Statistical Metadata Statistical Metadata Extensions to the X3.285 Extensions to the X3.285

MetamodelMetamodel

By

Daniel W. GillmanChairman, NCITS/L8

U.S. Bureau of the Census

IntroductionIntroduction

Context– Need– Definitions– Census Bureau– Uses for Statistical Metadata

Extensions Conclusion

ContextContext

Metadata– “Data about Data”– “One Person’s Metadata Is Another’s Data”

Context Statistics

Statistical DataStatistical Data

Microdata– Data about individual objects collected through

a survey or experiment.

Macrodata– Data derived through statistical aggregation or

other manipulation from microdata or other macrodata.

Statistical MetadataStatistical Metadata

Descriptive information or documentation that facilitates sharing and understanding statistical data over the lifetime of the data.

Includes– file location, record layout, database schemas, data

dictionary, definitions, questions, questionnaires, sample design, processing steps, data quality, etc.

Census Bureau Metadata Census Bureau Metadata ObjectivesObjectives

Gain Acceptance of One Logical Metadata Registry Model

Support wide Range of Projects, Surveys, Applications, and Users

Comply with Federal Standards

Purposes of a Statistical Purposes of a Statistical Metadata RepositoryMetadata Repository

End-user oriented– Electronic Data Dissemination

Production oriented– Automated Survey Design and Processing

Functions of the CMRFunctions of the CMR

Locate Data Sets Link Common Data Sets Locate Information About Data

Elements Locate Documentation Link Common Documents Link Images

Repository Model OverviewRepository Model Overview

Registration

Metamodel

BusinessData

Documen-tation

DataElement

Survey Survey Instance

Data Sets

Questionnaire

Questions

Products

Sample

Universe/Frame

Business Data ModelBusiness Data Model

Administered Component

Classification Scheme

Common Attributes

Objects ...

Registration ModelRegistration Model

Administered Component

Documentation

Documentation Type

Documentation ModelDocumentation Model

ConclusionConclusion