Statistics Portugal/ Metadata Unit

Monica Isfan (monica.isfan@ine.pt)«

Joint UNECE/ EUROSTAT/ OECD

Work Session on Statistical Metadata (METIS)

11 –13 March 2009

Variables Subsystem

Variables subsystem

Relationship with other systems

Search and management applications

Statistical indicators

Normalization and harmonization

Benefits

Overview

Variables Subsystem

Variables Subsystem

ISO/ IEC 11179 + IDMB Statistics Canada

Statistical Survey Design

Automatic Questionnaire Generations

Statistical Dissemination

Facilitate Standardization

Identify Duplicates

Facilitate Data Sharing

Variables Subsystem

Production System

Dissemination System

Variable subsystem

Variables Subsystem

Family/ Theme

Conceptual Variable

Variable

Statistical Indicator

Object Class

Value Domain

Unit of Measure

Property

Representation Class

Variables Subsystem

Property

Object class (population or statistical unit)

Representation class

Value domain

Variables

Statistical indicators

Variables Subsystem

defined

Variables Subsystem

Personal informationFilter 1

All persons of the household

Variables Subsystem

Labour force questionnaire/ personnel data (persons - members of the household)

Property

Object class Representation class

Value domain

Variables Subsystem

Property

Marital status

Object Class

PersonRepresentation class

CodeValue domain

Enumerated (classification + level of classification)

Concept “Marital status”- 174

A person's legal situation consisting of the qualities defining his or her personal status in terms of family relations figuring in the register. It comprises the following situations: a) single, b) married, c) widow(er), d) divorced.

No concept

Level Code Name

1 1 Single

1 2 Married or cohabiting

1 3 Widowed

1 4 Divorced or separated

Marital status_Person_Code_Table of marital status/ level 1

Variables Subsystem

Formal name not user friendly;

Formal name very long;

Variables must supply both production systems and dissemination systems;

Variables effectively searchable;

External name General Rule: Property + (Qualifier term) + Object Class

Example: Marital status of person

Legal reserves (€) of enterprise

Abbreviate nameGeneral Rule: Property + (Qualifier term)

Example: Marital status

Legal reserves (€)

Qualifier term: A word or words which help define and differentiate a name within the database

Variables Subsystem

Conceptual variables

Variables Subsystem

Relationship with other systems

Concepts Subsystem

Bidirectional View

Concepts

Value domain of variable

Variables Subsystem

Relationship with other systems

Classification Subsystem

Bidirectional Views

Version (level)

Bidirectional ViewsBidirection

al ViewsBidirectional Views

Variables

Variables Subsystem

Relationship with other systems

Methodological Documents Subsystem

Version

Variables

Variables Subsystem

Relationship with other systems

Data Collection Instruments Subsystem

Questionnaire

Variables

Variables Subsystem

Relationship with other systems

Questionnaire

Data base

Question

Observation: Not yet developed

Statistical indicators

Variables Subsystem

Relationship with other systems

Dissemination

Data base

Statistical indicators

view

Search and management application

Search application

Management application

Statistical Indicators

Data element that represents statistical data for a specified time, place, and other characteristics.

(“Terminology on Statistical Metadata, Conference of European Statisticians – Statistical Standards and Studies – Nº 53”).

Statistical Indicator

Variables subsystem

Statistical indicator

defined

Variables

Aggregate Variables

Dimensions

+

D1 = Time

D2 = Geography

…….

Dn = Other characteristics

Statistical Indicators

Statistical Indicators

Aggregate variable

D2 = Dimension (geography)

Dn = Other dimensions

,

by

and

…,

Dn-1 = Other dimensions

Name definition

Sex

Statistical Indicators

Aggregate variable

Dimension (geography)

Other dimensions

Resident population

Place of residence

,

by

andAge

group

Statistical Indicators

Step 1. Analyse of data and metadata

Step 2. Variables and statistical indicators proposal

Step 3. Register and approval of variables

Step 4. Register and approval of statistical indicators

Step 5. Transmission of metadata and data

Variables Subsystem

Statistical Indicators

(view)

Metadata

DataWarehouse

Data Base

Statistical Indicators DB

Metadata

Data

Data

Internet

Statistical Indicators

Why ?????

1. Sex:

Masculine………1

Feminine………..2

2. Gender:

……………………….

3. Sex of person:

Male………….1

Female………2

Normalization and harmonization

Normalization and harmonization

“A theory is more impressive the greater is the simplicity of its premises, the more different are the things it relates, and the more extended its range of applicability…” Albert Einstein

Basic steps:

Conceptual analysis;

Normalization;

Harmonization.

Normalization and harmonization

Selection of variables;

Identification and documentation of potential incompatibilities;

Compiling the existent documentation, determining variables availability and use;

Classification in chapters by main concept;

Preparation of the proposed variable;

Documentation for the future normalization scheme, etc .

Conceptual analyses

The normalization process consists in: If the variable is already registered in the Variables System, it is

equivalent to be normalized and ready to harmonization (if it’s the case).

If the variable is not in the Variables System, then we most follow:

Normalization and harmonization

1. Comparison of proposed variable with the normalized variables

2. Definition of all basic attributes of variables

3. Definition of formal, external and short names for variables

4. Process of registry, verification and approval

Harmonization

Reinforce the contextual study of variables

Production System (Methodological Documentation, Questionnaires, Administrative Sources, etc);

Dissemination System;

Data Warehouse.

Use/ reuse of the same variable in different contexts

Normalization and harmonization

Harmonization Proposal

Consulting Group (Production Division, Dissemination Unit and Methodological Unit).

Preferred variable for use in data interchange and in new or updated applications.

Normalization and harmonization

Chapter Statistical area of use:

Main Concept or Main Definition:

Observations:

Filter:

Statistical Unit:

Classification:

Normalized variables registered in Variables System proposed for harmonization

Coding process:

Questionnaire:

Example of a questionnaire module which meets the requirements documented in this proposal.

Operational issue:

Dissemination requirements:

Good practices:

Normalization and harmonization

Benefits

Increased chances of sharing data and metadata with other agencies;

Single point of reference for data harmonization; Reduce redundancies and anomalies; Central reference for survey re-engineering and re-

design; Reduce ongoing production costs; Reduce statistical burdens; Improvement of quality and understandability of

disseminated data

Thank you for your attention

Variables Subsystem