This website is made for the SSPHub, a network to foster collaboration and exchange among data scientists from the French Official Statistical Office. Indeed, in France, the French Official Statistical Office is decentralized :
The English version of the website aims at sharing code and innovative projects produced by the data scientists from the French Official Statistical Office.
The French version of the website offers broader resources to data scientists (newsletter, courses ⊠). As it has limited value added for people outside of the French administration, it has not been translated. But, if youâre interestedđ, you are more than welcome to have a look (by using automated translation tools).
Find out more information about the SSPHub network on the dedicated page.
It is always difficult to define ex ante what constitutes an innovative project. Technological innovation is by definition fluid and evolves very quickly. However, as stated in the manifesto (in French), recent technological innovations aim to simplify and accelerate certain production processes, facilitate the exploitation of non-traditional or large data sources, automate certain tasks, communicate with wider audiences using responsive visualisations, and, among other things, reduce the gap between statisticians and computer scientists. For example, modernising a processing chain through the use of new packages or new methods of information processing is an innovation. However, this may not be ambitious enough on its own to constitute a truly innovative project, and therefore will not necessarily be included in the projects presented here. The use of web scraping to build a database that is automatically populated will be considered an innovative project. Conversely, simply updating code or using new administrative databases, if it does not involve any particular technological obstacles, is not considered technological innovation in itself. Such projects can however be necessary or welcome đ.
Furthermore, a project that is innovative at a given point in time may no longer be so a few months or years later, when the innovation has become widespread enough to be considered conventional knowledge.
Innovation also occurs everywhere and is not limited to various data science innovation laboratories.
The list of projects presented here is not intended to be exhaustive. It is based on voluntary participation. The aim is to provide a central hub for sharing between SSP data scientists, as outlined in the manifesto (in French). Any proposals for additions or mergers on our platform are welcome!
