Implementation Experiences METIS – April 2006 Russell Penlington & Lars Thygesen - OECD v 1.0

OECD’s Statistical Information System Work Flow ProductionStorageDissemination XML Data Production Environments (incl. StatWorks) MetaStore Metadata Production Environment User Interfaces PubStat Publication Management Interface Published Outputs MetaStore is positioned in the production layer of the OECD’s Statistical Information System (SIS) for managing production metadata content OECD.Stat Corporate Data Warehouse Cubes Web Services XML

The Metadata Principles In 2004, OECD adopted a set of corporate principles set out the guidelines “Management of Statistical Metadata at the OECD”: Consistency The same variable name, definition, and other description should be connected to the same statistics Redundancy Metadata on one element (statistical collection, dataflow or concept) should only exist as one instance Commonality All metadata from different subject-matter areas must be grouped under 41 defined metadata type headings Attachment Metadata can be attached at any level of detail of the statistical data Metadata must primarily illuminate the following areas: Concepts, definitions of concepts Delimitation of populations Dimensions of quality, related to the original production

MetaStore and its Features Data Production Environments MS Office Documents Static HTML Web Pages MetaStore Migrate Metadata Data Coordinates Searching Adding Editing Ability to attach Metadata at any level Accessibility and Timeliness of Metadata Management Web Interface for Metadata Management Improving Quality Of Metadata Metadata Attachment Levels, Rich Text Formatting, Standard Classifications Efficiency For Managing Metadata Content Sharing, URL & Glossary References, Versioning Flags Making Metadata More Accessible Web Interface, Remote Application Access Methods, Reporting & Exporting Integration With Production Systems Connectivity to Data Structures, Remote Interaction, Bulk Processing

Governance Principles Local ownership and responsibility: Units responsible for managing the data also responsible for metadata Carrots rather than sticks: MetaStore not mandatory Data providers must be persuaded by attractive features and quality of results Drivers for MetaStore adoption: Metadata management can be more efficient Better quality metadata => reduce support to users Coherence of metadata between different databases Increase visibility on the Internet

Populating MetaStore MetaStore can be updated by two methods: Directly from data production systems (Remote Access) Through a rich editing web based user interface (User Interface) Remote Access – sharing content: 0 = No sharing 1 = Sharing within dataset 2 = Sharing across datasets User Interface – enhanced control: WYSIWYG rich text editor The interface allows text sharing and ownership Data coordinates built into the interface URLs facilitate integration with production systems Migrating metadata from legacy systems: Structured or database metadata: Bulk upload HTML or MS Office metadata: Cleaned by copying into the web interface

Showing Metadata To Users Dataset and Dimension Level Metadata shown when selecting or clicking the dataset or dimension text Single Dimension Members A red "i" is shown in the cell of the dimension member Incomplete Combinations Of Dimension Members An extra column is introduced containing a red "i" when there is a piece of metadata pertaining to all observations in the corresponding row Observation Values (Complete Combinations) A red "i" is shown in the cell of the observation value

Lessons Learnt Drivers to acceptance of MetaStore: Flexibility of design allows minimal initial migration cost Clear communication of efficiency gains and quality benefits Coherence and sufficiency of metadata in the system: Increase in volume and breadth of content (Comprehensiveness) Splitting and attaching content to accurate coordinates (Relevancy) Standardising metadata structure and content reuse (Coherency) Effects on Visibility: Search engines ‘crawl’ and index content by following hyperlinks found in online reference metadata There exists a set of core concepts that serve as significant components in major search engine algorithms MetaStore provides well structured reference metadata reported online in a way for search engines to optimally index it

Future Plans & Summary Stricter rules envisaged in future as migration reaches critical mass: Enforce reuse of exact text within the same dataset Enforce certain combinations of attachment coordinate and metadata type to be completed (e.g. Contact Person at Dataset level) Actions to be taken by dataset owners on metadata quality reviews Summary: The MetaStore metadata management model is a well suited solution for managing reference metadata in a decentralised environment for both national and international statistical organisations The quality of reference metadata can be enhanced by a metadata management system that promotes: Standardisation of metadata structure Sharing of metadata content across domains Flexibility in attaching metadata to data coordinates