Semantic Web Technology Stack - World Wide Web Consortium

Semantic Web Technology Stack - World Wide Web Consortium

Information Architecture 04-3-2018 ECP Metadata Registry 2 ECP Metadata Registry - Introduction What? Create a system to catalogue and describe content in ECP Implemented in RDF with an extensible ontology for content description Support provenance and rights management across the platform using industry standards Why?

Better content discoverability Lower barrier to entry, with different levels of buy-in More flexible in the types of technology it supports Quicker creation and distribution of new bundles of content for product managers

??? Time to market for products How? 3 Ontology created with industry standards Extensible e.g. CMP and CDF

SHACL constraints to enforce data quality & minimum thresholds Work with governance to establish standards and procedures Semantic Web Technologies Overview ECP Metadata Registry Registry Ontology 4 ECP Metadata Registry Logical Model and various distributions

5 ECP Metadata Registry simplified example :Distribution :Dataset rdfs:subClassOf rdf:type Exchange data feed :TabularDistribution rdfs:subClassOf :KafkaDistribution

rdfs:label rdf:type ecp:1-123456 rdf:type :hasDataset ecp:2-3456789 :hasDataset ecp:2-234567 :contains :contains

INSTTYP :hasHBaseColumnName :expresses ecp:5-123456 rdf:type rdfs:label ecp:8-947563 rdf:type Instrument Type

:Property 6 Semantic Web Technologies Overview :HBaseColumn Knowledge graph 7 Semantic Web Technologies Overview TR Knowledge Graph - Standards, Structure, Integration Based on industry standards ( RDF, SHACL)

to organize and represent information Structured data for objects and their relationships Automatic Integration and discovery of previously undetected relationships 8 TR Knowledge Graph RDFized DBORs RDF can be an extra layer on all DBORs Not all DBORs are covered Priority must be given to master DBORs (Instruments, PA ) to enable integration ?

? ? 9 TR Knowledge Graph Use Cases Bold Framework Graph Feeds from TR Graph Data Eikon Seach & Discovery Introducing graph search capability to surface news stories about companies or lists that the user has searched on but arent directly mentioned Resource for AI machine learning, NLP, intelligent tagging

DBORs may generate RDF versions of their content Integration of data from all DBORs Webification Web of Data 10 TR Knowledge Gragh Integrate Data from DBORs 11 SHACL W3C Data Modelling Language 12 Data Quality SHACL Constraints

Our TR models define also constraints, shapes on the data Data can be checked on these constraints and creates violation messages Example of a Violation:A quote is active and has exchanges but the instrument itself is inactive . 13 We can create our own messages Create new information - SHACL RULES Creates new information based on conditions Waves of rules with ordering to produce intermediate and target information example:Organization

rdf:type owl:Class ; rdf:type sh:NodeShape ; sh:rule [ rdf:type sh:TripleRule ; sh:condition [ sh:property [ sh:path example:Domicile ; sh:in ( example:EEAMeberCountry ]; ]; sh:predicate rdf:type ; sh:object example:MIFIDOrganization ; sh:subject sh:this ; ]; .

14 Example: If an organization is domiciled in a EEA Country ); then classify it as an MIFIDOrganization

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