Directions for Research Data Management in UK Universities

This report addresses five key topics: »» Policy development and implementation »» Skills and capability »» Infrastructure and interoperability »» Incentives for researchers and support stakeholders »» Business case and sustainability

Journal research data policy registry

Presentation on the journal research data policy registry at the Repository Fringe 2015.

Keeping Research Data Safe: a cost model and guidance for UK universities (KRDS1)

This study has investigated the medium to long term costs to Higher Education Institutions (HEIs) of the preservation of research data and developed guidance to HEFCE and institutions on these issues. It has provided an essential methodological foundation on research data costs for the forthcoming HEFCE-sponsored feasibility study for a UK Research Data Service.It will also assist HEIs and funding bodies wishing to establish strategies and TRAC costings for long-term data management and archiving. The rising tide of digital research data raises issues relating to access, curation and preservation for HEIs and within the UK a growing number of research funders are now implementing policies requiring researchers to submit data management, preservation or data sharing plans with their funding applications.

Keeping Research Data Safe 2 (KRDS2)

Data has always been fundamental to many areas of research but in recent years it has become central to more disciplines and inter-disciplinary projects and grown substantially in scale and complexity. There is increasing awareness of its strategic importance as a resource in addressing modern global challenges and the possibilities being unlocked by rapid technological advances and their application in research (NAS2009). The first Keeping Research Data Safe study funded by JISC made a major contribution to understanding of long-term preservation costs for research data by developing a cost model and identifying cost variables for preserving research data in UK universities (Beagrie et al, 2008). The Keeping Research Data Safe 2 (KRDS2) project has built on this work.

The Value of Research Data

Scientific research revolves around the production, analysis, storage, management, and re-use of data. Data sharing offers important benefits for scientific progress and advancement of knowledge. However, several limitations and barriers in the general adoption of data sharing are still in place. Probably the most important challenge is that data sharing is not yet very common among scholars and is not yet seen as a regular activity among scientists, although important efforts are being invested in promoting data sharing. In addition, there is a relatively low commitment of scholars to cite data. The most important problems and challenges regarding data metrics are closely tied to the more general problems related to data sharing. The development of data metrics is dependent on the growth of data sharing practices, after all it is nothing more than the registration of researchers’ behaviour. At the same time, the availability of proper metrics can help researchers to make their data work more visible. This may subsequently act as an incentive for more data sharing and in this way a virtuous circle may be set in motion. This report seeks to further explore the possibilities of metrics for datasets (i.e. the creation of reliable data metrics) and an effective reward system that aligns the main interests of the main stakeholders involved in the process. The report reviews the current literature on data sharing and data metrics. It presents interviews with the main stakeholders on data sharing and data metrics. It also analyses the existing repositories and tools in the field of data sharing that have special relevance for the promotion and development of data metrics. On the basis of these three pillars, the report presents a number of solutions and necessary developments, as well as a set of recommendations regarding data metrics. The most important recommendations include the general adoption of data sharing and data publication among scholars; the development of a reward system for scientists that includes data metrics; reducing the costs of data publication; reducing existing negative cultural perceptions of researchers regarding data publication; developing standards for preservation, publication, identification and citation of datasets; more coordination of data repository initiatives; and further development of interoperability protocols across different actors.

Project report: Journal Research Data Policy Registry

This document is a report from Spotlight Data to Jisc. It describes the project findings and steps required to build a prototype journal research data policy system.

KE Workshop report: Report Knowledge Exchange workshop Making data count - Research Data and Research Assessment

The possibilities of digital research have altered the production, publication and use of research results. Academic research practice and culture are changing or have already been transformed, but to a large degree the system of academic recognition has not yet adapted to the practices and possibilities of digital research. This applies especially to research data, which are increasingly produced, managed, published and archived, but play hardly a role yet in practices of research assessment. The aim of the workshop was to bring experts and stakeholders from research institutions, universities, scholarly societies and funding agencies together in order to review, discuss and build on possibilities to implement the culture of sharing and to integrate publication of data into research assessment procedures. The report 'The Value of Research Data - Metrics for datasets from a cultural and technical point of view' was presented and discussed. Some of the key finding were that data sharing should be considered normal research practice, in fact not sharing should be considered malpractice. Research funders and universities should support and encourage data sharing. There are a number of important aspects to consider when making data count in research and evaluation procedures. Metrics are a necessary tool in monitoring the sharing of data sets. However, data metrics are at present not very well developed and there is not yet enough experience in what these metrics actually mean. It is important to implement the culture of sharing through codes of conducts in the scientific communities. For further key findings please read the report.

