A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques

2021 ◽  
pp. 48-67
Author(s):  
Madhavi Arun Vaidya ◽  
Meghana Sanjeeva
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Big Data ◽  
Data Management ◽  
Large Volume ◽  
Research Data ◽  
Research Data Management ◽  
Visualization Tools ◽  
Using Data ◽  
Analytical Frameworks

Research, which is an integral part of higher education, is undergoing a metamorphosis. Researchers across disciplines are increasingly utilizing electronic tools to collect, analyze, and organize data. This “data deluge” creates a need to develop policies, infrastructures, and services in organisations, with the objective of assisting researchers in creating, collecting, manipulating, analysing, transporting, storing, and preserving datasets. Research is now conducted in the digital realm, with researchers generating and exchanging data among themselves. Research data management in context with library data could also be treated as big data without doubt due its properties of large volume, high velocity, and obvious variety. To sum up, it can be said that big datasets need to be more useful, visible, and accessible. With new and powerful analytics of big data, such as information visualization tools, researchers can look at data in new ways and mine it for information they intend to have.

scholarly journals Gathering Evidence of Benefits: A Structured Approach from the Jisc Managing Research Data Programme

2013 ◽  
Vol 8 (2) ◽  
pp. 123-133
Author(s):  
Laura Molloy ◽  
Simon Hodson ◽  
Meik Poschen ◽  
Jonathan Tedds
Keyword(s):  
Higher Education ◽  
Data Management ◽  
Research Funding ◽  
Research Data ◽  
Lessons Learned ◽  
Education Sector ◽  
Research Data Management ◽  
The Uk ◽  
Uk Higher Education ◽  
Structured Approach

The work of the Jisc Managing Research Data programme is – along with the rest of the UK higher education sector – taking place in an environment of increasing pressure on research funding. In order to justify the investment made by Jisc in this activity – and to help make the case more widely for the value of investing time and money in research data management – individual projects and the programme as a whole must be able to clearly express the resultant benefits to the host institutions and to the broader sector. This paper describes a structured approach to the measurement and description of benefits provided by the work of these projects for the benefit of funders, institutions and researchers. We outline the context of the programme and its work; discuss the drivers and challenges of gathering evidence of benefits; specify benefits as distinct from aims and outputs; present emerging findings and the types of metrics and other evidence which projects have provided; explain the value of gathering evidence in a structured way to demonstrate benefits generated by work in this field; and share lessons learned from progress to date.

Research data management practice in higher education institutions in Ethiopia

2021 ◽  
Vol 17 (4) ◽  
pp. 213-230
Author(s):  
Alehegn Adane Kinde ◽  
Assefa Chekole Addis ◽  
Getachew Gedamu Abebe
Keyword(s):  
Higher Education ◽  
Data Management ◽  
Management Practice ◽  
Higher Education Institutions ◽  
Research Data ◽  
Research Data Management

scholarly journals HPC-Cloud-Big Data Convergent Architectures and Research Data Management: The LEXIS Approach

2021 ◽  
Author(s):  
Stephan Hachinger ◽  
Jan Martinovič ◽  
Olivier Terzo ◽  
Marc Levrier ◽  
Alberto Scionti ◽  
...  
Keyword(s):  
Big Data ◽  
Data Management ◽  
Research Data ◽  
Research Data Management ◽  
Hpc Cloud

scholarly journals Research Data Management in a cultural heritage organisation

2020 ◽  
Vol 14 (1) ◽  
pp. 199-227
Author(s):  
Tom Drysdale
Keyword(s):  
Higher Education ◽  
Cultural Heritage ◽  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Research Data Management ◽  
Core Function ◽  
The Many ◽  
Management Audit ◽  
Uk Higher Education

Research is a core function of cultural heritage organisations. Inevitably, the undertaking of research by galleries, libraries, archives and museums (the GLAM sector) leads to the creation of vast quantities of research data. Yet despite growing recognition that research data must be managed if it is to be exploited effectively, and in spite of increasing understanding of research data management practices and needs, particularly in the higher education sector, knowledge of research data management in cultural heritage organisations remains extremely limited. This paper represents an attempt to address the limited awareness of research data management in the cultural heritage sector. It presents the results of a data management audit conducted at Historic Royal Palaces (HRP) in 2018. The study reveals that research data management at HRP is underdeveloped, while highlighting some causes for optimism. The results of the study are compared to the results of similar studies conducted in UK higher education institutions (HEIs), highlighting the many discrepancies in the ways that research data is managed at HRP and in the HE sector. Recognition of these differences and similarities, it is argued, is necessary for the development of better research data management practices and tools for the heritage sector.

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