{Surname} dbo:Event “Birth" xsd:gYear Mapping languages formalize patterns into rules to generate the RDF dataset from the original data
- 63. MQA with RDFUnit over RML dbo:birthDate http://example.com/ Chuck_Bednarik dbo:Person "1925-05-01" xsd:date DEL: <#ObjectMap> rr:datatype xsd:gYear ADD: <#ObjectMap> rr:datatype xsd:date
- 64. data map doc Mapping Processor violations MDQA MDQA: Uniform Mapping & Dataset Quality Assessment
- 65. Dataset Vs Mapping Quality Assessment Dataset Quality Assessment Mapping Quality Assessment size time size time DBPedia EN 62M 16h 115K 11s DBPedia NL 21M 1.5h 53K 6s DBpedia all 511K 32s * http://mappings.dbpedia.org/validation Live update of DBpedia Mapping Quality Assessment results every night!
- 66. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 67. Metadata manually defined by data publishers (person-agents), rather than produced by applications (software-agents)
- 68. Consider mapping rules to automatically generate self-descriptive provenance and other metadata
- 69. W3C standardized Metadata PROV provenance information VoID expressing RDF dataset metadata general metadata structural metadata, links between datasets DCAT describe datasets in data catalogs
- 70. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 71. Semantic Web experts Vs. Data specialists Modeling Domain Knowledge as Linked (Open) Data is not straightforward for Data Specialists Data context is not straightforward for Semantic Web experts
- 72. Semantic Web experts Vs. Data specialists Data Specialists should be able to specify the mappings, modify and extend them at any time
- 73. Approaches for Editing Mappings
- 78. Defining Mappings to generate Linked Data Retrieving Input Data Assessing Quality Generating Metadata Editing Mappings
- 79. The five stars of the Linked Open Data scheme should not be approached as a set of consecutive steps
- 80. Well-considered policy regarding mapping and interlinking of data in the context of a certain knowledge domain
- 81. RML.io Generating High Quality Linked Open Data from Open or Not Data Anastasia Dimou Data Science Lab, Ghent University - iMinds anastasia.dimou@ugent.be @natadimou