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MEETING TODAY’S DISSEMINATION CHALLENGES: Implementing international standards in.Stat Prepared by Jonathan Challener, OECD For MSIS, April 2014 - Dublin,

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Presentation on theme: "MEETING TODAY’S DISSEMINATION CHALLENGES: Implementing international standards in.Stat Prepared by Jonathan Challener, OECD For MSIS, April 2014 - Dublin,"— Presentation transcript:

1 MEETING TODAY’S DISSEMINATION CHALLENGES: Implementing international standards in.Stat Prepared by Jonathan Challener, OECD For MSIS, April Dublin, Ireland

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

3 What happens when standards are not applied well?

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

5 This all adds up…

6 …high costs…

7 and inefficiencies!

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

9 WHAT IS.STAT?

10 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

11 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)”.

12 .Stat Positioning in Statistical Information System DATA DELIVERY INTERNAL DATA SHARING DATA DISSEMINATION DATA PRODUCTION.STAT

13 .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”.

14 .Stat Functional Representation.STAT DATA DELIVERY ENGINE.STAT DATA DELIVERY ENGINE DATA PRODUCTION DATA SHARING DATA DISSEMINATION SEARCH ENGINES DATA ANALYSIS TOOLS P C WEBSITES, APPS PUBLICATIONS.STAT BROWSER.STAT DATA UPLOAD ENGINE FILE UPLOAD FILE UPLOAD SDMX IMPORT DATA PRODUCTION TOOLS TABLE & CHART EXTRACTION SERVICES RELEASE MGT SERVICES RELEASE MGT SERVICES.STAT BROWSER CONFIGURATION.STAT BROWSER CONFIGURATION DATA EXTRACTION SERVICES DATA EXTRACTION SERVICES SDMX INPUT E P BATCH UPLOAD SDMX GLOBAL REGISTRY PUBLISHING BACK OFFICE DATA MAPPING SDMX OUTPUT X X.Stat Component Process Human user Data Producer Data Editor Data Consumer API or Webservice Other SDMX hubs

15 .Stat Functional Representation.STAT DATA DELIVERY ENGINE.STAT DATA DELIVERY ENGINE DATA PRODUCTION DATA SHARING DATA DISSEMINATION SEARCH ENGINES DATA ANALYSIS TOOLS P C WEBSITES, APPS PUBLICATIONS.STAT BROWSER.STAT DATA UPLOAD ENGINE FILE UPLOAD FILE UPLOAD SDMX IMPORT DATA PRODUCTION TOOLS TABLE & CHART EXTRACTION SERVICES RELEASE MGT SERVICES RELEASE MGT SERVICES.STAT BROWSER CONFIGURATION.STAT BROWSER CONFIGURATION DATA EXTRACTION SERVICES DATA EXTRACTION SERVICES SDMX INPUT E P BATCH UPLOAD SDMX GLOBAL REGISTRY PUBLISHING BACK OFFICE DATA MAPPING SDMX OUTPUT X X.Stat Component Process Human user Data Producer Data Editor Data Consumer API or Webservice Other SDMX 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”.

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

17 .Stat Functional Representation.Stat Data Upload Engine

18 .Stat Functional Representation.Stat Data Delivery Engine

19 .Stat Functional Representation.Stat Data Browser

20 .Stat Positioning in GSBPM Reference Model

21 “.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”.GSBPM

22 Multipurpose SDMX within.Stat…

23 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

24 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

25 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.Stat Data warehouse XXX.Stat Data warehouse SDMX-RI Web Service Dissemination Mapping 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.

26 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

27 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.

28 Future outlook…

29 Further SDMX artifact support

30 SDMX ingest (Import)

31 SDMX global registry API

32 SDMX-RDF data cube vocabulary pilot

33 “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”.

34 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

35 References 1.Operationalising.Stat in a decentralised publishing environment (DataHub) by Tony Breen SNZ : https://community.oecd.org/docs/DOC https://community.oecd.org/docs/DOC Building a scalable architecture (.Stat) by Jens Dosse OECD: https://community.oecd.org/docs/DOC https://community.oecd.org/docs/DOC SDMX-RI and.Stat integration by Francesco Rizzo Istat: https://community.oecd.org/docs/DOC https://community.oecd.org/docs/DOC SDMX-JSON API:

36 Jonathan Challener, MSIS - Dublin, April 2014 Meeting today’s dissemination challenges: Implementing international standards in.Stat Thank you


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