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

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Presentation on theme: "Tips for Building an Effective Model for DDI Dan Gillman US Bureau of Labor Statistics."— Presentation transcript:

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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