Delivering sustainable Research Infrastructure

Dr Carina Kemp1, Mr Gavin Kennedy1, Dr Frankie Stevens1, Mr Ryan Fraser1

1AARNet, Sydney, Australia

AARNet has conducted broad and rigorous engagement across the Australian Research Ecosystem over the last 12 months with shareholders, researchers and research infrastructure providers. The aim of the engagement was to determine where AARNet can provide value towards sustainable and long term research infrastructure moving forward in much the same way that we have been providing network services for the last 30 years.

This engagement has involved AARNet partnering with the research community to understand their needs and it indicated that there was a gap in the market for a base level of standardised, sustainable and research ready infrastructure to accelerate the research capability of the research community across Australia. This infrastructure would be an extension of a Universities IT infrastructure ready to use on their network and supplement specialised discipline specific eResearch  and National High Performance Computing Infrastructures.

Institutions are currently managing individually the high cost of infrastructure to enable large-scale science, research and education. This had led to a number of gaps common across the “eResearch landscape”.

One of AARNet’s  key strategic pillars is to deliver customer value through a National Research Data Infrastructure. The engagement identified an opportunity for AARNet to expand on the existing CloudStor Active Research Data Storage and Analysis services to deliver a portfolio of eResearch Infrastructure Services to address some of the gaps identified during our extensive engagement and partnering across the community.

AARNet has now determined a technical roadmap to deliver these services to enable production services for our members in 2021.


Biography:

As the Director of eResearch at AARNet, Dr Kemp, leads a team building digital infrastructure to support Australian Researchers solve the worlds greatest challenges from the backbone network to enable the movement of big and small data through to easy to use tools for researchers in a trusted cloud environment.

Dr Kemp, holds a number of qualifications including a PhD from the University of Sydney and a Bachelor of Science (Geology and Geophysics) from the University of New South Wales. She has a technical background in geology, physics, mathematics and computer engineering

The journey to the Research Data Alliance Virtual Plenary 16

Ms Leanne Griffiths2, Dr Stefanie Kethers1

1ARDC, Caulfield East, Australia
2CSIRO, Adelaide, Australia

The Research Data Alliance (RDA) is a community-driven initiative launched in 2013 by the European Commission, the United States Government’s National Science Foundation and National Institute of Standards and Technology, and the Australian Government’s Department of Innovation with the goal of building the social and technical infrastructure to enable open sharing and re-use of data. Today, RDA has about 11,000 members from over 140 countries.

The 15th RDA Plenary was planned to be held in Melbourne in March 2019. In the lead up to the Plenary, RDA and ARDC held various events including an “RDA Meet & Greet” roadshow with Hilary Hanahoe, RDA Secretary General, and Webinars on topics of interest, and we saw great interest from the Australian community to participate, and run sessions and co-located events. However, the COVID-19 pandemic forced the cancellation of the physical Plenary, which was then held in virtual form, and a lot of local effort and momentum was lost.

To help people re-engage with RDA, we will look back on the outcomes and activities of RDA over the last 12 months, including RDA outputs, adoption stories, and recently established groups, and will look forward to the Virtual Plenary 16, to be held from 9-13 November 2020, and a series of regional events associated with the Virtual Plenary 16.


Biography:

Leanne Griffiths, CSIRO: Leanne Griffiths is a Senior Manager of the Information Outreach team at CSIRO. This team includes 5 data librarians. Leanne has worked in Special Libraries for over 25 years and has experience over a number of years supporting the CSIRO repositories for data and publications.

Stefanie Kethers, ARDC – Dr Stefanie Kethers is the Director of Operations of the Research Data Alliance. She has a strong interest in supporting cooperation in the workplace, and has previously worked as a researcher on a variety of related projects investigating how to support people working together in different contexts.

Developing eResearch maturity at Curtin University through the eResearch Special Interest Group

Mr Peter Green1

1Curtin University, Perth, Australia

The eResearch Special Interest Group was established in July 2018 at Curtin University to support, in the area of eResearch, the strategic research objectives of the University.

The eResearch Special Interest Group was directed to focus on future strategic needs and development of eResearch infrastructure, resources, services and programs; drive change through the drafting and discussion of specific issues papers; facilitate the development of eResearch projects capable of attracting external funding; promote effective communication on matters related to eResearch; and provide advice on operational planning, policy and processes related to eResearch.

