There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Pr...
This report summarizes a presentation by Dr. Michel Dumontier. It reviews innovative scientific rese...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
The current amount of scientific scholarly output is immense. In order to make further progress we h...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
In this review, we discuss FAIR Data, why it exists, and who it applies to. We further review the pr...
This is a review of book titled "Data Stewardship for Open Science: Implementing FAIR Principles", w...
For open science to flourish, data and any related digital outputs should be discoverable and re-usa...
There is a growing demand for quality criteria for research datasets. We will argue that the Data Se...
The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoper...
This report summarizes a presentation by Dr. Michel Dumontier. It reviews innovative scientific rese...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
The current amount of scientific scholarly output is immense. In order to make further progress we h...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
In this review, we discuss FAIR Data, why it exists, and who it applies to. We further review the pr...
This is a review of book titled "Data Stewardship for Open Science: Implementing FAIR Principles", w...
For open science to flourish, data and any related digital outputs should be discoverable and re-usa...
There is a growing demand for quality criteria for research datasets. We will argue that the Data Se...
The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoper...
This report summarizes a presentation by Dr. Michel Dumontier. It reviews innovative scientific rese...
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A dive...
The current amount of scientific scholarly output is immense. In order to make further progress we h...