Making Reproducible Research Data by Utilizing Persistent ID Graph Structure

globally, in order to share the achievements of science, we open the published papers that are the output of scientific research. In addition, research data as supplemental data of the paper, and source data that is generated as a large amount of volumes of data from various experimental equipment are disclosed and shared to all researchers. This research data is enabling to grow and improve scientific research, quickly. In Europe, as open research data are archived enough, projects (EOSC, REANA, WES-ELIXIR, and so on) are being actively conducted for research environments in which researchers analyze and reproduce research data. Major publishers are also supporting the publication of open accessed papers and their supplemental data in keeping with the flow of open science, and developing platforms to support researchers' research activities. Therefore, in this paper, we design a system that can reproduce data analysis and research environment of researchers who published existing papers. The data structure in the proposed system utilizes a PID graph that connects papers, research data, and software. We analyze the functional requirements for building the system.