To achieve these functions the membership of the eResearch Special Interest Group was required to straddle the breadth of the University, encompassing the different areas that provided support for eResearch, draw in research staff active in eResearch, and engage with external organisations that fund and support eResearch.

This presentation will discuss the formation, growth and activities of the eResearch Special Interest Group at Curtin University in those two year, the progress in eResearch that has been made and the challenges that persist.


Biography:

Peter Green is the Associate Director, Research, Collections, Systems and Infrastructure in the Curtin University Library. He is responsible for providing strategic direction, leadership and management of library services in support of research, the acquisition, management, discovery and access of scholarly information resources, and information technology, infrastructure and facilities. Peter manages Curtin’s team of Faculty Librarians and is also chair of Curtin’s eResearch Special Interest Group.

https://orcid.org/0000-0002-0298-722X

How to improve virtual collaborative meetings – sharing experiences, resources and stories

Dr Stefanie Kethers1, Dr Sara King2, Dr Frankie Stevens2, Dr Lesley Wyborn3

1ARDC
2AARNet
3ANU

A variety of reasons have led to a massive increase in virtual meetings over physical ones. While the COVID-19 situation may, at some point, again allow for physical meetings, other aspects, such as climate and carbon footprint considerations, travel costs (money, time) will probably lead to fewer people being able/wanting to travel to meetings that have traditionally been held face-to-face.

How then can meeting organisers, facilitators and attendees make the most of virtual meetings? What can we learn from smaller and larger meetings to make working meetings more effective, efficient, and fun?

Example questions include:

How can virtual meetings be more inclusive, enabling participants from all areas of the globe to join and contribute?

How can session facilitators make virtual meetings engaging and interactive?

What technologies and techniques can support networking, serendipitous conversations and other unplanned interactions that usually occur at face-to-face meetings?

How can we continue to build a community in the virtual space?

What is the virtual equivalent of the traditional conference ‘icebreaker’?

For an organiser, what are the key differences in preparing a meeting?

This BoF aims to bring organisers, facilitators, and attendees of virtual collaborative meetings together to share ideas, resources, experiences, and stories of what worked and what did not work, and start a curated list that would be useful to organisers and facilitators, as well as attendees of virtual meetings.

The session will start with 3-4 lightning talks (5 minutes each) followed by breakout discussions on the above aspects of virtual meetings.


Biography:

Stefanie Kethers, ARDC – Dr Stefanie Kethers is the Director of Operations of the Research Data Alliance and has been a member of the RDA Secretariat since before the RDA’s launch in 2013. She has a strong interest in supporting cooperation and collaboration in the workplace, and has previously worked as a researcher on a variety of related projects, including investigating archival services for Koorie communities, researchers’ data management practices and needs, and improving handover processes in hospitals.

Sara King, AARNet – Dr Sara King is the Training and Engagement Lead for AARNet. She is focused on outreach within the research sector, developing communities of interest around training, outreach and skills development in eResearch. She is currently working on creating reusable guidance information for Jupyter Notebooks and other AARNet services to be adapted for Carpentry training workshops. She is passionate about helping others develop the infrastructure and digital literacies required for working in a data-driven world, translating technology so it is accessible to everyone.

Frankie Stevens, AARNet – Dr Frankie Stevens is AARNet’s Associate Director, eResearch. Previously, Frankie has held roles with the Australian Research Data Commons, the NSW state body for eResearch, the Research Data Storage Infrastructure (RDSI) Project and was eResearch Programme Manager at the University of Sydney. Frankie has 20 years’ experience in the Higher Education Sector, having worked in both the Australian and overseas university sectors. She is on the Technical Advisory Board for the Global Research Data Alliance.

Lesley Wyborn, ARDC / ANU – Dr Lesley Wyborn works part time at ARDC as a Senior Data Strategist. She is also a visiting fellow at both the National Computational Infrastructure (NCI) Facility and the Research School of Earth Sciences at the Australian National University (ANU). She had had nearly 50  year’s experience in scientific research and in transparent management of geoscientific data in Geoscience Australia. She is currently Chair of the Australian Academy of Science ‘National Committee for Data in Science’ and is a  member of the American Geophysical Union (AGU) Data Management Advisory Board.

