Research data

Research data (RD) is the set of information collected, observed or created, in a digital form or not, by the research research teams as part of a research project.

Research data is information from which hypotheses are built. A product of research, they are an element of scientific communication and bring together a heterogeneous set of research sources and materials.

They are generally defined according to their level of completion:

"hot" data

• Raw data : collected, not organized, not formatted.

• Processed data : organized, structured, and ready for analysis.

"cold" data

• Analyzed data : completed, they allow the production of publications and theses, and will be archived for their eventual reuse.

Research data are concrete elements that the scientific community accepts as necessary to document and validate research results.

They concern, in addition to the research community, the professions that support research (documentation, archives (documentation, archives, computer science, scientific and technical information, ...).

Each of these professions plays an essential role in the life cycle of data.

What does it mean to "manage your data"?

Research data management encompasses all the operations of collecting, describing, storing, processing and accessing the data produced during a research project.

It covers the entire life cycle of the project and beyond: creation, dissemination, conservation of data, with a view to their preservation and/or reuse.

Data management is part of the research process. Project leaders have a particular responsibility towards their institution and the agency that funds their research.

Ensuring quality, archiving and sharing data is a requirement of public funders who often link funding of research projects to the opening of data.

To put it simply, this means:

• accompanying your data throughout the life cycle of the research project (creation, processing, analysis, sharing and reuse);

• organizing them from the start of the project ;

• saving regularly the data you use (so-called "hot" data);

• preserving/archiving "cold" data, and making them accessible for reading and future use;

• respecting ethical rules for their sharing.

Data life cycle

The data life cycle gathers all the steps for managing, preserving and disseminating research data, associated with research activities.

It includes 6 steps :

1. planning
2. creation / collection
3. processing / analysis
4. access / sharing
5. preservation
6. reuse

The Data Management Plan (DMP)

The management of research data is facilitated by the creation of a data management plan - or Data Management Plan, DMP.

A data management plan is a formal document explaining how you obtain, document, analyze and use your data during your research and after the project is completed. It describes in detail the methods and processes for creating, providing, maintaining, preserving and protecting data.

Since 2019 this deliverable is required by most national and european funders. It determines the payment of the budget and allows to report all the resources used to manage the data of the project.

The drafting of the data management plan is starting to become widespread, beyond the projects funded. The French Decree No. 2021-1572 of December 3, 2021 on the respect of scientific integrity requirements by public institutions devotes its article 6 to this.

[...] The public establishments and foundations recognized as being of public utility mentioned in the third paragraph of the'article L. 211-2 of the research code define a policy of conservation, communication and re-use of the raw results of the scientific work carried out within it.carried out within it. To this end, they ensure that their staff implement data management plans and contribute to the infrastructures that allow the conservation, communication and reuse of data and source codes.[...]

It allows to :

- make data reliable and facilitate their management;

- anticipate and promote their eventual disseminationn ;

- describe how the scientific data of a research project will be produced, processed, disseminated, protected...

In short:

- The DMP specifies what data is collected or generated, how it is managed, shared and preserved during and after the project.

- It is THE best practice for any research project generating data.

- It is required by funding agencies and public institutions.

- It is a a concrete project management tool.