Terminology and Standards

Dan GillmanUS Bureau of Labor Statistics

Terminology

Principle – To communicate, we need to agree on

terms Concept –

– unit of thought

Term – – linguistic expression (similar to a word)

linked to a concept

Special Language –– set of terms describing a subject field

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Terminology

Examples of special languages Probability and statistics Database theory Statistical metadata Statistical activity within each SI

– E.g., US Current Population Survey• Labor force• Unemployed

Union of special languages within SI

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Projects

UNECE Metadata Glossary Glossary (a.k.a. Vocabulary) –

– Alphabetical listing of terms and their definitions

BLS Taxonomy and Lexicon Taxonomy (artefact, not the science) –

– Scheme for organizing terms within some subject field, typically a hierarchy

Lexicon –– Vocabulary, or dictionary, of terms

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UNECE Metadata Glossary

Create glossary of terms In order of importance

– UNECE statistical metadata standards• GSIM, GSBPM, GAMSO, CSPA, etc.

– Other statistical metadata standards• DDI, SDMX, etc.

– Other standards and specifications• Maybe ISO/IEC 11179, Dublin Core, etc.

Disseminate in user-friendly format

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UNECE Metadata Glossary

Build special language for Statistical institutes

– Designing metadata systems– Building interfaces to metadata systems– Message frameworks for sharing

metadata

Establish authoritative source Terms Definitions For international use

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BLS Taxonomy and Lexicon

Project to Record terms describing BLS data

– For all disseminated time series– Separate terms into facets• Measures (estimates on populations)• Characteristics (classifications used to subset

measures)

Produce– Taxonomy – hierarchy of terms– Lexicon – list of terms

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BLS Taxonomy and Lexicon

Goals For each term, find related documents

and data– organize data – use taxonomy– tag documents – use lexicon

Use taxonomy to drive and guide– Web site reorganization

Provide plain English equivalent words– Help unsophisticated users find resources– Alleviate common confusions 8

BLS Taxonomy and Lexicon

Plain English examples Inflation – CPI Field of work – industry or occupation Wages, earnings, income,

compensation Plain English names for categories Authoritative source for BLS

language

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Usage of Terms

Metadata models Names of classes, attributes,

relationships E.g., Universe, Category,

Specialization Metadata content

Content stored in attributes in a model E.g., establishment, retail grocery

store, etc. Terminology systems

Authoritative sources for terms / meaning

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Standards

Why standards? Consistency

– Eliminate inconsequential (gratuitous) differences• Spelling and phrasing differences

Semantic interoperability– Shared meaning w/o need for negotiation

Data harmonization– Ability to combine data from different

sources

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Standards

Many levels Program, Agency, National, Regional,

International Weaker condition

Authoritative sources– Term and meaning for some subject

field(s)• E.g., unemployed in US CPS• Plain English -> not employed• US CPS -> not employed but still in Labor

Force

– Not necessarily standard12

Standards

Consistency and Interoperability Handled by authoritative sources Use URI’s to terminological entries Spelling and phrasing differences

eliminated Access to meaning ensured

But, Differences across subject fields

remain 13

Standards

Data Harmonization Authoritative sources not sufficient

– Subject fields may differ– Gratuitous differences may exist too

Need new standards and agreements– Bilateral agreements not scalable

Multiple standards on same subject a problem– E.g., Geographical standards (US MSA vs.

CSA)– BLS has 6 definitions of Boston 14

Contact Information

Dan Gillman

gillman.daniel@bls.gov