An Open Question: A comparison of proprietary and open-access teaching materials for researchers

Mr Aidan Wilson1, Dr Anastatios Papaioannou1

1Intersect Australia, Sydney, Australia

 

Intersect Australia has been a significant eResearch training provider for several years. Since the first courses in eResearch tools like HPC and Microsoft Excel, the Intersect repertoire has expanded to over 25 distinct courses, delivered at our 12 member universities, hundreds of times per year to thousands of researchers.

Intersect began utilising open access training materials in 2015: teaching Software Carpentry’s Creative Commons licensed courseware in Python, Matlab, R, Unix, and Git. Shortly thereafter, two Intersect eResearch Analysts were accredited as Software Carpentry instructors. The following year this was expanded with four more accredited instructors, and in 2017, a further six instructors were accredited and Intersect joined the Software Carpentry Foundation as a silver member, a status we recently reaffirmed.

Throughout this period, Intersect has continued to maintain a proprietary catalogue of Intersect-developed courses taught alongside the Software Carpentry materials.

In this presentation, we will explore the differences, if any, in the reception of Intersect developed course material and openly available Software Carpentry material by course attendees. The differences in cost to maintain proprietary courseware or utilise openly available materials is explored. We will also analyse differences between the delivery of the two sets of courses based on other variables, such as the experience level and teaching style of the trainer.

This presentation will be valuable to similar organisations who are grappling with the logistics of running eResearch training courses, and deciding on strategies regarding developing their own material or using material that already exists in the public domain.

As one of Australia’s most recognised eResearch training organisations, Intersect hopes that other, similar organisations may be able to benefit from our experiences, so that the research community can ultimately benefit from high-quality training from a diverse range of providers.


Biography:

Aidan Wilson is Intersect’s eResearch Analyst for the Australian Catholic University, and coordinator of Intersect’s training platform. Aidan’s research background is in documentary linguistics, concentrating on the syntax and morphology of Australia’s Aboriginal languages. He has also been actively involved in research support, and worked as a data manager for PARADISEC, an archive of Pacific and regional digital enthographical data, including linguistic and ethnomusicological recordings. In his time at Intersect, Aidan has been involved in a number of engineering and data science projects, including secure data movement for health and medical, and imaging datasets, and genome sequencing as-a-service.

http://orcid.org/0000-0001-9858-5470

Anastasios Papaioannou is Intersect’s Research Data Scientist, and one of the coordinators of Intersect’s training platform. Anastasios holds a BSc in Physics and MSc in Computational Physics, with his research focus mainly being on computational physics applied in medicine and biology. He also holds a Ph.D. in Computational Biophysics/Medical Physics from the University of Sydney. He has over 4 years of experience as an academic tutor and over 6 years in research. His role at Intersect involves working collaboratively with relevant stakeholders to develop and implement activities to ensure Intersect’s success in the Data Science field for research. He is involved in various national and state level health and medical (and other) eResearch data, while possessing a deep technical understanding of data and a combination of expertises such as programming, data and business analysis and analytics.

https://orcid.org/0000-0002-8959-4559

Roles for eResearch

Nicholas May1, Sheila Mukerjee2, Samara Neilson3

1RMIT University, Melbourne, Australia, nicholas.may@rmit.edu.au

2La Trobe University, Melbourne, Australia, sheila.mukerjee@latrobe.edu.au

3Swinburne University, Hawthorn, Australia, sneilson@swin.edu.au

 

The position descriptions of roles within the eResearch industry are not consistent and are not standardized. As an example, AeRO [1] has collected over a hundred different role titles for position descriptions within the industry. This makes the recruitment of staff and career progression within the industry much harder. However, efforts are underway, as discussed at a recent AeRO Forum [2], to determine the scope of these positions and to describe the skills associated with common roles. The first step in any movement towards standardizing position descriptions, is to set some boundaries and identify some common eResearch roles.

In this ‘Birds of a Feather’ session, participants will collaborate to perform a simple role modelling process, in which they will classify and transform existing position titles into a more manageable collection. An appropriate framework, which will be presented at the start of the session, will provide a basis for participants to classify the roles. This may be based on the overlapping domains that eResearch spans (such as: Research, Information Technology, and Innovation) or the skill categories of SFIA [3]. The role modelling process, shown in Table 1., has been adapted from an existing ‘user role modelling’ process, as described by Cohn [4]. The steps of the process that will be performed in the session include: Discovery, Organization, and Consolidation.

