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Guides thématiques

Données de la recherche

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Technical issues

Research data management is the result of several movements that support research in France and abroad, including: Open Access or free access to scientific and technical information, the administration of scientific evidence to validate results through replication, the reuse of data sets, their enhancement and more broadly the safeguarding of the scientific heritage. Policies (e.g. Open Science National Plan, July 4, 2018), initiatives (e.g.: Go FAIR), network (e.g.: Research Data Alliance) are actions that set the beat for research. Impacts can be immediate, such as depositing open-access datasets for the submission of an article (American Journal of Political Science) or the drafting of a data management plan for Horizon Europe and ANR projects or longer term projects. Developing management strategies to document, preserve, enhance and safeguard data will allow the community to better understand your work and its results, but above all will save your time and increase your visibility. 

Some points to adress technical risks:

Why manage data

  • How has the data been constituted? Archives, interviews, surveys, financial databases, web-based data?
  • How have you processed your data? How did you go from raw to refined data?
  • What variables did you use? How are they structured in your files? By date, number, text?
  • Who participated at the various stages of work on the data: entry, processing, coordination...? 

Recording your answers to these questions from the outset of your research will enable you to reuse and share your data easily.

[Video] Data Sharing and ManagementNYU Health Sciences Library Licence Creative Commons

How to process your data

Recording all the processing (collection, cleaning, fusion, encoding...) enables you to retrace the stages of your work to maintain a clear understanding of your data. Do you want to anonymize your surveys to share them?  

[Video] Tips on Documentation, John MacInne, Professor of Sociology, University of Edinburgh (MANTRA) Licence Creative Commons

[Video] Anonymisation: theory and practice (part 1 of 3), Mark Elliot (NCRMLicence Creative Commons

Tools from the medialab

The médialab helps social science and humanities researchers make the most of the mass of data made available by digital technology. It has three main missions that are highly integrated: methodology, analysis, theory. The team develops a large number of software programs that make it possible to organize, automate and visualize research on natively digital or digitized data. Here they are: medialab.sciencespo.fr/tools/​

Focus on your photographs

Some recommendations to better manage your camera or phone images

Before the shooting, check the settings to be made once in your camera or phone: 

  • Format and resolution: JPEG without compression or with the lowest compression possible and the highest resolution
  • Date and Time: updated information, especially if there is a time zone change.
  • Author: your initials or preferably your name.
After the shooting
  • Organize: copy the files to your computer or Institutional Google DRIVE and order the files in a tree structure (e. g. place, subject, date, etc.) and rename them.
  • Document: assign keywords, captions and other attributes to your files, modify metadata with an image management software. This will allow you to make batch changes, such as associating a keyword with a series of images. You can use a table-type tracking file to record where the picture was taken, the context (street visit, regional archives, etc.) or the names of people or contacts. 

How to organize your data

Use a naming convention for your files and choose formats appropriate to your needs. Organizing your data hierarchically with an an appropriate folder structure will allow you to save time, easily find your files, work optimally in collaboration with your colleagues and reuse your data at any time.

[Video] Research Data Management : Organise, Massey University

►​ Data folder structure (case 1)

Model : https://www.ukdataservice.ac.uk/manage-data/format/organising


Data folder structure (case 2)

A model for a simple structure enables you to organize all the data, publications and administrative documents for a particular project.
Source :

Store and share: where, when, how

How to store and secure your data during your research

And some good practices to have in mind: strong password choices, up-to-date operating system and software, encrypted spaces and data.

Storage solution Advantages Risks / Precautions Recommandation

Local storage (computer, laptop)

Easy to manage and to prevent from unauthorised access

Not sufficient if data are stored on only one device (=> backup is needed). Laptops can be stolen Hard-drive encryption is mandatory

Backup your computer

External hard-drive

Useful to exchange data without transmitting them over the Internet Easily lost, stolen and damaged Use preferably for temporary storage

Network shared drive on research center server / Network Attached Storage

Automated backups. Centrally stored. High storage capacity

Can not be accessed by external people For long-term storage

Google Drive - Cloud storage provided by Sciences Po

Can be accessed by external people (if they have a Google email address). Automatic Backup

Storage in E.U. not guaranteed => conflict with GPDR. Not suitable for all research projects. Control access when sharing

Encrypt personal data before uploading them to the cloud (compliance to GPDR).
Other cloud storage managed by a university or CNRS Secure in case of E.U. storage Size may be limited May be secure and appropriate
Cloud storage without any agreement (e.g. Dropbox)

Widespread use. Not depending on an email provider

Free services by commercial providers may claim rights to use content you manage and share them for their own purposes

Risky. Not recommended for sensitive data

Your Google Sciences Po account is not your private Google account.  As part of the Google Apps for Education business agreement, you benefit from special terms and conditions of use. Google DRIVE Sciences Po is better than any other private solution: Private Google Drive, Drop Box, Orange Box, Facebook, etc.). More information: Google Apps [accès réservé].

