During a time of thorough transformation towards Open Access and, moreover, Open Science, the field of scholarly communications is facing new challenges. Some of the challenges are related to an aging and somewhat antiquated infrastructure, and others are related to new technologies and the evolving landscape of scientific dissemination, where the disclosure of data is becoming central to and an essential part of research and reproducibility.

In this white paper we highlight three use cases in scholarly communications that need data, and particularly FAIR data, considering these developments.

The use cases are: 

• Artificial intelligence (AI);
• Research integrity; and
• Researcher affiliation identification and disambiguation.