Participants can submit their role titles, in advance of this session, via the following URL:        https://eresear.ch/roles

The resulting set of titles will subsequently be assigned appropriate skills and levels of responsibility using an appropriate framework, such as SFIA, as has already been done for various ICT roles [5].

Step Time (Mins) Goals
Introduction 15 Present the modelling process and classification framework.
Discovery 15 A visual representation of the framework is outlined on a whiteboard or wall.

Starting list of titles is shared amongst the participants.

Everyone writes role titles on sticky notes.

Notes are posted on the framework.

No discussion of the role names is allowed in this step.

Organization 15 Move the notes around the board to represent their relationships.

If roles overlap then overlap the notes, the degree of overlap represents the degree to which the roles overlap.

Consolidation 15 If notes overlap entirely,

·         remove a note, or

·         replace both with a consolidated name.

If notes overlap partially,

·         remove a note if the difference is not significant, or

·         replace one with a title that corresponds to the difference.

Remove any notes for roles that are not significant.

Rearrange the notes to show the important relationships and hierarchies between roles.

    Inputs: List of Role Titles, Classification Framework.

Outputs: Transformed and condensed set of Role Titles.

Table 1. Session Format.

REFERENCES

  1. Australian eResearch Organisations (AeRO), http://aero.edu.au/, accessed 6 June 2018.
  2. C3DIS, AeRO Forum – eResearch Workshop, http://www.c3dis.com/1903, accessed 6 June 2018.
  3. SFIA Foundation, The Skills Framework for the Information Age – SFIA, Available at: https://www.sfia-online.org/, accessed 6 June 2018.
  4. Cohn, M., User Stories Applied, Addison-Wesley, 2004, ISBN: 0-321-20568-5.
  5. ACS, Common ICT Job Profiles and Indicators of Skills Mobility, ICT Skills White Paper, 30 December, 2013,
    Available at: https://www.acs.org.au/content/dam/acs/acs-publications/ICT%20Skills%20White%20Paper%20-%20Common%20Job%20Profiles%20and%20Skills%20Mobility%2030%20Dec%202013.pdf, accessed 6 June 2018.

Biographies:

Nicholas May is a software developer in the Research Capability unit at RMIT University. He has over twenty-nine years of varied experience within the software engineering profession, across industries and domains, and holds the Certified Professional status with the Australian Computer Society. His current role includes the responsibility for promoting research data management across the research lifecycle at RMIT University. http://orcid.org/0000-0002-1298-1622

Samara is a computer scientist and technologist working in the Research Analytics Services team at Swinburne University. In addition to being a representative of FAVeR, she is also on the Melbourne Committee for Random Hacks of Kindness (RHoK), Australia’s longest running hackathon for social good, and a member of Girl Geek Academy, supporting women in STEMM.

Caroline Gauld is the Deputy Director, Research Information Management (RIM) at Defence Science and Technology (DST) Group. The Research Information Management team supports research data management, knowledge management and records management across DST Group and works in collaboration with other technology specialists to support DST Group researchers to manage and preserve their research outputs and data.

What researchers really want: and what it means for researcher-centric services

Steven Chang1, Eva Fisch2, Michele Hosking3

1La Trobe University, Melbourne, Australia, s.chang@latrobe.edu.au

2La Trobe University, Melbourne, Australia, e.fisch@latrobe.edu.au

3La Trobe University, Melbourne, Australia

 

INTRODUCTION

In a scholarly environment undergoing rapid cultural changes to researcher norms and expectations, a crucial factor in the development and adoption of eResearch infrastructure is an appreciation of researchers’ attitudes, habits, and needs [1]. Moreover, researchers may face varying challenges according to discipline and their career stage [2]. The increasing emphasis on designing and reconfiguring researcher-centric services requires tailoring them to the research community’s preferences. This approach leads to wider adoption of research infrastructure, as there is a closer alignment between everyday research practice, disciplinary norms, and the research toolset.

