IPS 264 - Flexible infrastructure for next generation of statisticians

Category: IPS

Wednesday 19 July 10 a.m. - noon (Canada/Eastern) (Expired) Room 108

Official Statistics needs to innovate continuously in order to stay relevant and gain agility. New technologies are key enablers for this. New architectures allow rapid changes and continuous deployment at scale and using open source solutions allow to maximise its reuse. This session will aim at reviewing recent initiatives harnessing cloud technologies built on open source solutions in the context of official statistics and discuss opportunities for National Statistical Institutes to collaborate to realise economies of scale.

All over the world, there is a continuous need for a flexible environment where statisticians and data scientist can use the latest technologies to create new innovative products. To fulfil these requests several initiatives were launched around the globe, just to name a few:

- Data science campus, ONS (https://datasciencecampus.ons.gov.uk)

- Advance Analytics Workspace, StatCan (https://statcan.github.io/daaas/en/)

- Onyxia, INSEE (https://github.com/inseefrlab/onyxia)

- EC Data Platform (https://ec-europa.github.io/digit-dataplatform/)

- Cloudlab, Eurostat (https://github.com/eurostat/datalab)

Many of these projects are using cloud based technologies and built on open source solutions for possible reuse by the statistical community. The session would review some of these initiatives providing the guiding principles of technological choices and the limitations of the different solutions. The session would provide a chance to discuss best practices, new trends and possible opportunities for National Statistical Institutes and international scientific community to collaborate in order to realise economies of scale.

The session can be divided in two parts, with a series of brief presentations by the speakers followed by a panel discussion between the speakers moderated by a discussant or the chair. Alternatively, depending on the number of speakers, the session could comprise only the presentation of ongoing projects with no panel discussion.

Potential speakers are the developers or project managers of the above listed solutions and the discussant can be one of the member of the UNECE 2022 Machine Learning group working on IT infrastructure (https://statswiki.unece.org/display/ML/Machine+Learning+Group+2022).

Organiser: Mr Mátyás Mészáros

Chair: Monica Pickard

Speaker: Mr Romain Lesur

Speaker: Ms Marie Haldorson

Speaker: Christie Sambell

Discussant: Albrecht Wirthmann