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Tips for Building an Effective Model for DDI

Tips for Building an Effective Model for DDI. Dan Gillman US Bureau of Labor Statistics. Modeling Paradigms. Entity-Relationship (ER) Older Used to design RDBs Looser rules IDEF1x Based on ER and RDBs Tight rules ISO/IEC 31320-2 Not bound to software development. Modeling Paradigms.

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Tips for Building an Effective Model for DDI

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  1. Tips for Building an Effective Model for DDI Dan Gillman US Bureau of Labor Statistics

  2. Modeling Paradigms • Entity-Relationship (ER) • Older • Used to design RDBs • Looser rules • IDEF1x • Based on ER and RDBs • Tight rules • ISO/IEC 31320-2 • Not bound to software development

  3. Modeling Paradigms • Unified Modeling Language (UML) • Based on OOD and OOA • ISO/IEC 19501 • Based on MOF • Tight Rules • Bound to Programming Languages (Java, C++, etc) • Major support by other specs • Interchange models through XMI

  4. Modeling Paradigms • Object-Role Modeling (ORM) • Based on NIAM (built in 1980s) • Purely Conceptual Modeling • Fact-Based Modeling • Diagrams to be read as series of statements • Similar to RDF • Graph like structure • Separates Concepts and Objects • Not so much for system design • Best for understanding

  5. Current Situation • XML-Schema • Modeling language as well • Designed to be human readable • Not so easy • Very verbose • Relationships • not naturally supported • Overall design not easily illustrated • Limits implementation types

  6. Current Situation • Current DDI • Much good work • Good statistical understanding • Life-cycle support • Data set support • Shouldn’t be lost • But not the only game in town

  7. GSIM • Generic Statistical Information Model • Version 1.0 due in Dec 2012 • Version 0.8 out for review until 19 October • Companion Model to • Generic Statistical Business Process Model • GSBPM • GSIM – data model • GSBPM – process model

  8. GSIM • Detailed model for • Variables, Data, Classifications • Data sets • Processes and Activities • Full support for life-cycle

  9. DDI/ SDI • Survey Design and Implementation WG • Questionnaire design • Frame and Sample description • Weighting • Paradata

  10. Design Criteria • Terminology (Concepts and related things) • Methodology • Statistics and Probability • Cognitive psychology • Computer science • Computation (IT resources) • Normative specifications • Rationales • Specifications • Procedures

  11. Level of Detail • Multiple views • Conceptual layer • Managers • High level view • Communication layer • More detail • Still conceptual • Specification layer • Implementation and interoperability • Detailed metadata

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