LITERATURE REVIEW

In a 2011 literature study on researcher needs, Feijen’s environmental scan identified that non-technical, soft, or social factors influencing research data management such as control and incentives were most significant for researchers. The report identified that successful researcher support services must be of immediate benefit, local, available at the point of need, easy to use, and optional rather than forced. A “cafeteria” model is favoured, where researchers can pick and choose services most relevant to them.

A study on data management practices in Australian universities found that researchers recognise the need for formal research data management plans, but do not usually have one that is more than rudimentary. Furthermore, the evidence suggested researchers are often willing to share their data, but only when there is an easy means of doing so without bureaucratic or time-consuming constraints [3].

METHODS

In order to develop and transform support structures in a researcher-centric way, up-to-date data is needed to understand the user. Accordingly, this paper investigates behaviours towards eResearch at La Trobe University based on 2017 interviews with over 130 researchers at various career stages. This data was used to develop the business needs and requirements for the University’s Enterprise Research Data Management System (ERDMS) project.  A high-level summary of the business needs and requirements from the interviews was presented at eResearch Conference 2017 by Williams, Fisch, and Huggard [4].

La Trobe’s ERDMS project is now completed and the research data management systems implemented by it (figshare, LabArchives, etc.) have now transitioned into “business as usual”. In order to effectively design services and training to maximise the value of these systems, the Library Research Data support team is revisiting the original stakeholder interviews to mine them for evidence that illuminates user preferences, behaviours, knowledge, and disciplinary needs.

IMPLICATIONS

This presentation discusses how these factors have significant implications for the ways in which research support staff design training and, crucially, engage with researchers from the inception of the service design process to co-create effective programs. Our qualitative evidence provides insight on what researchers really want from support services. This knowledge will inform a pilot project working with researchers to co-design customised research infrastructure and support. This approach is in line with La Trobe’s orientation towards centring technology around the research community’s needs by delivering nuanced and effective services to facilitate high-quality research outcomes.

In addition, the project personnel are reflecting and acting on current literature about the benefits of co-designing services [5]. The library and information sciences scholarship on this topic tends to focus on co-designing services in the context of public libraries, academic learning and teaching for undergraduate students, developing physical library spaces, and website redesigns [6, 7, 8, 9]. It is less common for these participatory design methods to be associated with research infrastructure development. This pilot project will contribute to broadening the deployment of co-design to the research services world in order to enhance stakeholder engagement and harmonise researcher workflows with enterprise level systems.

REFERENCES

  1. Hickson, S., Poulton, K. A., Connor, M., Richardson, J., & Wolski, M. (2016). Modifying researchers’ data management practices: A behavioural framework for library practitioners. IFLA journal, 42(4), 253-265.
  1. Yoon, A., & Kim, Y. (2017). Social scientists’ data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories. Library & Information Science Research, 39(3), 224-233.
  1. Henty, M., Weaver, B., Bradbury, S., & Porter, S. (2008). Investigating data management practices in Australian universities. Accessible at: http://hdl.handle.net/1885/47627
  1. Williams, A., Fisch, E., & Huggard, S. (2017). Leveraging projects for institution-wide benefit – expect the best, plan for the worst, and prepare to be surprised. eResearch Australasia Conference 2017. Accessible at: https://conference.eresearch.edu.au/2017/08/leveraging-projects-for-institution-wide-benefit-expect-the-best-plan-for-the-worst-and-prepare-to-be-surprised/
  1. Steen, M., Manschot, M., & De Koning, N. (2011). Benefits of co-design in service design projects. International Journal of Design, 5(2).
  1. Wood, T. M., & Kompare, C. (2017). Participatory Design Methods for Collaboration and Communication. Code {4} Lib Journal, 35.
  1. Bech-Petersen, S. (2016). Dokk1: co-creation as a new way of working in libraries. AIB STUDI, 56(3), 441-450.
  1. Foster (2014), Participatory Design in Academic Libraries New Reports and Findings https://www.clir.org/pubs/reports/pub161/
  1. Somerville, M. M., & Brar, N. (2006). Collaborative co-design: the Cal Poly digital teaching library user centric approach. Library Scholarship, 24.