Research Data Management — Activities and Challenges Report on the Knowledge Exchange Workshop

Workshop Research Data Management – Activities and Challenges 14-15 November 2011, Bonn The Knowledge Exchange initiative organised a workshop to highlight current activities and challenges with respect to research data management in the Knowledge Exchange partner countries and beyond. The workshop brought together experts from data centres, libraries, computational centres, funding organisations, publishing services and other institutions in the field of research and higher education who are working to improve research data management and encourage effective reuse of research data. A considerable part of the programme was dedicated to sharing perspectives from these communities, leading to the development of a roadmap of practical actions for the Knowledge Exchange initiative, partner organisations and other stakeholders to progress over the next two years. On the first day, principal investigators and project managers from a great variety of recent projects shared their insights on objectives and methods for improving data management ranging from discipline-specific to more general approaches. A series of short presentations of selected projects was followed by an extensive poster session that functioned as a “trade fair” of current trends and activities in the field of research data management. Moreover, the poster session offered ample network opportunities for participants. The second day was dedicated to intensive group discussions looking at a number of data management challenges. First the most important findings from the "Surfboard for 'Riding the Wave'" report were presented. This included the state of the art on activities and challenges in the field of research data management. The subgroups will concentrate on the following key themes: funding, incentives, training and technical infrastructure. These discussions culminated in the identification of practical recommendations for future cooperation on practical as well as on strategic levels that should be taken forward by the KE partner organisations and beyond. These activities aim to improve the sustainability of services and infrastructures at both national and international levels.

KE Workshop Report - Main Drivers for Successful re-use of Research Data

On 23-24 September 2009 an international discussion workshop on “Main Drivers for Successful Re-Use of Research Data” was held in Berlin, prepared and organised by the Knowledge Exchange working group on Primary Research Data. The main focus of the workshop was on the benefits, challenges and obstacles of re-using data from a researcher’s perspective. The use cases presented by researchers from a variety of disciplines were supplemented by two key notes and selected presentations by specialists from infrastructure institutions, publishers, and funding bodies on national and European level. Researchers' perspectives The workshop provided a critical evaluation of what lessons have been learned on sharing and re-using research data from a researcher’s perspective and what actions might be taken on to still improve the successful re-use. Despite the individual differences characterising the diverse disciplines it became clear that important issues are comparable. Combine forces to support re-use and sharing of data Apart from several technical challenges such as metadata exchange standards and quality assurance it was obvious that the most important obstacles to re-using research data more efficiently are socially determined. It was agreed that in order to overcome this problem more efforts should be made to rise awareness and combine forces to support re-using and sharing of research data on all levels (researchers, institutions, publishers, funders, governments).

JRDPR Research Data Policy Survey

Spreadsheet list of discovered journal research data policies, gathered in 2015 as a part of the JRPDR project. Research conducted for Jisc by Research Consulting and Spotlight Data. Underpins project final report [http://repository.jisc.ac.uk/6264/ ]

Data for research data policy registry final report

Underpins final report at: http://repository.jisc.ac.uk/6264/ Spreadsheet of discovered research data journal policies, collected late 2015.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

The varieties of student experience - an open research question and some ways to answer it

Based on meetings of the Society for Research into Higher Education’s Student Experience Network over the past three years, the genuinely open research question is posed whether there is one or more undergraduate student experience within English higher education. Answering this question depends on whether what is taught or what is learnt is examined. If the latter, then a unitary student experience can be said to exist only in the narrowest of normative senses. What undergraduates actually learn – defined in the widest sense – is the $64,000 question of research on the student experience. Various ways to answer this question are proposed, including using students to research students. Conceptual tools to apply to findings can be developed from youth studies and cognate disciplines, particularly in relation to student identities and aspirations. Lastly, these proposals are placed in the wider context of comparative models of the varieties of student experience, including those emerging in the UK’s national regions.

D10.2 - Research Data Management Plan, version 1.0

This document is the first out of three iterations of the DMP that will be formally delivered during the project. Version 2 is due in month 24 and version 3 towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. In this first version we describe the planned research data sets related to the RAGE evaluation and validation activities, and the fifteen principles that will guide data management in RAGE. The former are described in the format of the EU data management template, and the latter in terms of their guiding principle, how we propose to implement them, and when they will be implemented. This document is thus first of all relevant to WP5 and WP8 members.