Future models and architecture of data repositories in African universities

Research data repositories as part of research infrastructures are being developed and are important tools and components that help to store, preserve, and allow for the re-use of data. As the technologies, networks, and systems that the data repositories are built upon are advancing, this study explores the future models and architectures that African universities can follow to have reliable and sustainable systems for the preservation of research data. A scoping review was done to focus on the future shape of data repositories based on past experiences of the last 10 years of research institutions in establishing data repositories. This study was done to gauge the communities’ responses to the architecture of existing platforms to prepare other institutions planning to establish digital research data repositories. Articles were retrieved from Scopus, Web of Science, and Dimensions databases using relevant keywords. The content analysis approach was used to establish the requirements for establishing digital research data repositories to develop a framework that can be utilised by other research institutions to develop their repositories. The framework would be handy in providing a roadmap for research institutions that want to establish research data services in Africa enhancing the future of research infrastructure in African universities.

Authors

Institutions

Publication Details

Journal
IASSIST Quarterly
Published
2024-09-27
DOI
https://doi.org/10.29173/iq1099
Citations
1
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Future models and architecture of data repositories in African universities

Josiline Phiri Chigwada, Elisha Chiware
1 citations
IASSIST Quarterly
Research Data Management Practices
0.78
article

Future models and architecture of data repositories in African universities

Josiline Phiri Chigwada, Elisha Chiware
article en
1 citations

Abstract

Research data repositories as part of research infrastructures are being developed and are important tools and components that help to store, preserve, and allow for the re-use of data. As the technologies, networks, and systems that the data repositories are built upon are advancing, this study explores the future models and architectures that African universities can follow to have reliable and sustainable systems for the preservation of research data. A scoping review was done to focus on the future shape of data repositories based on past experiences of the last 10 years of research institutions in establishing data repositories. This study was done to gauge the communities’ responses to the architecture of existing platforms to prepare other institutions planning to establish digital research data repositories. Articles were retrieved from Scopus, Web of Science, and Dimensions databases using relevant keywords. The content analysis approach was used to establish the requirements for establishing digital research data repositories to develop a framework that can be utilised by other research institutions to develop their repositories. The framework would be handy in providing a roadmap for research institutions that want to establish research data services in Africa enhancing the future of research infrastructure in African universities.

IASSIST QuarterlyVol. 48(3)
Cape Peninsula University of Technology (ZA), University of South Africa (ZA)
Openalex Percentile: Top 21%
Research Data Management Practices
0.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.