MetaPlusKlas Blomqvist

Statistics SwedenResearch and Development – Central Methods

klas.blomqvist@scb.se

Agenda

• The VHS-project– Background

• MetaPlus– The concepts, the product

• KMI-group – Support and management for classifications, metadata and

content harmonisation

• The Lotta project, process reengineering at Statistics Sweden– A more effective production process– MetaPlus, future development

• MetaPlus and the production process

Why do we need metadata?

Why do we need metadata?

Metadata at Statistics Sweden

• SCBDOK– Word template, standardised structure free text description

• MetaPlus (Metadok)– Formalized metadata, coded information

• KDB, the classification database– Statistical standards and classifications

• Other documentation– Description of the statistics – the quality declaration– Product database– Private production documentation

The VHS-project

• The VHS-project started 2004– Compilation of requirements: Metadok, new

requirements

• Systems design from 2005– Use cases, modeling

• System development 2006– Application, data base

• Production 2007– From January 2

MetaPlus

• Replace Metadok

• Scope:– Documentation tool with improved quality– Better overview over variables and data– Tool for standardisation and harmonisation– Possibilities for reuse and coordinated use– Consecutive documentation

• Requirement:– That the documented material in Metadok can be

migrated

Information

• User groups

• The Metadata group (reference group)

• The methods council

• The IT council

• The register council

• The board of directors

• The scientific council

• Seminars

The plus with MetaPlus

• Support for the production– Cooperation with other metadata systems, Archiving, the

Personal Data Act, connection to data

• User support– Search the microdata

• Improved quality– Contents, accessibility and comparability

• More cost-effective– Increased use of collected data

• Reduced respondent burden– No new collection if data already exists

Easier to document

• Starting point in already existing metadata– Classifications and standards– Documentations made by others– Search the metadata repository

• Document once - reuse

• Input data in the form of tables– Document the table at once instead of one cell at a time

• Consecutive documentation

• Effects:– Higher metadata quality– Automatic harmonisation

Using MetaPlus

• New requests (commissions), new surveys– Examine if the issue can be solved with already existing

data.

• Information for facilitating coordinated use and harmonisation

• Search for variables– Look at value domains

• Find information on populations– Shows possibilities for matching data– Highlights differences in data materials

Content

• Standard variables

• Variables

• Object classes

• Classifications and value domains

• The survey’s registers

• Survey population and register population

The model

Object class

Value domain

Context Population

Variable

Population

Context variable

Object variable

Register

Register version

Register variant

Conceptual value

domain

Value

Objectclass

Population

Variable

Valuedomain

Register

Registervariant

Register version

ColumnDatabase/

file

The application structure

Can be reused

Contentoriented

IT-oriented

Unique for the survey

round

MetaPlus functionality, some examples

• Documentation

• Reuse

• Harmonisation

• Administration

• Classifications

• Variable groups

• Personal Data Act Administration System

• Advanced search

• Longitudinal registers

• Time series

• Historical information

• Archiving

• Web prototype

The KMI-group

• Research and Development department, all units represented– Management, Central Methodology, Register coordination

and microdata and Central IT units

• Responsibilities– Classifications– Metadata– Content harmonisation

• MetaPlus support– Migration, training, helpdesk

The Lotta project

• Standardised production and tools– Process orientation– Customer focus– Efficiency– Standardisation– Quality control

• New organisation after summer– Internal review during summer

The Statistical Production Process

Target,cust.dem Frame and sample

Data collection

Datapreparation

Statisticalcomputation

Dissemination and

communication

Evaluation/cust.satisf.

Assessment

Survey design

The colours relate to potential areas for process ownership

Customer contacts

Tender/agr.

Technical preparations

Documentationpreparations

Compilationof frame

Sampling

Administrative registers

Direct data collection

Other primary statistics

Coding

Editing

Corrections

Datadelivery

Estimations

Productionof tables anddiagrammes

Statistical analysis

Dissemination

Data dellivery To customers

Archiving

Customerreactions

Analysis of Process data and customer

reactions

Feed-back to the production

process

Identification ofdata sources

Compilationof results

Internalevaluation,

quality control

General for all processes:

Deliveries between processes

Process data Meta data System architect. Keeping of reg.Treatment of Time series

breaks

Prognosis

Simulation models

Cont.,predesign

Level

1

L

e

v

e

l

2

MetaPlus in the Statistical Production Process

Target,cust.dem Frame and sample

Data collection Datapreparation

Statisticalcomputation

Dissemination and communication

Evaluation/cust.satisf.

Cont.,predesign

MetaPlusInternalevaluation,

quality control

General for all processes:

Deliveries between processes

Process data Meta data System architect. Keeping of reg.Treatment of Time series

breaks

Conclusions

• Reuse

• Harmonisation and standardisation tool

• MetaPlus 1.2 in production

• Organization (the KMI-group)

• Content – slow progress

The End!