Meeting today’s dissemination challenges – Implementing International Standards in OECD.Stat...

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MEETING TODAY’S DISSEMINATION CHALLENGES:Implementing international standards in .Stat

Prepared by Jonathan Challener, OECDFor MSIS, April 2014 - Dublin, Ireland

Doesn’t non-standard power supplies make things difficult?

What happens when standards are not applied well?

Picture: ‘The day Sweden changed from left-hand drive to right’

Confusion entails

This all adds up…

…high costs…

and inefficiencies!

and inefficiencies!“A little like the grade 8 student who doesn’t pay attention in class all year”.

WHAT IS .STAT?

What is .Stat?

.Stat is the central repository ("warehouse") of validated statistics and related metadata

.Stat is the central hub connecting data production, sharing & dissemination

processes

It is the corporate source of data for data sharing and dissemination purposes

What is .Stat?

.Stat is the central repository ("warehouse") of validated statistics and related metadata

.Stat is the central hub connecting data production, sharing & dissemination

processes

It is the corporate source of data for data sharing and dissemination purposes

“.Stat is now being used and shared with 10 organisations including the OECD, as part of the Statistical Information System Collaboration Community (SIS-CC)”.

.Stat Positioning in Statistical Information System

DATA DELIVERY

INTERNAL DATA SHARING

DATA DISSEMINATION

DATA PRODUCTION

.STAT

.Stat Positioning in Statistical Information System

DATA DELIVERY

INTERNAL DATA SHARING

DATA DISSEMINATION

DATA PRODUCTION

.STAT

“The diagram illustrates the .Stat contribution to the SIS processes. .Stat’s core value-added lies in “Data Delivery”, a set of functions that enable dissemination and data sharing, and “Data Upload”, a set of functions interfacing data production processes into a single upload mechanism to feed dissemination channels”.

.Stat Functional Representation

.STAT DATA DELIVERY ENGINE

DATA PRODUCTION

DATA SHARING DATA DISSEMINATION

SEARCH ENGINES

DATA ANALYSIS TOOLS

PC

WEBSITES, APPSPUBLICATIONS.STAT BROWSER

.STAT DATA UPLOAD ENGINE

FILEUPLOAD

SDMX IMPORT

DATA PRODUCTION TOOLS

TABLE & CHART EXTRACTION SERVICES

RELEASE MGTSERVICES

.STAT BROWSERCONFIGURATION

DATA EXTRACTION SERVICES

SDMX INPUT

E

P

BATCH UPLOAD

SDMX GLOBAL

REGISTRY

PUBLISHINGBACK

OFFICE

DATA MAPPING

SDMX OUTPUT

X

X

.Stat Component

Process

Human userData ProducerData EditorData Consumer

API orWebservice

OtherSDMX hubs

.Stat Functional Representation

.STAT DATA DELIVERY ENGINE

DATA PRODUCTION

DATA SHARING DATA DISSEMINATION

SEARCH ENGINES

DATA ANALYSIS TOOLS

PC

WEBSITES, APPSPUBLICATIONS.STAT BROWSER

.STAT DATA UPLOAD ENGINE

FILEUPLOAD

SDMX IMPORT

DATA PRODUCTION TOOLS

TABLE & CHART EXTRACTION SERVICES

RELEASE MGTSERVICES

.STAT BROWSERCONFIGURATION

DATA EXTRACTION SERVICES

SDMX INPUT

E

P

BATCH UPLOAD

SDMX GLOBAL

REGISTRY

PUBLISHINGBACK

OFFICE

DATA MAPPING

SDMX OUTPUT

X

X

.Stat Component

Process

Human userData ProducerData EditorData Consumer

API orWebservice

OtherSDMX hubs

“The grey shaded boxes in the figure below show a visual representation of how .Stat fits within a broader Data Dissemination Information System of organisations; the boxes with dotted lines represent other components of the Data Dissemination Information System that are not supported by .Stat but are enabled by it”.

