1 / 25

Integration of Clinical Trial Data Standards Part II – Models and Applications

1. Presented by Frederik Malfait Data Standards Office, PD Biometrics, F. Hoffmann-La Roche IMOS Consulting, Switzerland. Integration of Clinical Trial Data Standards Part II – Models and Applications. 2. Global Data Standards Repository (GDSR) Content Perspective. Content. Model.

fergal
Download Presentation

Integration of Clinical Trial Data Standards Part II – Models and Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 1

  2. Presented by Frederik Malfait Data Standards Office, PD Biometrics, F. Hoffmann-La Roche IMOS Consulting, Switzerland Integration of Clinical Trial Data StandardsPart II – Models and Applications 2

  3. Global Data Standards Repository (GDSR)Content Perspective Content Model Applications

  4. Current Scope From Protocol to Submission • End-to-End datastandards from protocol to submission cover the complete life cycle of clinical research data • Protocol Design • Data Collection • Data Tabulation • Data Analysis • Regulatory Submission • Based on CDISC Industry Standards • Objective • Support consistent definition, management, and processing of clinical research data throughout all stages of the life cycle

  5. Wide Variety of Content Types • CDISC versus sponsor defined standards • Collected versus tabulated versus analysis data structures • Controlled terminology, Lab Metadata, Questionnaires • External references, e.g. NCI Thesaurus • Sources available in Word, Excel, and PDF formats • Administrative metadata, e.g. versioning and life cycle information

  6. Global Data Standards Repository (GDSR)Modeling Perspective Content Model Applications

  7. Modeling Objectives • Develop a meta-model to capture and interconnect • Common Conceptual Domain Model • Data Standard Models • Value Level Metadata • Represent the output of the standardization effort as structured information • Avoid implicit information in documents • Capture this information in an electronic repository called the Global Data Standards Repository (GDSR) • Provide access to the GDSR • As input to other systems for machine consumption • As a knowledge source for human consumption

  8. Modeling Paradigms • Candidate meta-models • UML object-oriented model • Relational meta-data model • Semantic model (aka ontology) • Advantages of semantic models • Easy to federate disparate types of data and meta-data (Linked Data) • Biomedical information is increasingly published in semantic formats • e.g. NCI Thesaurus • Prepare adoption of the CDISC BRIDG model and SHARE repository • Semantic Modeling Standards and Tools • Mature W3C standards (URI, XML, RDF, RDFS, OWL, SPARQL) • Availability of good semantic modeling tools (e.g. TopBraid)

  9. Knowledge as RDF Graphs Directed Graph of Subject - Predicate - Object Triples Subject Predicate Object livesIn Jon Basel age partOf 32 Switzerland

  10. Content and Schema (RDF and RDFS/OWL) Content livesIn partOf Jon Basel Switzerland age 32 rdf:type rdf:type rdf:type Schema partOf livesIn rdfs:range rdfs:range rdfs:domain rdfs:domain Person City Country rdfs:subClassOf rdf:type rdfs:subClassOf rdf:type Location owl:Class Everything is a Triple

  11. Uniform Resource Identifiers • In RDF everything is a triple (content and schema) • A triple is either a <Subject Predicate Object> or a <Subject Predicate Value> • Subjects, predicates, and objects are commonly called RDF resources • Every RDF resource has a unique Uniform Resource Identifier (URI) • Much like every web page has a unique Uniform Resource Locator (URL) • Namespaces provide a convenient way to group related resources together

  12. Examples • Global Data Standards Repository • The resource representing the SDTM domain AE (Adverse Events)http://gdsr.roche.com/cdisc/sdtmig-3-1-2#Table.AE • The prefix sdtmig identifies the namespacehttp://gdsr.roche.com/cdisc/sdtmig-3-1-2# • The qualified name for the same resource sdtmig:Table.AE • Examples from the W3C standards • rdf:type is the qualified name ofhttp://www.w3.org/1999/02/22-rdf-syntax-ns#type • owl:Class is the qualified name ofhttp://www.w3.org/2002/07/owl#Class

  13. Inference • RDFS and OWL provide a set of predicates for schema modeling • e.g. owl:inverseOf relates two inverse properties<hasCitizen owl:inverseOf livesIn> • owl:inverseOf is a W3C defined URIhttp://www.w3.org/2002/07/owl#inverseOf • Its meaning is defined by the way new triples may be derived from existing triples • Stated Triple<Jon livesIn Basel> • Derived Triple<Basel hasCitizen Jon>

  14. W3C Standards for Semantic Models • Resource Description Framework (RDF) • RDF defines how to express a knowledge base (content) as a directed graph of resources (set of triples) • Every resource has a unique URI and is part of a namespace • RDF Schema (RDFS) and Web Ontology Language (OWL) • A set of standard predicates to build vocabularies (schemas) • Inference capabilities • SPARQL Protocol and RDF Query Language (SPARQL) • Language to query an RDF knowledge base • Simple Knowledge Organization System (SKOS) • Small footprint RDF based schema for concept models

  15. Linked Data • Semantic models in RDF format are easy to federate • Federation of Data = Union of Triples (from both graphs) • Use owl:sameAs to specify that two resources are equal Federated Graph http://example.org/geo/# http://example.org/people# livesIn Jon Basel Switzerland age owl:sameAs partOf 32 Basel

  16. Example DBPediadbpedia.org Linked Open Data

  17. Linked Open Data (LOD) and The Cloudlinkeddata.org

  18. Linked Open Data (LOD) and The Cloudlinkeddata.org Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

  19. Roche Global Data Standards Repository (GDSR) Value Level Metadata Data Collection Data Tabulation Data Analysis CDASH SDTM ADaM CDISC Controlled Terminology Biomedical Concepts Meta-Model Schema Concept Schema NCI Thesaurus Metadata Registry Schema (ISO 11179) RDFS OWL SKOS RDF External Sources GDSR Schemas GDSR Translation GDSR Content

  20. Global Data Standards Repository Applications Perspective Content Model Applications

  21. Domain Model Standard Models Transformation Models Metadata Repository Code Generator Executables Protocol Design Data Collection Data Tabulation Data Analysis Regulatory Submission Some Considerations on Architecture

  22. UML Component Diagram

  23. We Innovate Healthcare

More Related