EXPERIENCES FROM DISTRIBUTED REGISTERING OF METADATA IN METAPLUS

EXPERIENCES FROM DISTRIBUTED REGISTERING OF METADATA IN METAPLUS Klas Blomqvist and Lars-Göran Lundell Statistics Sweden

Agenda • Background – The metadata system – Organisational impact – Reorganisation • Experiences • Future plans

Statistics Sweden’s metadata system • SCBDOK • Description of the statistics • Meta. Plus Metadata repository Description of the statistics Quality Declaration SCBDOK KDB Meta. Plus

Organisational impact • Decentralised organisation – Strong subject matter departments – Functional departments • Decentralised registration of metadata – Central support and coordination (R&D dept. ) – Central dissemination (Info dept. )

Organisational impact • New organisation – The Process Department – The Research and Development Department – The Communication Department – Classifications, metadata and content harmonisation (KMI)

Re-organising Statistics Sweden • Standardised production and tools – – – Process orientation Customer focus Efficiency Standardisation Quality control

Meta. Plus - Contents • • • Standard variables Variables Object classes Classifications and value domains Registers created and used Population

Meta. Plus current functionality, some examples • Documentation • Longitudinal registers • Reuse • Time series • Harmonisation • Historical information • Classifications • Administration • Variable groups • Advanced search • Personal Data Act Administration System • Web interface • Archiving

Meta. Plus - Model Register Object class Variable Conceptual value domain Register variant Population Object variable Value domain Register version Context Population Context variable Value

Registering metadata with Meta. Plus • Organisational issues for registering metadata – Decentralised organisation – Stovepipe production model – Documentation is a burden • The KMI Group • Networks

The KMI Group • Governance and development of the metadata system – Implementation and maintenance of Meta. Plus – User training, helpdesk and support – Presentation on the web • Harmonisation – Classifications and classification related methods – Contents within the metadata systems

The documentation network • All departments represented • ”Standard” • PCA – Supplying methodology resources • Bridge between central knowledge and subject matter expertise

Graphical view KOM WWW. SCB. SE Dept. A Dept. B PCA KMI

Contents Harmonisation • History: The Metadok system • A constant demand • Lack of understanding from users • Stepwise approach 1. Classify contents • Statistical, Administrative and General variables 2. Remove duplicates 3. Subject matter control

Statistics and evaluation • The Management – Monitors overall progress – Follows up and takes relevant actions • The KMI Group – Follows up and evaluates the detailed contents of the Meta. Plus database – Reports to Management

Experiences from working with Meta. Plus • Disadvantages of the decentralised mode: – Central control is more difficult – Coordination and harmonisation of contents is more difficult – Registration of documentation is not always prioritised locally

Experiences from working with Meta. Plus • Advantages of using a decentralised mode: – Relatively sparse and efficient use of central resources – Enforces knowledgeable participation from the subject matter specialists – Possibility to join the metadata system with other systems

Meta. Plus and archiving • Long-term archiving – Data sent to the National Archives • Dedicated archiving system – Creates archive files in required format – Converts archive files to database tables – Uses Meta. Plus information • Metadata from Meta. Plus and SCBDOK is a required part of the archived material

Future plans • Web presentation of metadata based on the Meta. Plus database – First version to be launched later this year – Documentation (variables, micro registers, statistical units, populations, etc) – Classifications • Meta. Plus used by other Swedish providers of statistics

Future plans • Planned additions – Web presentation will include links between metadata on micro and macro levels – End-user tool for metadata driven production of tables – Expanded classification database

Use in the life cycle