VIRTUAL RESEARCH ENVIRONMENTS AND THEIR COMPONENTS AND TOOLS

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INTRODUCTION

Virtual Research Environments (VREs) as technology frameworks to facilitate collaborative research projects have been used by a number of universities and research institutions globally. VREs “are an intricate part of e-Research and comprise of digital infrastructure and services (online tools, content, and middleware), which enable research to take place within the virtual multi-disciplinary and multi-organisation partnership context. The specific aim of a VRE is to help researchers manage the increasingly complex range of tasks involved in carrying out research” (Van Deventer, et al., 2009). According to Fraser (2005), VREs arose from the development of e-Science and are intrinsically linked to e-Science. Fraser (2005) also includes cyberinfrastructure and e-infrastructure as part of VREs. He compares them to “Managed Learning Environments (sum of services and systems which together support the learning and teaching processes)” rather than virtual learning environments (VLEs). Fraser regards VREs as “the result of joining together new and existing components to support as much of the research process as appropriate for any given activity or role” (Fraser, 2005). For the purposes of this study, a component is seen as a “uniquely identifiable input, part, piece, assembly or subassembly or subsystem” that is needed to perform “a distinctive and necessary function in the operation of a system” (Business Dictionary, 2018).

Research Design

In this section, a brief overview is provided of the research design followed in this study (for a more detailed overview, see Chapter 6). This study follows an interpretivist paradigm, with a focus on empirical interpretivism. Empirical interpretivism focuses on the investigation of social phenomena in natural settings (Pickard, 2007: 11), which is ideal when studying a VRE as a ‘social
phenomenon’ in its natural setting.

Case Studies

The empirical part of the study, which focuses on two case studies, is covered in Chapter 7. In this chapter, the results gained through a formative evaluation process, are discussed, followed by a discussion of results gained from a summative evaluation process through interview questions. Data from these case studies were collected through a method of Participatory Action Research (PAR) in conjunction with prototyping, by using the following data collection tools: observation, semi-structured interviews, and testing/experimenting.

Research Data Management (RDM)

This chapter starts with an overview of the concepts data and research data, as well as related concepts, and how each relates to RDM. The discussion also includes the concepts data curation, data stewardship, data governance, data archiving, and data management. RDM is then defined, followed by an overview of a number of international developments with regards to RDM. Thereafter, the different approaches to RDM are compared and the similarities and differences highlighted. The South African situation with regard to RDM is examined next, discussing government initiatives, national collaborative initiatives, initiatives at higher education institutions, other initiatives and potential partners. After this, the concept of a research data lifecycle is explored by comparing a number of cycles from literature, followed by a discussion of the different stages of a research cycle as well as the corresponding processes that takes place in each, and the potential role that the various stakeholders can play in each. The chapter is concluded with a discussion on the processes that takes place throughout the whole lifecycle.

