Research Institutions

The research data management platform GakuNin RDM provides academic institutions with a secure platform for storing and managing academic resources within the institution. This is especially necessary, in terms of accountability and research transparency purposes, whenever academic institutions are responsible for research outputs within their institution.
The repository platform (WEKO3) and discovery platform (CiNii Research) provides a base where academic institutions can publish their research outputs, and thus present the institution's scholarly achievements to the public. Academic institutions are expected to encourage affiliated researchers to archive their research outputs on the platform.

GakuNin RDM features a trail management function that uses time stamps from a third-party time authentication authority, allowing one to prove that the data stored in a system existed at a particular time. This is also a powerful function from the perspective of research integrity.

Published research outputs in WEKO3 are disseminated in human-readable formats on the Web and in a machine-readable format. For example, WEKO3 supports metadata provision protocol by OAI-PMH and ResourceSync. WEKO3 also supports sitemap and Google Scholar meta tag, and Open Graph Protocol for social services.

WEKO3 has a function to automatically publish research outputs on a specific date (embargo function). For example, WEKO3 allows setting the publication settings such as making the registered research outputs accessible only within a particular institution and, after one year, making it available to the public.

WEKO3 manages and publishes the research outputs of academic institutions in units of items. The item type represents the metadata of the item and can be flexibly customized by the user institution. By mapping the customized item type to a specific XML schema, metadata output using the XML schema is possible.

In order to ensure the reliability of results published in papers, researchers are required to publish the data on which they base their findings. However, unless the programs used to process the data are also made available, other researchers will not be able to reproduce the results. With the NII RDC Computational Services, the program used for data processing and its execution environment can be packaged, linked to the paper and data, and publicated so that the results can be reproduced by anyone.

In order to develop and execute a program, an execution environment including hardware and middleware must be properly provisioned, which is a difficult task for many researchers. With the NII RDC Computational Services, the execution environment can be packaged and stored in GakuNin RDM, and collaborators and/or students can rebuild the same execution environment with a single click.

In the "Design and Practice of Research Data Management Services" course, you will learn what you need to know to support research data management. Research data has a lifecycle: how it is generated, stored, and finally reused. In this course, you will learn about service design, pre-research support, in-research support, post-research support, and day-to-day support in a way that follows the research data lifecycle.

In "Research Data Management for Researchers," researchers at universities and research institutions can learn the knowledge required for each situation in research data management. The textbook is divided into thematic sections to provide the necessary expertise efficiently.

GakuNin LMS allows the person in charge of the institution to view students' enrollment status at each institution based on their login information linked to GakuNin Federation. This supports systematic course management by the person in charge of the institution and provides primary data for efficient provision and evaluation of course materials according to the students' attributes.

In order to achieve data governance, academic institutions should continuously monitor the research data management status of their researchers to understand what research data is being generated, managed, published, and reused as assets within the organization. Manually checking these tasks can be a huge burden for both the institution and the researchers. Therefore, the Data Governance Platform aims to semi-automatically collect research data information from the research data environment, and to support the generation of statistical information and reports.

For researchers to use research data in the humanities and social sciences, it is necessary to look up the institutions that publish research data and search for the research data that meets their needs in each institution's repository. As an environment for centrally exploring each institution's research data, we are developing Japan Data Catalog for the Humanities and Social Sciences (JDCat) on behalf of the Project for Promotion of the Construction of a Data Infrastructure for the Humanities and Social Sciences.

There are some contents of research data that are not desirable to share through public disclosure. In medicine and social sciences, from the perspective of protecting human research subjects' privacy, research data is not made available for anyone to access, but only to users who meet the conditions. This type of research content provision is called restricted access, and more than 40% of the world's research data repositories support this type of content provision.