Research papers in various fields such as natural sciences, humanities, social sciences, etc. that are released online have disappeared online due to the closure of the website and are not easily accessible. In order to preserve an environment where anyone can easily read research papers, the non-profit internet archive focuses on archives of research papers aimed at storing all research papers on the web.
Research papers on the web can be viewed online for free through Internet archives as well as open access journals. Since this research paper is easily accessible from anywhere in the world, it has supported many student and researcher studies.
However, it became difficult to read research papers due to the closure of the open access journal website. Research shows that between 2000 and 2019, 176 open access journals disappeared from the web. Internet Archive’s Wayback Machine was organized to solve the problem of content loss caused by website closure. In fact, there are many research papers that can only be viewed on the Wayback Machine.
In 2017, the Internet Archive launched a project focused on storing all research papers with public access funded by the Andrew Melon Foundation and the Caleostin Foundation. In this project, the Internet Archive has been archiving 14.8 million research papers published on the web since 1996. The number of papers disappeared from the web is increasing year by year, but more than that, the Internet archive has succeeded in storing numerous research papers, and it is said that more than 9.1 million research papers are currently stored.
The Internet Archive said its goal is to archive as many research papers on the web as possible. To keep up with the increasing number of new research papers released every day, Wayback Machine’s vast web content can be traced back to 1996 to find content that cannot be easily found. He said the goal was to do it. He added that he wants to make research papers and research materials available on the web permanently, and that he wants to provide new methods, including large datasets. Related information can be found here .