                                                                                                                          


Biography:

Steven Chang is Research Data Outreach Officer at La Trobe University Library. He is interested in open scholarship, systematic review methodology, research data management, and health librarianship. Steven comes from a medical librarian background, and is the former editor of the publication Health Inform.

https://orcid.org/0000-0002-3193-7969

Eva Fisch is manager of the Library Research Team, who provide services relating to research information expertise, publication management, open access publishing, copyright, research impact, and research data management.

https://orcid.org/0000-0002-2224-954X

“It’s all about the researcher, stupid!”

Michelle Krahe1, Julie Toohey2, Malcolm Wolski3, Paul Scuffham4, Sheena Reilly5

1Menzies Health Institute Queensland, Griffith University, Gold Coast. Australia, m.krahe@griffith.edu.au

2Library and Learning Services, Griffith University, Gold Coast, Australia, Julie.toohey@griffith.edu.au 3eResearch Services, Griffith University, Nathan, Australia, m.wolski@griffith.edu.au

4Menzies Health Institute Queensland, Griffith University, Nathan, Australia p.scuffham@griffith.edu.au

5Health Group, Griffith University, Gold Coast, Australia, s.reilly@griffith.edu.au

 

BACKGROUND

The adage coined in the 1992 presidential campaign “It’s all about the economy, stupid”, was to remind everyone that they should be focused on the plight of the working people and not get side tracked on other issues. The same could be said for research data management (RDM), it’s the researcher who should be the main focus!

Building or acquiring RDM capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that different RDM practices can have direct influences on the integrity and longevity of data, optimising institutional services and support in recognition of RDM needs is especially valuable within the context of the broader open science movement.

The national research agenda, funding requirements, institutional research strategies and the open science movement including the F.A.I.R principles, are stimulating change in academic institutions, researchers and centres to develop sound RDM practices throughout the entire research life cycle.

So do researchers understand RDM, and do they really care? In an attempt to instill sound RDM practices among the research community, Griffith University’s approach is to work with the researchers (bottom up approach) to better understand their current practices and needs. Figure 1 illustrates a typical day for a researcher, filled with competing priorities and tasks and begs to question whether RDM is a high priority.

Figure 1: Researchers to do list .

METHOD

A collaborative project conducted with the Health Executive, eResearch Services and Library and Learning Services at Griffith University, evaluated factors relating to current RDM and data sharing practices among health and medical researchers within the Menzies Health Institute Queensland.

A cohort of 81 researchers were surveyed about their RDM practices including:  data storage and retention, data sharing practices and RDM tasks aligned to the research lifecycle.

RESULTS

This project highlights characteristics indicative of the broader academic researcher population. Current strengths and needs of the cohort were also identified that will inform priorities for future development of the eResearch and Data Management support services, training and networks.

Project findings indicate a large number of academics are conducting research on their non-secure desktops and external hard drives which many lead to potential risk of data loss.  Why is this the case?  And why don’t researchers use secured desktops, enterprise systems and computational services throughout the entire research lifecycle?  Perhaps, it is simply a lack of knowledge.

We are starting to realise that researchers don’t know what they don’t know, so in terms of developing capabilities and sound RDM practices at Griffith, what should be our next step?

CONCLUSIONs

At what stage of the research life cycle do we engage with researchers to potentially change their data gathering, analysing and storage behaviours?  The one size fits all approach does not work and data management plans may not be the answer.  What are the skills and knowledge gaps as well as the motivators and opportunities we can leverage to bring about necessary change?  Which university elements are responsible for delivering that change?

So what is our solution? Let’s say it is a work in progress.

For example the recent establishment of the RDM Steering Group lead by Office for Research, comprises of four working parties: Services, Infrastructure, Policy, and Skills. Working parties membership include stakeholders representatives from across the community and will steer Griffith’s efforts collaboratively providing further support services, strengthening researcher capability and good RDM practices.

This presentation will focus on an evaluation of researchers’ current RDM practices from the survey and strategies used towards building researcher capacity around good RDM practices.  This presentation will be of interest to institutions embarking on University wide collaborative approaches in working towards development and delivery of training programs supporting researchers.


