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

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.

2014 ◽  
Vol 9 (2) ◽  
pp. 47-64
Author(s):  
Sarah Jones ◽  
Jonathan Rans ◽  
Diana Sisu ◽  
Angus Whyte

This paper shares results from the Digital Curation Centre’s programme of Institutional Engagements (IEs), and describes how we continue to provide tailored support on Research Data Management (RDM) to the UK higher education sector.Between Spring 2011 and Spring 2013, the DCC ran a series of 21 Institutional Engagements. The engagement programme involved helping institutions to assess their needs, develop policy and strategy, and begin to implement a range of RDM services.We have conducted a synthesis and evaluation of the programme, analysing the types of assistance requested and the impact of our support. The findings and lessons to emerge from these exercises have informed our future strategy and helped reshape the programme.


2020 ◽  
Vol 14 (1) ◽  
pp. 199-227
Author(s):  
Tom Drysdale

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.


First Monday ◽  
2017 ◽  
Vol 22 (5) ◽  
Author(s):  
Katy Jordan

Web link mining has been previously used as a way of gaining insight into how the Internet may be replicating or reshaping connections between institutions within the higher education sector. Institutions are increasingly active on social media platforms, and these connections have not been studied. This paper presents an exploratory analysis of the network of UK higher education institutional accounts on Twitter. All U.K. institutions have a presence. Standing in recent university rankings is found to be a significant predictor of several network metrics. In examining the communities present within the network, a combination of ranking and geolocation play a role. Analysis of a sample of tweets which mention more than one U.K. higher education institution provides an indication of why the topics of tweets would reinforce prestige and location in the network structure.


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