Recording your answers to these questions from the outset of your research will enable you to reuse and share your data easily.
Recording all the processing done to the data (collection, cleaning, fusion, encoding, etc.) enables you to retrace the different stages of your work in order to maintain a clear understanding of your data.
[Video] Tips on Documentation, John MacInne, Professor of Sociology, University of Edinburgh (MANTRA)
A dataset is comprised of a collection of data files forming an intellectual unit, as well as the documentation of this data and its metadata (administrative and structural descriptions).
Title, author, date, publisher, etc. – these constitute the metadata of your publications. Your data can also be described using metadata (type of data, creation date of dataset, manager name, version, format, etc.).
► SCIENCES PO HAS ADOPTED THE DDI STANDARD
DDI (Data Documentation Initiative) is the scheme operating natively in data.sciencespo (available soon), the Sciences Po data repository.
Designed for data produced in the social sciences, it is particularly well adapted to describing survey data.
If you would like to deposit your data in data.sciencespo or in any other repository, contact the library’s Data Team.
[Video] Les schémas de métadonnées (DoRANum)
Credits: This guide is written by the Library Research Data team in collaboration with the Sciences Po research centers, the Office for Research (DS) and the Office of Information Systems (DSI). For more information, please contact the Data team: email@example.com. Translation : Anita Beldiman-Moore, Sophie Forcadell from the Library.
Legal notices: https://www.sciencespo.fr/bibliotheque/en/legal-notices.html