Biography:

Julie has worked in academic libraries for 23 years and is currently the Health Discipline Librarian at Griffith University, Gold Coast campus.  Julie is passionate about research data management practices and is in the process of publishing her first co-authored journal article. Throughout 2016, Julie co-facilitated the Australian National Data Services 23 Things (research data) Health and Medical Data Community Group webinar series and is a member of the Queensland University Libraries Office of Cooperation (QULOC) Research Support Working Party.

https://orcid.org/0000-0002-4249-8180

Understanding and governing data ecosystems using a social architecture approach: a CSIRO research infrastructure case study

Paul Box1, Cynthia Love2, Jonathan Yu3

1CSIRO Land and Water, Sydney Australia, paul.j.box@csiro.au

2CSIRO Information Services, Melbourne Australia, cynthia.love@csiro.au

3CSIRO Land and Water, Melbourne, Australia, Jonathan.yu@csiro.au

Introduction

Today, efforts to change how we work, requires the navigation of and negotiating change in, complex social, institutional and technical environments. Knowledge workers and especially those in data intensive environments such as science, directly use and are enabled by numerous information systems. Collectively, these information and technology resources (data, information systems, and technologies), together with social and institutional contexts in which they are embedded, (work routines, standards, culture, relationships, governance and norms) comprise information infrastructure (or data ecosystem).

Successful introduction into an existing installed base of systems, practices, and institutions, of new systems or approaches to improve the way we manage and use data, requires an understanding of data ecosystem. This includes and understanding of the system(s) which it replaces or interacts with; how users interact with these existing systems, and why; and the design of institutions (such as incentives, policies, standards and governance) that shape how users will interact with the new system. An inter-disciplinary approach to designing environments that are conducive to change, called ‘social architecture’,  will be presented in this paper.

Current approaches

Tradition systems development approaches take a technical perspective and apply limited social and institutional analysis to system design, typically undertaking rudimentary stakeholder analysis to identify uses cases and requirements, and putting in place ‘boilerplate’ change management, communication and governance mechanisms. This may be sufficient for smaller largely standalone systems. However, in many cases the systems we are trying to change are much more interconnected and complex and therefore require different approaches.

Although ‘users’ are brought increasingly into the systems design processes through user centered design (UCD) approaches, these tend to focus on the end users that interact with the systems and the ‘experience’ of using the system. UCD approaches have raised the profile and provide useful tool for exploring, understanding and designing information systems with cognizance of the social and institutional context within which they operate. However these approaches tend to be rather ad hoc, and limited in scope, often neglecting to engage with and understand users’ attitudes and practices as well as the institutional context that needs to be factored into the design process.

When attempting to implement larger, more complex, interconnected systems, the primary challenge lies in working with a wide range of stakeholders to influence behaviours and enable collective action across organisational boundaries. This requires a much deeper understanding of institutional arrangements, attitudes and behaviours and the often invisible hand of data economics – the costs, value generation and benefit flows inherent in data supply chains and data platforms.

A SOCIAL ARCHITECTURE APPROACH

Social architecture[1] is multi-disciplinary approach to the analysis, design and implementation of complex socio-technical systems. It takes a data ecosystem (information infrastructure) perspective viewing (social and technical) systems as being interconnected in networks. It draws on a range of inter-related disciplines organised in three inter-related themes of work:

  • Social – attitudes, behaviours and practices together with the social structures and mechanism through which people formally and informally collaborate, influence each other and affect change;
  • Institutions – the rules of the road (legislation, regulation, policy, standards and licensing) and how they are created (authority structures, roles and responsibilities and decision rights);
  • Economics – the costs, value generation, benefit flows in data ecosystems , together with an understanding of data market mechanisms

Using these three lens, the aim is to explore and understand current system dynamics and design a future state together with a plan for incremental change to achieve it. A critical element of the approach is the ability to measure progress and change in behavior and attitudes necessary to secure sustainable long term outcomes.

CSIRO Data governance program

Within CSIRO, a number of efforts are underway to improve the management and re-use of data at enterprise levels and within individual business units. There is a recognition of the federated nature of the CSIRO operating model and the need for solutions that meet the differing science business needs in various parts of the organization.

The CSRO data governance program aims to develop an integrated interoperable data ecosystem with established accountability for data at all levels, a default assumption of openness, whist ensuring that licensing, ethical and contractual obligations are honoured and supported by data management and data governance tools and infrastructure. The project is being led by CSIRO Information Management & Technology in partnership with CSIRO business units and other corporate functions.

