Data Processing Methods service (DPM)

DPM is there for methodological and technical accompaniment at all data processing stages of the research projects conducted at INED.

The service intervenes from the early database-structuring stage by advising research teams on data source choice, use of statistical software, variable construction; enhancing databases through matching and integration of contextual databases, running exploratory and inferential analyses, and interpreting results.

It handles a highly diverse range of data types: survey, administrative, textual, geographic, network, internet, and contextual.

DPM also supports research teams in data management: documentation, processing automation, reproducibility, and trackability. And in connection with INED’s Open Science charter MISO, it implements and works to diffuse a number of “best practices,” including:

• Code and program sharing
• Training and documentation support (literate programming, dynamic reports that combine scripts and comments).
   

DPM offers organized training to enrich the data processing skills of INED researchers, technicians, post-docs, and doctoral students, as well as sessions on how to select the best-adapted software tools.

Main activities in this area:

• In-house researcher training in methods, statistical analysis programs, data visualization, programming, reproducibility, and others)
• Designing and writing up learning material (technical documentation, tutorials, learning and teaching kits)
• Platform, program/software monitoring (R, Stata, mapping, textual analysis, and others).

DPM’s specialist technicians offer seminars on methodology open to all researchers/personnel (registration required):

• At the “INED Mondays": weekly lunch-hour seminar sessions, a place for multidisciplinary scientific presentations and discussions on population questions; INED researchers and outside guests present their work, then discussed by a peer. Every year DPM offers two sessions on the development of innovative technical methods in statistics or data science applications in the human and social sciences.
   
• The R for Social Science Use (RUSS) seminar: presentation to statistical processing practitioners of programming experiments connected with R multiplatform software. 2 to 4 sessions per year. Seminar co-organized with the School of Advanced Studies in the Social Sciences (EHESS) and the National Center for Scientific Research (CNRS).    

The list and content of previous seminars in these two areas can be found on the relevant web pages, together with the software, supports, and video presentations. (Diffused via video link to the INED channel of Canal U). 

DPM is active in further diffusing of INED-produced scientific data and results to reach a variety of audiences.

This includes:

• Producing visualizations (graphs, maps, networks, interactive applications) to be used as editorial supports and on our website.
• Developing, managing, documenting, making available, and widely diffusing demographic and contextual databases.

DPM service members participate actively in scientific life outside INED, presenting and discussing papers at conferences, running seminars, and taking part in academic events, sitting on scientific committees, and organizing scientific events. 

DPM is an active and valued collaborator in French and international scientific, professional, and institutional networks. 
These partnerships are a means of sharing skills, contributing to joint projects, and giving further weight to research communities and research support services.

DPM engineers regularly take part in training both inside and outside INED. They teach master’s classes at universities, take part in schools structured around particular fields, and design training modules in data-processing tools and methods.

These activities diffuse knowledge and work to update skills as methodology evolves. DPM support service partners include the ENSAI national school of statistics and information analysis, the Center for the Study of Economic Programs (CEPE), the Graduate School of Demography (HED), the School of Advanced Studies in the Social Sciences (EHESS), and the National Center for Scientific Research (CNRS).