Transcript Metadata-driven Business Process in the Australian Bureau of Statistics Aurito Rivera, Simon Wall, Michael Glasson – 8 May 2013

Metadata-driven Business Process
in the
Australian Bureau of Statistics
Aurito Rivera, Simon Wall, Michael Glasson – 8 May 2013
Content
1. Why have it?
2. What is meant by metadata-driven business
process?
3. What is the ABS doing?
•
Two case studies
4. Implications for metadata management
5. Key messages
Why have metadata driven business process
• ABS perspective - the business benefits include
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Reduced time and cost of statistics production
Improved quality of statistical products
Increased agility in meeting new demands for statistical products
and services.
Increased agility in harnessing new sources of statistical data.
• Industry perspective - directly supports the HLG’s approach to
industrialising and standardising statistics production.
What is metadata-driven business process
In the ABS, it is the systematic and consistent
use of metadata to determine the inputs, outputs
and behaviour of a statistical business process.
What is metadata-driven business process
Key characteristics
1.
Metadata is used systematically
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2.
Metadata is used consistently
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3.
Metadata is used in a planned and managed way across the
organisation.
Authoritative ‘single source of truth’ metadata is used throughout the endto-end lifecycle of an activity and/or across activities.
Metadata is used actively
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Metadata is used to automate the definition and execution of statistical
processes
Metadata is structured so as to be machine-consumable.
What is metadata driven business process
Necessary components for ABS implementation:
1.
GSIM/DDI/SDMX-based metadata
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2.
Libraries of business processes, methods and IT components
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3.
that serves as or identifies inputs to and outputs from processes
standardised and discoverable via a metadata registry
analogous to ‘blood that flows through vital organs’.
that can be assembled in a ‘plug and play’ way
that are atomic or are complex processes that are assembled from atomic
process components
Effective governance framework
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to ensure the appropriate specification and use of contents
that dictate what and how metadata is used in what processes.
What the ABS is doing in this area
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Examples of earlier work:
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2002 – Business Statistics Innovation Program (BSIP)
2003 – development of ABS strategy for e-2-e management of
metadata
2009 – formal adoption of SDMX and DDI Standards
2010 – Information Management Transformation Program (IMTP).
Examples of more recent work (under the ABS 2017 Program):
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Metadata Registry and Repository (MRR), Statistical Workflow
Management systems (SWM)
Online Forms Prototype Project (eForms)
Enterprise Data Warehouse (EDW).
Case study 1 – MRR/SWM
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Two Core applications that will form the ‘central nervous system’
of future ABS metadata management infrastructure.
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MRR/SWM are intended to guide and quicken the work of
Statistics Producers as well improve metadata management.
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MRR/SWM in themselves are not sufficient to realise the
business benefits.
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Also need Business Process re-engineering, instilling Information
Management governance, etc.
Case study 1 – MRR/SWM
• Components
• MRR is a store of statistical metadata that is authoritative,
centralised, and standards based
• Repository – logically centralised store
• Registry – metadata catalogue and data directory.
• SWM helps to assemble business processes from a library of
re-useable building blocks
• SWM helps to automate and manage the execution of these
business processes.
• SWM in concert with MRR will:
• Guide and quicken the work of Statistic Producers
• Greatly improve the way we manage metadata.
Case study 1 – MRR/SWM
E.g. Register metadata
Repository
Complete metadata
package resides in
Repository
Registry
Register key elements
of metadata package
Case study 1 – MRR/SWM
E.g. Metadata search
Repository
Search for metadata here
Registry
?
1.
2.
3.
Returns a list of matches
based on search criteria
Match1
Match2
Match3
Case study 1 – MRR/SWM
E.g. Retrieve metadata based on
search results
Registry
]
Repository
Case study 1 – MRR/SWM
• Proof of Concept undertaken in 2011/2012
• Lessons learnt from POC
• Concepts and technologies employed are sound
• Automation of business processes feasible.
• First production version due December 2013
Case study 2 – eForms
• Prototype web-based collection tool
• Forms the basis for ABS capability for building and deploying
web-based collection tool.
• Test the feasibility of using
• DDI 3.1 Instrument specification,
• Strategic ABS technologies,
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especially SWM/MRR
• GSBPM-aligned processes.
Case study 2 – eForms
Components
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Web Instrument
Production
Application
MRR
SWM
ABS Collections
Electronic System
(ACES)
DDI to ACES
Transformer Service.
Brief case study 2 – eForms
Lessons learnt from POC
• Automatic generation of web-base collection tool was
possible
• Need an ABS (or a wider-NSI) DDI profile
• Need for a Metadata Creation and Management Toolbox
• Centrally registered, accessible and governed metadata.
Conclusions from the two case studies
• Metadata-driven business process is feasible
• There are technical challenges but the more significant ones
are non-technical.
• There are implications for metadata management
• Move from siloed systems to integrated metadata
infrastructure
• Conceptualise and implement metadata consistently
• Govern metadata definition, use, etc. effectively.
Likely implications for metadata management –
based on ABS experience
• ‘Templates’ depicting what GSIM object are required
as input/output to GSBPM sub-processes are needed
• Informal Task Force on Metadata Flows across the GSBPM – a
good start.
• Versioning strategy for metadata is required
• ‘Eco system’ of governance arrangements – e.g. IT
governance, Information Management governance,
etc. should all cohere
Likely implications for metadata management –
based on ABS experience (cont.)
• Statistical Metadata Systems should be made to be
shareable
• Broadening and deepening role of metadata
practitioners
• Metadata practitioners must be up-to-date with
frameworks and Standards.
Key Messages
• Metadata driven business process is feasible
• Metadata driven business process credibly presents
tangible business benefits
• Metadata driven business process is consistent with
HLG Vision
• Metadata driven business process will require
potentially significant changes to the way metadata is
managed in an NSI.