Declaration
ACKNOWLEDGEMENTS
ABSTRACT
CHAPTER 1: INTRODUCTION
1.1 CONTEXT OF THE RESEARCH PROBLEM
1.2 RESEARCH PROBLEM / QUESTION
1.3 RELEVANCE OF STUDY FOR THE SUBJECT FIELD
1.4 RESEARCH METHODOLOGY
1.4.1 Research Design
1.4.2 Literature Review
1.4.3 Case Studies
1.4.4 Methods Of Analysis
1.5 LIMITATIONS OF THE STUDY
1.6 STRUCTURE OF THE THESIS
1.7 EXPOSITION OF CHAPTERS
1.8 SUMMARY
CHAPTER 2: VREs AS PART OF E-RESEARCH INFRASTRUCTURE, AND OTHER CONCEPTS RELATED TO VREs
2.1 INTRODUCTION
2.2 KEY CONCEPTS
2.2.1 E-Science
2.2.2 Cyberinfrastructure
2.2.3 Science Gateways
2.2.4 Cyberscience
2.2.5 E-Research
2.2.5.1 Approaches to e-Research
2.2.6 Collaboratories
2.2.7 Web-Based Research Support Systems (WRSS)
2.2.7.1 Institutional Level: Research Support For Management Personnel
2.2.7.2 Research Support For Individual Researchers
2.2.8 Virtual Research Environments (VREs)
2.2.8.1 What Is A VRE?
2.2.8.2 The Aim Of A VRE
2.2.8.3 Characteristics Of A VRE
2.3 DIFFERENCES AND SIMILARITIES WITH THE CONCEPTS CYBER-INFRASTRUCTURE, CYBERENVIRONMENTS, COLLABORATORIES AND SCIENCE GATEWAYS
2.4 SUMMARY
CHAPTER 3: VIRTUAL RESEARCH ENVIRONMENTS AND THEIR COMPONENTS AND TOOLS
3.1 INTRODUCTION
3.2 AN OVERVIEW OF THE DEVELOPMENT OF VREs ACROSS THE WORLD, FOCUSING ON THE UNITED KINGDOM, THE USA, THE NETHERLANDS AND GERMANY
3.2.1 United Kingdom
3.2.2 USA
3.2.3 The Netherlands
3.2.4 Germany
3.3 SIMILARITIES AND DIFFERENCES BETWEEN THE VRE PROGRAMMES IN THE UK, THE USA, THE NETHERLANDS, AND GERMANY
3.3.1 Organisational Aspects
3.3.2 Technical Aspects
3.3.3 Functional Aspects
3.3.4 Policy / Legal / Financial Aspects
3.3.5 Cultural Aspects
3.4 RESEARCH CYCLES AND VRE COMPONENTS
3.4.1 Research Cycles
3.4.2 VRE Components
3.5 POSSIBLE CONCEPTUAL VRE FRAMEWORK
3.5.1 Keraminyage, Amaratunga And Haigh’s (2009b: 129-142) Visualised Structure Of A VRE
3.5.2 De Roure et al.’s (2009) Illustration of the myExperiment Architecture
3.5.3 Simeoni et al.’s (2008) Illustration Of gCube Architecture / Framework
3.5.4 Yang And Allan’s (2007) Service-Orientated Architecture (SOA) For VRE Systems
3.5.5 Mclennan And Kennell’s (2010) Illustration Of Hubzero
3.5.6 Fernihough’s (2011: 101) E-Research Implementation Framework For South African Organisations
3.5.7 Proposed Conceptual Model Of A VRE And Its Components
3.5.7.1 The Human Components Layer
3.5.7.2 Hardware Components Layer
3.5.7.3 Software Components Layer
3.5.7.4 Management Services Component (Vertical Layer In Green)
3.5.7.5 Standards, Protocols And Specifications (Vertical Layer In Amber)
3.5.7.6 Policy Components (Vertical Layer In Red)
3.5.7.7 Research Cycle
3.6 SUMMARY
CHAPTER 4: RESEARCH DATA MANAGEMENT (RDM)
4.1 INTRODUCTION
4.2 KEY CONCEPTS
4.2.1 Data
4.2.2 Research Data
4.2.3 The Concept ‘Research Data Management’
4.2.3.1 Data Curation
4.2.3.2 Data Stewardship
4.2.3.3 Data Governance
4.2.3.4 Data Archiving
4.2.3.5 Data Management
4.2.3.6 RDM
4.2.3.7 Critical Summary
4.3 INTERNATIONAL RDM INITIATIVES
4.3.1 Introduction
4.3.2 UK
4.3.2.1 The UK Data Archive
4.3.2.2 UK Data Service
