The FAIR (Findability, Accessibility, Interoperability, Reusability) principles were created by experts in the integration of data on scientific activity into electronic information systems in order to make this data accessible, compatible, and legally reusable.

Finding, Accessibility, Interoperability, and Reusability (findability, accessibility, compatibility, and reuse) are the four guiding principles of FAIR data. A common abbreviation, FAIR, is sometimes known as "fair." These principles were presented in a March 2016 article in the journal Scientific Data by a consortium of several scientists and organizations.

The FAIR principles focus on automatic processing capabilities - that is, the ability of computing systems to find, access, interact and reuse data without human intervention or with minimal human intervention - this is necessary due to the constant growth in the volume, complexity and speed of information.

The main FAIR data principles

Findable 

In order to make good use of data, you have first to go out and get it. For both people and computers, metadata and data must be readily accessed through search engines. As part of the FAIRification process, metadata that can be interpreted by computers must be provided.

• F1. (Meta)data is assigned a globally unique and permanent identifier

• F2. Data is described using extended metadata (defined below in clause R1). 

• F3. Metadata clearly and explicitly includes the identifier of the data it describes.

• F4. (Meta)data is registered or indexed in a system with search capabilities.

Accessible 

Once the data is located, the user must determine how to get access to it, maybe considering authentication and authorization.

• A1. (Meta)data can be retrieved by their ID using a standardized communication protocol. A1.1 The protocol is open, free, and universally implementable.

• A1.2 The protocol allows an authentication and authorization procedure where appropriate.

• A2. Metadata remains available even when the data itself is no longer available. 

Interoperable

The majority of the time, data must be linked to other data. Data must also connect with other apps or processes for analysis, storage and processing. 

• I1. (Meta)data uses a formal, accessible, common and widely used language to represent knowledge.

• I2. (Meta)data uses vocabularies that follow the FAIR principles.

• I3. (Meta)data includes qualified links to other (meta)data. 

Reusable 

As a result of FAIR, data reuse will be maximized. Metadata and data must be well-described so that they may be copied and/or integrated under diverse circumstances.

• R1. Meta(data) is detailed with many precise and relevant properties.

• R1.1. (Meta)data is published with a clear permissive license.

• R1.2. (Meta)data associated with a detailed description of the origin.

• R1.3. (Meta)data complies with community standards relevant to the subject area.

Data (or any digital entity), metadata (information about that digital thing), and infrastructure are all included in the FAIR principles. F4 states that metadata and data should be recorded or indexed in a searchable database.

SciNote ELN

SciNote ELN is the ability to create a large-scale searchable database, which saves a lot of time. For example, SciNote users can save up to 9 hours per week! 

In addition, the flexibility of SciNote ensures that all your data is organized in the way that is most convenient for you. It gives structure and context to all your notes, Excel sheets, spreadsheets, checklists or images. 

By the way, it takes, on average, 1 week for a user to become an advanced SciNote user and fully customize their own system in SciNote. But if you have any difficulties with the development of ELN, SciNote implementation specialists will solve any of your problems.