1. State of the art of CSPA and sharing tools projects
Marco Silipo
THE CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION

2. Introduction What’s happening with… …and how can CSPA help ?
Statistical Organizations ?
World of statistics ?
Technologies ?
…and how can CSPA help ?

3. Statistical Organizations – Trends
Agency transformation
Agility, Flexibility, Quality, Efficiency, Relevance
New modes of engagement and delivery – products, services, partnerships, collaboration, leadership, education
Provider Partnerships, Administrative and Big Data
Digital platforms and shared services
Cost optimization
Advanced methods and tools
Cross-agency, domain, levels of government, statistics to support new policy, service delivery initiatives
Locally relevant statistics (small area) for local government service delivery
Sustainable development goals and world collaboration
Internal innovation programs
Open data platforms

4. World of Statistics – Trends
Data Science and Scientists
Collaborative statistics
Collaborative methods and tools
Visualization and visual analytics
Data prospecting, exploration, integration
Open data and “open by default”
Artificial Intelligence and Machine Learning
“Oceans of data”
Event-stream statistics, near real-time, now-casting, predictive analytics
Public sector leverage of statistics
Open training – e.g. MOOCS, universities, web-based
“Citizen statisticians”

5. Technology – Trends
Collaborative development, sharing of tools and methods, “experts in a box” starter kits
Cloud-based statistics
Cognitive Solutions, Artificial intelligence, Machine Learning
API’s and microservices
High-performance processing
Data lakes
Advanced search, discovery, use of knowledge, data
COTS – OpenSource integrations
Advanced geo-informatics
Internet of Things – a world of sensors and event streams
…and more
Cloud

6. How will you meet the challenges and harness the opportunities this new world creates?
As an Enterprise
As a Designer
As an Investor
As a User
As an Assembler

8. Wiesbaden Workshop 2017 Investor Designer “Mon – Tue- Wed” “Future”
Assembler
“You”

9. More and more data is available to public sector, science and business!
Drivers:
Cloud Computing
Internet of Services
Internet of Things
Cyberphysical Systems
sensor data
web archives
video streams
Underlying Trends:
Connectivity
Collaboration Computer generated data
simulation data
audio streams
RFID data

11. Skills Best-Practices
The 5 Dimensions of Data
Ownership
Copyright/IPR
Liability
Insolvancy
Privacy
Data-driven Decision Making
Risk Management
Competitive Intelligence
Digital Humanities
Personalised services
Industry 4.0
Legal Dimension
Social Dimension
Economic Dimension
Technology Dimension
Application Dimension
User Behaviour
Societal Impact
Collaboration
Data Ecosystem
Infrastructures
Skills Best-Practices
Entrepreneurship
Business Models Benchmarking
Deployment Models
Data Pricing
Scalable Data Processing
HPC
Statistics/ML
Multilinguality
Visualization

12. Policy context: the European Digital Single Market
1.Better access for consumers and businesses
to digital goods and services across Europe
Unlocking the e-commerce potential
Enable SMEs and start-ups to scale-up
End to geoblocking of goods and services
2. Shaping the right environment for
digital networks and services to flourish
Establish role of online platforms
Telecoms rules fit for the digital age
Improved data protection rules
Combat illegal content online
3. Building a European Digital Economy
and society with growth potential
Big data and Cloud Strategy
Digitalising European Industry
e-Government Action Plan
Standardisation
e-Skills
Access to data

13. The data economy

14. Data-driven applications …
home automation
health
lifecycle management
water management
information marketplaces
market research
traffic
management
energy management
… will revolutionise decision making!
… have great economic potential!

15. We need efficient statistical data ecosystem/s

16. Transformation of organisations
Organisations evolving towards more service oriented approach. Focus on the service and the customer and not in the product itself
Organisations developing shared services that can scale-up and be reused

17. Create Services for reuse
Services should be created once and then reused many times
How the statistical community can benefit from this approach?

18. CSPA as enabler for building shared-services (current situation)
NSI 1
Collect
Process
Analyse
Disseminate
country 2
Output
Different tools and process for the same requirements.
COSTLY
NSI 2
country 1
CSPA is a reference architecture for the statistical industry build by the international statistical community. It includes technology architecture and principles but does not prescribe technology environments

19. CSPA as enabler for building shared-services (targeted model)
Collect
Process
Analyse
Disseminate ?
Sharing Services where economical
“Plug and Play” architecture ?
CSPA is a reference architecture for the statistical industry build by the international statistical community. It includes technology architecture and principles but does not prescribe technology environments

20. Building the future of European statistics
Political: DSM (Digital Single Market)
Statistical: European Statistical System (ESS) members are committed to sharing and reuse. Members and Eurostat participate in standards building and maintenance (CSPA, GSBPM…)

21. WHAT? Five priority areas
better understand and address user needs
be a global partner and leader for innovation
build strategic alliances with public and private partners
Users
abide with the European Statistics Code of Practice
apply fit-for-purpose tools to enhance quality assurance
assess the usability and quality of source data
Quality
exploit potential of new data sources
invest in new IT tools and methodology
continue to improve existing data collection methods
New data sources
adopt a new dissemination and communication strategy
create a data pool of European statistics
optimise ESS portfolio of products and services
promote European statistics as a brand
Dissemination
further intensify the collaborative partnership of the ESS
further identify and implement standards for statistical production
adopt enterprise architecture as a common reference framework
advance in sharing IT services and infrastructure
benefit from exchange of (micro)data, while fully respecting statistical confidentiality
Production process

22. Shared SERVices
Goal: Developing and sharing IT services in the ESS by implementing UNECE's steered Common Statistical Production Architecture (CSPA)
Achievements:
Infrastructure for centrally hosting services set up
Service catalogue for ESS and CSPA community (soon with integrated lifecycle of services)
Interaction and advice to Validation and ESBRs
National Accounts started deploying SERV
ESSnet building example services in NSIs and guidelines
Phase 2 launched by the ESSC

23. First finalised ESS project: Validation
Project successfully finalised: methodological handbook, validation language (VTL), architecture, service prototypes
Now – following a roadmap for implementation at the national level
Start with 7 pilot domains and 8 pilot countries
Even on this code list, most codes can be agreed.
Even on this code list, most codes can be agreed.