AMIDER: A Multidisciplinary Research Database and Its Application to Promote Open Science

TL;DR

AMIDER is a newly developed multidisciplinary research database with user-friendly features and advanced functions aimed at enhancing open science and collaboration across scientific disciplines.

Contribution

The paper introduces AMIDER, a comprehensive multidisciplinary research database with innovative visualization, data management, and accessibility features for promoting open science.

Findings

Over 15,000 metadata entries in polar science as of July 2024

Approximately 500 daily website visitors

Successful implementation of visualization and data management functions

Abstract

The AMIDER, Advanced Multidisciplinary Integrated-Database for Exploring new Research, is a newly developed research data catalog to demonstrate an advanced database application. AMIDER is characterized as a multidisciplinary database equipped with a user-friendly web application. Its catalog view displays diverse research data at once beyond any limitation of each individual discipline. Some useful functions, such as a selectable data download, data format conversion, and display of data visual information, are also implemented. Further advanced functions, such as visualization of dataset mutual relationship, are also implemented as a preliminary trial. These characteristics and functions are expected to enhance the accessibility to individual research data, even from non-expertized users, and be helpful for collaborations among diverse scientific fields beyond individual disciplines. Multidisciplinary data management is also one of AMIDER's uniqueness, where various metadata schemas can be mapped to a uniform metadata table, and standardized and self-describing data formats are adopted. AMIDER website (https://amider.rois.ac.jp/) had been launched in April 2024. As of July 2024, over 15,000 metadata in various research fields of polar science have been registered in the database, and approximately 500 visitors are viewing the website every day on average. Expansion of the database to further multidisciplinary scientific fields, not only polar science, is planned, and advanced attempts, such as applying Natural Language Processing (NLP) to metadata, have also been considered.