A Novel Tightly Coupled Information System for Research Data Management

Author:

Senagi KennedyORCID,Tonnang Henri E. Z.

Abstract

Most research projects are data driven. However, many organizations lack proper information systems (IS) for managing data, that is, planning, collecting, analyzing, storing, archiving, and sharing for use and re-use. Many research institutions have disparate and fragmented data that make it difficult to uphold the FAIR (findable, accessible, interoperable, and reusable) data management principles. At the same time, there is minimal practice of open and reproducible science. To solve these challenges, we designed and implemented an IS architecture for research data management. Through it, we have a centralized platform for research data management. The IS has several software components that are configured and unified to communicate and share data. The software components are, namely, common ontology, data management plan, data collectors, and the data warehouse. Results show that the IS components have gained global traction, 56.3% of the total web hits came from news users, and 259 projects had metadata (and 17 of those also had data resources). Moreover, the IS aligned the institution’s scientific data resources to universal standards such as the FAIR principles of data management and at the same time showcased open data, open science, and reproducible science. Ultimately, the architecture can be adopted by other organizations to manage research data.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference82 articles.

1. A World that Counts: Mobilising the Data Revolution for Sustainable Development. The United Nations Secretary Generalhttps://www.undatarevolution.org/wp-content/uploads/2014/11/A-World-That-Counts.pdf

2. Behind every great research project is great data management

3. Big Data Curation

4. Principles of Information Systems A Managerial Approach;Ralph,2016

5. The FAIR Guiding Principles for scientific data management and stewardship

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