4.3.2.3 The Digital Curation Centre (DCC)
4.3.2.4 JISC
4.3.2.5 Other Significant Developments In The UK
4.3.3 The European Union (EU)
4.3.3.1 Consortium Of European Social Science Data Archives (CESSDA)
4.3.3.2 The European Strategy Forum On Research Infrastructures (ESFRI)
4.3.3.3 EUDAT
4.3.3.4 European Cloud Initiative
4.3.3.5 European Data Portal
4.3.3.6 Open Research Data Pilot
4.3.3.7 Other significant RDM initiatives in the EU
4.3.4 USA
4.3.5 Australia
4.3.5.1 National Collaborative Research Infrastructure Strategy (NCRIS)
4.3.5.2 Australian National Data Service (ANDS)
4.3.5.3 Data Storage Infrastructure (RDSI) Project
4.3.5.4 Other Significant Developments In Australia
4.3.6 Comparisons Between RDM Developments In The UK, EU, USA And Australia
4.3.7 International Collaborative Initiatives
4.3.7.1 Committee On Data For Science And Technology (CODATA)
4.3.7.2 World Data System
4.3.7.3 Research Data Alliance
4.3.7.4 DataCite
4.3.7.5 International Federation Of Data Organisations For Social Science(IFDO)
4.4 RDM DEVELOPMENTS IN SOUTH AFRICA
4.4.1 The Context
4.4.2 Government Initiatives
4.4.2.1 National Integrated Cyber-Infrastructure System (NICIS)
4.4.2.3 Human Sciences Research Council (HSRC)
4.4.2.4 Council For Scientific And Industrial Research (CSIR)
4.4.2.5 South African Data Archive (SADA)
4.4.2.6 South African National Parks (SANParks)
4.4.3 National Collaborative Initiatives
4.4.3.1 African Research Cloud (ARC)
4.4.3.2 Inter-University Institute For Data Intensive Astronomy (IDIA)
4.4.3.3 The Digitisation And Digital Data Preservation Centre
4.4.3.4 Network Of Data And Information Curation Communities (NeDICC)
4.4.3.5 African Open Science Platform
4.4.3.6 Seminar Hosted By DST, HSRC, And UP On 5 November 2012
4.4.3.7 The South African Astroinformatics Alliance (SA³)
4.4.3.8 The South African Biodiversity Information Facility (SABIF)
4.4.3.9 The Western Cape Data Intensive Research Facility (WCDIRF)
4.4.4 Initiatives At South African Higher Education Institutions
4.4.4.1 Cape Peninsula University Of Technology (CPUT)
4.4.4.2 Nelson Mandela University (NMU)
4.4.4.3 Sol Plaatje University (SPU)
4.4.4.4 Stellenbosch University (SU)
4.4.4.5 University Of Cape Town (UCT)
4.4.4.6 University Of Kwa-Zulu-Natal (UKZN)
4.4.4.7 University Of Pretoria (UP)
4.4.4.8 University Of South Africa (UNISA)
4.4.4.9 University Of The Western Cape
4.4.4.10 University Of The Witwatersrand (WITS)
4.4.5 Other Initiatives
4.4.5.1 Southern African Large Telescope (SALT)
4.4.5.2 Square Kilometre Array (SKA)
4.4.5.3 The Africa Centre For Population Health
4.4.6 Potential Partners In RDM In South Africa
4.4.6.1 Southern African Research And Information Management
Association (SARIMA)
4.5 RESEARCH DATA LIFECYCLE
4.5.1 Introduction
4.5.2 Stages Of The Research Data Lifecycle
4.5.2.1 Creating Data Stage
4.5.2.2 Processing Data Stage
4.5.2.3 Analysing Data Stage
4.5.2.4 Preserving Data Stage
4.5.2.5 Giving Access To Data Stage: Data Sharing
4.5.2.6 Re-Using Data Stage
4.5.2.7 Processes / Actions Taking Place Through The Whole Research Data Lifecycle: Data Provenance
