Interfacing Natural Language Processing (NLP) Tools with Open Access Publications

Scientific publications are valuable, and open research data (ORD) like open access publications have made scientific knowledge more accessible. However, merely accessing this data is insufficient; we must extract and utilize the knowledge within. Traditional keyword-based search engines have limitations. As Natural Language Processing (NLP) techniques advance, we can improve tasks like discovering, reviewing, summarizing, and generating discussions from scientific literature. Our proposal aims to enhance the value of open access scientific content by creating an OR database with over 140 million papers and providing access to cutting-edge NLP tools. We plan to publish the database's code and content, offer an API, and run a web-based application using NLP to assist scientific manuscript authors in assimilating literature. These efforts facilitate knowledge utilization, streamline scientific discovery, and aid in writing processes.