methodological network and strategy

Methodological network and strategy

B1 Unit Meeting, 5 of September 2016by Dario Buono

Outline

Eurostat Methodological Networko Some history, pipeline and foreseen activities

Eurostat Methodological Strategyo Definition & Scopeo Data-driven world o Implications for Eurostato Focus on cross-cutting methodological worko Implementation

Eurostat Methodological Network (1)

Some history• End of 2014, idea proposed by the Eurostat 2020

discussion group B on “Permanent Methodological Development”

• April 2015, idea adopted by the DM seminar • Summer 2015, methodological skills Survey• September 2015, B1 brainstorming event • October 2015, DM approves METAC mandate• February 2016, 1st Seminar on Data Science• April 2016, DM approves Methodological Strategy


….more history• June 2016, DM approves procedure to join

the network• June 2016, 2nd Seminar on Indicators• July 2016, Cybernews call for expression of

interest • July 2016: About 25 people officially join

following approval by HoU and Director

• Up to 10 WDs within objectives


Pipeline• September 2016 kick-off event for network Clustering:

1. Data integration 2. Data analytics 3. New statistical methods for new data

• October 2016, appointing coordinator and drafting work programme

• November 2016, presentation of clusters and co-ordinators to the HUM

• 2017, running activities and reporting back to DM

What's in for the Network?

Examples of activities• Eurostat Statistical working papers• methodological help-desk services• scientific work for Eurostat events: authoring articles,

peer reviewing, scientific committee membership, session chairing, panellist, literature reviewing

• methodological Q&A sessions• ESTP and EMOS• metadata template for quality grading of indicators

Methodological Strategy (1)• "Methodology is… a system of methods

used in a particular area of study or activity; • Methodology is… about how we conduct

the statistical processing

• which reminds…

Methodological Strategy (2)

Scopeo focuses on cross-cutting areas and methods

o Compilation/production of statisticso Analysis of statisticso Co-operation with Member States for a given statistical

areao Metadata management

o domains' priorities in line with work programmeso forward-looking perspectiveo focusing on new developments

Data Driven World: context• Objective 1 ESP• Demand of data users• Methodologists need to innovate based on new statistical methods and information technologies

Data Driven World: challenges

• ESS needs alternative methods• Limitations of traditional surveys• Not same quality standards of statistics produced and

published by organisations• Eurostat needs to adapt to increasing competition

Implications for Eurostat

• Become a statistical services provider• Combine skills (data science, IT, domain knowledge)• Integrate existing data and new sources• Validate or replace data• Involve staff from different directorates• Proactive approach• New communication and dissemination• Capacity of innovation

Three Strategic orientations!

Implementation of cross-cutting methodological work• ESS Vision 2020 portfolio• Existing programmes in Eurostat directorates• Identify and coordinate cross-cutting areas• Screen and approve project proposals (METAC)• Collaborate with external organisations

• ….and now….• two • Enterprise • Architecture • masterpieces!!

METHODOLOGICAL ACTIVITIES ALONG THE GSBPM STEPS Legend: Cross-cutting methodological activities requiring horizontal initiatives

Methodological activities with horizontal ad-hoc support

Directorate methodological domain activities

1. Specify needs

•Definition of new needs and dealing with unstructured data•Definition of new statistical products and/or services•Identification of possible new sources

2. Design

•Design of statistical products and services (new sources, new data analytics services)•Harmonisation: statistical classification, concept, data collection instrument.•Design for European surveys.•Standardised methods/tools: validation methods, model based estimation , integrating and

combining sources, EU aggregates estimation, confidentiality procedures, or quality assessment.• Statistical methodology services (guidelines, handbook)

3. Build.

•ESS activities on harmonisation, standardisation, and modernisation

4. Collect

•ESS activities on harmonisation, standardisation, and modernisation•Data Exchange/reception/sharing

5. Process

•Combining sources (data matching/ record linkage methods). •Validation procedure.•Imputation/estimation methods (time series analysis, nowcasting, model based methods, micro-

data simulation).•EU aggregate estimation.

6. Analyse

•Quality indicators including uncertainty measurement (non-sampling error, outliers detection, revisions impact).

•Development of confidentiality on the fly allowing external users to get tailor made extractions based on microdata that respect relevant confidentiality requirements.

7. Disseminate

•Provision of necessary input and tools for disseminating statistical product and services.•Vertical and horizontal methodological support

QU

ALITY AND M

ETADATA MAN

AGEM

ENT

Thank you for your attention

methodological network and strategy

Data & Analytics