4.6 THE MANAGEMENT OF BIG DATA
4.7 THE VALUE OF RDM
4.8 RDM AT THE UNIVERSITY OF PRETORIA (UP)
4.8.1 First Initiatives
4.8.2 Survey – August-October 2013
4.8.3 Pilot Projects
4.8.4 Appointment of Assistant Director RDM
4.8.5 High Level Report on RDM
4.8.6 Visit To Purdue University
4.8.7 New RDM Policy For UP
4.8.8 RDM Infrastructure Project.
4.8.9 Involvement In Data / Library Carpentry
4.9 SUMMARY
CHAPTER 5: RESEARCH DATA MANAGEMENT AND VIRTUAL RESEARCH ENVIRONMENTS (VREs)
5.1 INTRODUCTION
5.2 RESEARCH DATA LIFECYCLE AND ITS RELATION TO THE RESEARCH LIFECYCLE
5.3 A VRE AS AN ESSENTIAL FRAMEWORK FOR THE MANAGEMENT OF RESEARCH DATA
5.3.1 Managing Research Data By Means Of A VRE
5.4 A POSSIBLE CONCEPTUAL MODEL FOR RDM IN A VRE
5.4.1 The Human Components Layer
5.4.2 Hardware Components Layer
5.4.3 Software Components Layer
5.4.3.1 Interface Or Platform Layer
5.4.3.2 Core Interface / Software Layer
5.4.3.3 RDM Components
5.4.3.4 The Bottom Layer Of The Software Components Layer
5.4.4 Management Services Component (Vertical Layer In Green)
5.4.5 Standards, Protocols And Specifications (Vertical Layer In Amber)
5.4.6 Research Lifecycle And Research Data Lifecycle (Figure 5.2c)
5.4.7 Policy Components (Vertical Layer In Red)
5.5 SHORT OVERVIEW / SYNOPSIS OF THE LITERATURE REVIEW
5.6 SUMMARY
CHAPTER 6: RESEARCH METHODOLOGY
6.1 INTRODUCTION
6.2 RESEARCH DESIGN
6.2.1 Literature Review
6.2.2 Case Studies
6.2.2.1 Sampling Method
6.2.2.2 Triangulation
6.2.2.3 Participatory Action Research (PAR) Method
6.2.2.4 Prototyping
6.2.2.5 Data Collection Protocol
6.2.2.6 Testing And Prototyping
6.2.2.7 Data validation
6.2.2.8 Ethical considerations, and data confidentiality, access and use
6.3 AN OVERVIEW OF THE QUESTIONS DEALT WITH DURING THE INTERVIEW
6.3.1 Face Sheet (Background Information)
6.3.2 Questions
6.3.2.1 Part 1: Questions To Student Researchers Participating In The VRE
6.3.2.2 Part 2: Questions To VRE Managers
6.3.2.3 Part 3: Questions To VRE Designer
6.3.2.4 Part 4: Questions To Information Specialist / Librarian
6.4 METHODS OF ANALYSIS
6.5 EVALUATION
6.5.1 Formative Evaluation (Interactive, Informal)
6.5.2 Summative Evaluation (Formal)
6.6 SUMMARY
CHAPTER 7: RESULTS: PRESENTATION AND DISCUSSION
7.1 INTRODUCTION
7.2 FORMATIVE EVALUATION
7.2.1 Case Study A
7.2.1.1 Identify Case Study A (Pro-Active Dimension)
7.2.1.2 Explore The Case Study (Pro-Active Dimension)
7.2.1.3 Expand The Exploration Of The Case – Needs Identification For The VRE (Pro-Active Dimension)
7.2.1.4 Demonstration Of The Initial VRE Prototype (Pro-Active Dimension)
7.2.1.5 First Formative Evaluation: Adapt The VRE (Interactive Dimension)
7.2.1.6 Training Session 1 (Clarificative Dimension)
7.2.1.7 Identify More Needs And Adaptations To The VRE (Clarificative Dimension)
7.2.1.8 Second Formative Evaluation: Replace The Moodle VRE Platform With An Instance On Alfresco (Interactive Dimension)
7.2.1.9 Training Session 2 (Clarificative Dimension)
7.2.1.10 Identify Additional Needs For Adaptations To The VRE (Clarificativ Dimension)
