Joint ESS data analysis undertakings


Many statistical institutes face similar data analysis requests. As for many other areas, there might be a potential for ESS members to collaborate on certain aspects of data analytics: sharing tools, approaches and methods.  This the more as both the ESS Vision 2020 and the ESS priorities beyond 2020 set out needs that could be tackled by data analytics initiatives. 

At this daWos session, we will explore the potential for ESS collaboration on data analytics. 

Questions that could be addressed include

  • How to identify commonalities in the ESS? Are there any ideas for joint collaboration for development/deployment of data analytics tools?
  • What should be the strategic components to be developed (and shared) in-house w.r.t. those normally available externally (through "competitors")?
  • Is there actually a need for common framework/guidelines to integrate data analytics tools and techniques (e.g., a common architecture) in daily business?
  • Are they business areas where data analytics could benefit from actual European partnership/collaboration: in accessing data? in providing common infrastructure? in sharing software resources? in adopting a common metadata template[1]?
  • Considering the different state of advancement in the different statistical institutes, how to best take advantage of shared practices and validated tools?

[1] See for instance the work of the Research Data Alliance: http://rd-alliance.github.io/metadata-directory/.


Matyas Meszaros, Statistical Officer – Eurostat.