Presentation is loading. Please wait.

Presentation is loading. Please wait.

Information about the HLG work Some considerations on HLG and related work from an NSI point of view Rune Gløersen, Statistics Norway.

Similar presentations


Presentation on theme: "Information about the HLG work Some considerations on HLG and related work from an NSI point of view Rune Gløersen, Statistics Norway."— Presentation transcript:

1 Information about the HLG work Some considerations on HLG and related work from an NSI point of view Rune Gløersen, Statistics Norway

2 Introducing the HLG High-level Group for the Modernisation of Official Statistics Created by the Conference of European Statisticians in 2010 Vision and strategy endorsed by CES in 2011/2012

3 Who are the HLG members? Ireland - Chair Australia Canada Italy Netherlands New Zealand Republic of Korea Slovenia  Eurostat  OECD  UNECE

4 What does the HLG do? Oversees activities that support modernisation of statistical organisations Stimulates development of global standards and international collaboration activities “Within the official statistics community... take a strategic leadership and coordination role” Two strands; 1) high level models and standardisation, 2) innovation in products and methods

5 Why is the HLG needed? Before the HLGNow Many expert groupsClear vision Little coordinationAgreed priorities No overall strategyStrategic leadership Limited impactReal progress

6 The Challenges

7 HLG Organisation CSPA sub-committee

8 Standards-based Modernisaton 135 28% 43% 34,600

9

10 What is CSPA CSPA provides a framework within an Enterprise Architecture to help each agency in their modernisation, based on common standards: o GSBPM o GSIM o DDI / SDMX CSPA is a service oriented approach that allows us to modernise our environment and (re)use existing international solutions (services/ components)

11 CSPA catalogue Eurostat is hosting the global service catalogue

12 CSPA Implementation - 2015 Specify together, develop individually Catalogue extensions Sustainable governance and support mechanisms Logical Information Model More CSPA services

13 Machine Learning Innovation in products, sources and methods Share the cost of innovation! Immediate pay back.

14 Big Data Project: 2015 More sandbox experiments More data –UNSD Comtrade –Wikipedia –Business data from company web sites Future of the sandbox –Subscription model will be launched soon –Not just for Big Data – other uses e.g. shared development of methods, shared training materials, …

15 Big Data Project: 2015 Challenge from the High-Level Group: Produce and release a set of internationally comparable statistics from one or more Big Data sources By the end of 2015!

16 Other initiatives GAMSO Machine learning –overview of the machine learning techniques currently in use or in consideration at statistical agencies worldwide –Seminar in The Hague 23 november Generic Statistical Data Editing Models –To be launched at the HLG Seminar 24-25 November

17 Strategic Investment Planning Sharing plans between organisations Finding partners with similar priorities Trialing an Investment Comparison Tool

18 NSI collaboration within HLG Voluntarily basis Solving common challenges Bottom up approach, but turning quicly into necessary top down processes, leading to sufficiently anchored common decisions –i.e. Building CSPA services, revealing the need to develop the Logical Information Model Strong belief in the need for agreements/harmonisation at conseptual level, as a basis for sustainable business standardisation/industrialisation Still; important elements are missing

19 HLG work; Get involved! Anyone is welcome to contribute! More Information HLG Wiki: www1.unece.org/stat/platform/display/hlgbas LinkedIn group: “Business architecture in statistics”

20 Modernisation programme at Statistics Norway Some considerations made on the value and impact of international work and international obligations during our planning phase Our focus has been on describing an enterprise architecture based upon national and international accepted frameworks, models, standards and recommendations

21 Modernisation Programme at Statistics Norway In planning, but the level of ambition will be discussed Comprehensive analysis and target descriptions are developed, contributing to further development within all areas of our Enterprise Architecture

22 Building EA at StatsNorway Using TOGAF Based upon international models and frameworks from our statistical community Coherence between the architecture domains Coherence between the different levels of abstraction and details Useful for different stakeholders (management, users, IT etc)

23 Enterprise Architecture Level of abstraction Conceptual Logical Physical Detail Business «demands» IT solutions

24 GSBPM GAMSO (HLG) GSIM HLG models and framework HLG has not designed a complete EA framework However, the models form useful elements of an EA, and are accepted standards for their purpose The models are at different levels of maturity There are missing links through the levels of abstraction and details CSPA

25 GSBPM GAMSO (HLG) GSIM HLG models and framework The conseptual and high level of abstraction within the Business Architecture should be harmonised within our industry (otherwise; what defines our industry?) International work should systematically feed back enhancements GAMSO/CM merge Capability Model (ESS/EARF)

26 GSBPM GAMSO (HLG) GSIM HLG models and framework There is a missing link between the Business architecture models and the CSPA i.e business services used during the process phase; Sample surveys, registerbased stats, macroeconomic stats The logical description of the business services should close this gap, referencing i.e GSBPM through building blocks A complete set of CSPA services comprises all relevant business functions to provide for a statistical production system Capability Model (ESS/EARF) CSPA ?

27 CSPA Logical Information Model CSPA services are built bottom up, shared as IT services Business service descriptions are needed, at a sufficient logically detailed level

28 NSI and ESS collaboration in EA context ESS BB/Business services Associated IT services Common BB/Business services Associated IT Services NSI BB/Business services Associated IT services ESS components and solutions Common components and solutions Local components and solutions EU view NSI/ HLG view

29 NSI and ESS collaboration in EA context Deployment scenarios ESS BB/Business services Associated IT services Common BB/Business services Associated IT Services NSI BB/Business services Associated IT services Centralized service Shared service Reused service or component ESS service There is a need to be rather concrete. The type of service to be built varies within one project, e.g. Validation. Not mentioned: Local NSI service Local ESS service

30 Conclusions At StatsNorway, we are far from finished in developing a complete EA reference framework within statistics. In addition to developing the EA framework, we analyse our current situation, and identifies the as-is – to-be gap. Any project should be examined according to this gap. There are no complete frameworks to lean on, which means that we reveal the need for new elements described/developed according to our business needs (which most likely is similarly to the need among a lot of institutes). New (part of) models should therefore be examined and approved, avoiding competing models Architecture competence must be enhanced Architecture must be maintained Architecture Governance must be implemented. This is the way to show the value of the architecture work Communication of architecture must be targeted according to stakeholders needs and knowledge The architecture work should lead to flexible and agile production and organisations.


Download ppt "Information about the HLG work Some considerations on HLG and related work from an NSI point of view Rune Gløersen, Statistics Norway."

Similar presentations


Ads by Google