7.2.1.11 Third Formative Evaluation: Adapt The VRE (Interactive Dimension)
7.2.1.12 Implement Changes To The VRE (Monitoring Dimension)
7.2.1.13 Identify Further Needs And Adaptations (Clarificative Dimension)
7.2.1.14 Fourth Formative Evaluation: Adapt The VRE (Interactive Dimension)
7.2.1.15 Implement Changes To The VRE (Monitoring Dimension)
7.2.2 Case Study B
7.2.2.1 Identify A New Group That Would Form Case Study B (Pro-Active Dimension)
7.2.2.2 Training Session 1 (Pro-active Dimension)
7.2.2.3 Explore The Case And Identify Needs (Clarificative Dimension)
7.2.2.4 First Formative Evaluation: Create The First Instance Of The VRE
7.2.2.5 Training Session 2 (Clarificative Dimension)
7.2.2.6 Implement The First Instance Of The VRE
7.2.2.7 Expand The Exploration Of Needs, And Identify New Needs And Adaptations To The VRE (Interactive Dimension)
7.2.2.8 Second Formative Evaluation: Adapt The VRE To Meet The Needs
7.2.2.9 Implement Changes To The VRE
7.2.2.10 Training Session 3 (Clarificative Dimension)
7.2.2.11 Identify Further Needs Or Adaptations (Monitoring Dimension)
7.2.2.12 Third Formative Evaluation: Adapt The VRE
7.2.2.13 Implement Changes To The VRE
7.2.2.14 Identify Further Needs Or Adaptations (Monitoring Dimension)
7.2.2.15 Fourth Formative Evaluation: Adapt The VRE
7.2.2.16 Implement Changes To The VRE
7.2.2.17 Identify Further Needs Or Adaptations (Monitoring Dimension)
7.2.2.18 Fifth Formative Evaluation: Adapt The VRE
7.2.2.19 Implement Changes To The VRE
7.2.2.20 Identify Further Needs Or Adaptations (Monitoring Dimension)
7.2.2.21 Sixth Formative Evaluation: Adapt The VRE
7.2.2.22 Implement Changes To The VRE
7.2.3 Summary Of The Formative Evaluation
7.2.4 Schematic Figures Of Development Of VRE’s For Case Study A And Case Study B
7.2.5 Conclusion About The Formative Evaluation
7.3 SUMMATIVE EVALUATION
7.3.1 Questions Of The Interview Schedule
7.3.1.1 Questions To Postgraduate Student Researchers Participating In The VRE
7.3.1.3 Questions To The VRE Designer
7.3.1.4 Questions To The Information Specialist / Librarian
7.3.2 Summary Of The Summative Evaluation
7.4 SUMMARY
CHAPTER 8: CONCLUSIONS AND RECOMMENDATIONS
8.1 INTRODUCTION
8.2 CENTRAL RESEARCH QUESTION
8.2.1 What Is A VRE?
8.2.2 What Is The Current State Of VRE Research In The World?
8.2.3 What Are The Generic Components That Make Up A VRE?
8.2.4 How Does A VRE Support A Research Cycle?
8.2.5 What Is RDM?
8.2.6 Why Should A VRE Be An Essential Framework For The Management Of Research Data?
8.2.7 To What Extent Can The Components Identified Through Question
8.2.3 Be Formalised Into A Conceptual Framework (Model) And Where Would RDM As Component Be Placed?
8.2.8 To What Extent Can This Model Be Generalised For Use In Other Environments?
8.2.9 How Was The Central Research Question Answered?
8.3 REFLECTION
8.4 CONTRIBUTION OF THIS STUDY TO THE SUBJECT FIELD
8.5 LIMITATIONS OF THIS STUDY
8.6 GUIDELINES AND RECOMMENDATIONS
8.7 SUGGESTIONS FOR FURTHER RESEARCH
8.8 CONCLUDING REMARKS
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