metaplus klas blomqvist statistics sweden research and development – central methods...
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MetaPlusKlas Blomqvist
Statistics SwedenResearch and Development – Central Methods
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!