► Huma-Num

 For more information, visit the dedicated page.  


► My CoRe - CNRS

​This cloud for "individual storage and backup, nomadism and secure sharing" stores up to 100MB, synchronizes your computers and shares your files. Several types of accounts are available: individual, services (for collective, projects), guests. To find out more, visit the dedicated page.

► FileSender
  • Authentication via the Education-Research identity federation
  • Fast file submission to one or more correspondents
  • Consulting the files uploaded
  • Invitation of correspondents to upload files to their personal file repository space.

 Find out more here: Online Tools / Best practice.

► 7-zip

Do you use or share confidential or personal data? Use 7-zip! This tool, recommended by Sciences Po,  allows you to encrypt a document and meets the need for secure transfer to third parties. The procedure [restricted acces]. To encrypt your data you must use passwords that should not be forgotten years later. For any question, ask sos@sciencespo.fr.

How to deposit your data after your project in data.sciencespo, our repository

Why deposit? You ensure that they are preserved, reused, and shared, thanks to their documentation and associated metadata.

► Depositing = sharing? The choice is yours between open or restricted access. You can choose the persons with whom you wish to share your data (collaborators, reviewers, etc.).  

► Which data? All the data you have produced, a selection of the data you have collected.

► How to download and deposit and your data? Contact us ! And some guidance.

Be careful of the formats! Which file formats are best for tabulated data, text, sound, images, video, etc.?
This question should be posed from the very outset of your research in order to be able to reuse, share, and preserve your data.
Follow the recommendations of UK Data Services:
 Recommended formats

How to name your data

Following rules for file naming will ensure the readability of your data over time. It is essential to establish and share these rules in writing with all the members of your team. Always maintain the same order for the elements of a filename. 

► Sciences Po 7 recommandations

1. Short but meaningful

The filename should contain enough information to be comprehensible beyond its storage location. No redundant or unnecessary information.

DMP.pdf  |data management plan.pdf

RapportActivitePolitis2018.pdf  |rapport d’activité du projet politis 2018.pdf

2. Never use spaces

Distinguish the elements of a filename using capitals, underscores (“_”).

PolitisDMP.pdf  |DMP du projet Politis.pdf

Politis_budget_2019.xls  |Politis budget 19.xls

3. No special characters

Do not use characters with accents or special characters: à é `ù % , { } ! @ $ € & * ().

Politis_Budget_Prev.pdf  |Politis(Budget_Prévisionnel).pdf

Politis_DMP_ethique.pdf  |Politis DMP & éthique.pdf

4. Sorting informations

For records of the same type, always use the same order for the files.

Politis_Budget_2019.pdf et Politis_Rapport_2019.pdf  |Politis_Budget_2019.pdf et Rapport_2019_Politis.pdf

​EntretienSyndicat.wav et EntretienONG.wav  |EntretienSyndicat.wav et ONGEntretien.wav

5. Numbering: identical structure

Always use the same number of characters: e.g., 1-9, 01-99, 001-999, etc.

Politis_entretien01.wav [...] Politis_entretien26.wav  |Politis_entretien1.wav [...] Politis_entretien26.wav

Budget2015.wav [...] Budget2019.wav  |Budget2015.wav [...] Budget19.wav

6. Formatted dates

​​Use numbers only: e.g., YYYY-MM-DD or YYYY-MM or YYYY or YYYY-YYYY.

Politis_CR_20180910  |CR 10 septembre 18

Politis_budget20182019  |budget 2018-19

7. Version

Use the reference “V” followed by a number to indicate the version. Indicate drafts using “Vdraft”.

rapportV01  |rapport version 1

Dernière mise à jour: May 19, 2024 12:15 PM