.Stat Functional Representation

In particular, .Stat provides the following 3 key functional areas…

.Stat Functional Representation.Stat Data Upload Engine

.Stat Functional Representation.Stat Data Delivery Engine

.Stat Functional Representation.Stat Data Browser

.Stat Positioning in GSBPM Reference Model

.Stat contributes to Planned additions

Archive incorporated into the over-arching process of data and metadata management

.Stat Positioning in GSBPM Reference Model

.Stat contributes to Planned additions

Archive incorporated into the over-arching process of data and metadata management

“.Stat can be mapped today to the Generic Statistical Business Process Model (GSBPM) under “Disseminate” and “Build”. In the future it will also incorporate archive functions as part of the over-arching process for data and metadata management”.

Multipurpose SDMX within .Stat…

For dissemination and data eXchange

SDMXWS and RESTful API• SDMX 2.0 compliant• SOAP + REST• Pull• SDMX-ML• SDMX Structural

metadata created on the fly

For ‘Open Data’ dissemination

SDMX-JSON (beta)SDMX-TWG agreed in mid 2013 on proposal for data and their structural metadata (inc. flat & sliced layouts) and referential metadata (dataset, series, obs) as annotations.

Further enhancements to come: Complete data structures and referential metadata

For data reporting

SDMX-Reference Infrastructure (RI)*• SDMX 2.0 and 2.1

compliant• SOAP + REST• SDMX Common APIs

(SdmxSource.NET)

• Pull + Push• SDMX-ML, GESMES ,

CSV• Structural metadata

stored in mini registry• One web service - several

mapped database instances

Mapping Store DB

XXX.StatData

warehouse

SDMX-RI Web Service

DisseminationMapping Assistant

SDMX-RI

* The integration of SDMX-RI in .Stat is based on collaboration with Eurostat, provider of the SDMX-RI component with ISTAT taking the lead on behalf of the OECD’s Statistical Information System Collaboration Community.

For internal data sharing

DirectAccess• Restful SDMX query• Flat data, flags, units• Referential metadata

Excel-add-in• DirectAccess (Rest

SDMX)• Native Excel pivot table• Wizard to select data

For a decentralised publishing environment

DataHub*• One interface to the

publishing tools• Centralised reporting and

auditing• SDMX based structural

metadata, and referential metadata management

• Flexible load tool that promotes ‘self publish’ for data custodians

• In-built checks and safeguards to minimise errors

• Manages security and access rights

• Can be extended to manage other outputs and not limited to .Stat

* DataHub has been developed and integrated with .Stat by Statistics NZ, with an additional connection to the Fusion Registry for managing structural metadata through the definition of DSDs.

Future outlook…

Further SDMX artifact support

SDMX ingest (Import)

SDMX global registry API

SDMX-RDF data cube vocabulary pilot

SDMX-RDF data cube vocabulary pilot

“Explore further semantic web/linked data opportunities (SDMX-RDF data cube vocabulary). To be taken forward by ISTAT and ABS under the SIS-CC umbrella”.

• Lower technology adoption costs• Increased development consistency,

simplicity and predictability• Improved code reuse• Reduced cost, time and effort to transition

between different solutions

We all know the…

• Reduced focus on infrastructure• Ability to create composite interfaces that are tailored to the

needs of specific task• Improved application portability• Enable faster time to market because it is easier to use off the

shelf components and applications that can integrate and provide features for the solution

References

1. Operationalising .Stat in a decentralised publishing environment (DataHub) by Tony Breen SNZ : https://community.oecd.org/docs/DOC-68362

2. Building a scalable architecture (.Stat) by Jens Dosse OECD: https://community.oecd.org/docs/DOC-68363

3. SDMX-RI and .Stat integration by Francesco Rizzo Istat: https://community.oecd.org/docs/DOC-68696

4. SDMX-JSON API: http://stats.oecd.org/opendataapi/Index.htm

Jonathan Challener, OECD jonathan.challener@oecd.org@Challener

MSIS - Dublin, 14-16 April 2014Meeting today’s dissemination challenges: Implementing international standards in .Stat

Thank you