Investigating a secure and scalable infrastructure for experimental data management by using distributed PDS in developmental research

Abstract

In developmental psychology research focused on infants, several experiments have been conducted, primarily within controlled laboratory settings, and many results have been obtained. However, these datasets are limited to fragmentary records within a specialized laboratory context, limited by time and scope. To tackle such restrictions, we believe that collecting data in real-world environments will be necessary. In view of this, we have developed GO-E-MON, an online experiment platform leveraging a distributed personal data store (PDS), for conducting experiments in real-world settings. GO-E-MON is designed to provide the requisite security protocols for real-world experimentation with distributed PDS, while also being scalable for large-scale use and seamless integration with external systems. We are using GO-E-MON as our experimental environment for real-world-oriented experiments with high school students’ learning. We present a case study illustrating its application. In addition, we believe that the development of an online experimental platform capable of safeguarding personal data represents an important issue in infant research oriented toward real-world applications.