In parallel, to this enterprise wide activity, within the CSIRO Land and Water business unit a Digital Asset Management improvement program (DAMbusters) is underway which aims to support improved data management and reuse practices through a range of technical and institutional interventions.

To maximize the value of CSIRO data assets through a range of interventions at CSIRO enterprise-wide and business unit scale, there is a need to understand prevailing attitudes and practices of a range of stakeholders within the organisation and the complex external (legislative, policy, economic, legal) and internal organisational (policy, contractual and IP) environment within which they work. All of these factors shape the systems and practices that we currently use and constrain and inform our ability to change.

A social architecture approach is being used to inform how both the enterprise wide and DAMbusters projects tackle what is a complex multi-dimensions challenge.

This paper will briefly describe the theoretical underpinnings of social architecture focusing on the value, practices and institutional aspects of data. It will describe how social architecture is being used in practice to inform CSIRO efforts at enterprise and business unit level, to understand the current installed base of practices, technology and institutions as well as to design a comprehensive and instrumented change program to guide and monitor the CSIRO data ecosystem improvement. The paper will conclude by offering some lessons learned and pointers for others engaged in similar data oriented improvement programs.

REFERENCES

  1. Box, P. and Lemon, D. (2016). Social architecture – cultivating conditions for data sharing. SciDataCon2016, Denver Collorado USA. http://www.scidatacon.org/2016/sessions/37/paper/139/

Biography:

Paul works in the Environmental Informatics Group in CSIRO Land and Water, building and leading a program of research into the social, institutional and economic aspects large scale distributed information platforms for government. The  ‘social architecture’ practice that he is currently developing, brings together social science, economics and institutional analysis to guide and inform the development of information infrastructures (or systems of systems) that underpin effective policy and decision making.

Understanding organisational, sector-specific, disciplinary and individual factors influencing research data sharing

Claire Mason1, Paul J. Box2, Shanae Burns3

1Data61, CSIRO, Brisbane, Australia, Claire.Mason@data61.csiro.au

2Land and Water, CSIRO, Sydney, Australia, Paul.J.Box@csiro.au

3Data61, CSIRO, Brisbane, Australia, Shanae.Burns@data61.csiro.au

 

Introduction

CSIRO’s data governance initiative aims to improve the discoverability, management, accessibility and re-use of research data. One of the first activities carried out under the initiative was an organisation-wide survey whose purpose was to (a) provide a baseline view of data attitudes and practices and (b) reveal how organisational, sector, disciplinary and individual factors were shaping data sharing practices, responses. We report on the findings of the survey and explain how they can be used to inform CSIRO’s institutional and technical responses to promote data sharing and open data outcomes.

RESEARCH APPROACH

The survey was sent to CSIRO staff and affiliates who worked in research units and roles where they were likely to be dealing with research data. Of the 5,704 individuals who received the invitation to participate in the survey, 806 agreed to participate in the survey, representing a 22% response rate for staff and a 1% response rate for affiliates. Apart from the low representation of affiliates in the sample, the survey achieved input from across the range of age-groups, roles, tenure and education levels. Use of data management plans and channels to share research data amongst these respondents was relatively high – 87% of respondents reported sharing or depositing data through one or more channels over the past five years. However, although the response rate was high for a survey of this kind, we did not achieve input from the majority of CSIRO research staff, so these figures may not be representative of data practices organization-wide.

Findings

Organisational factors that were assessed in the survey included organizational data culture, peer support for data sharing and organisational support (funding, processes, tools and training) for data sharing. The organisational culture was open, indicating that most respondents believed that data should be made publically available when possible, although respondents also agreed that data was viewed as a source of competitive advantage (which is shared when there is a benefit to the organisation, rather than simply to benefit others). Peer support for data sharing was perceived to be high and the great majority of respondents reported a desire for organisational processes and systems to support data management and sharing, both during and beyond the life of the project.

The survey also revealed that the industry sector or domain area that researchers work in has an impact on their data attitudes and practices. Furthermore, these external influences appear to do more to inhibit than to foster data sharing. Only 39% of survey respondents reported that their funders “encourage” or “mandate” data sharing, whereas most researchers (especially those working with industry rather than government) reported that contractual arrangements, privacy concerns and ownership and licensing arrangements were important inhibitors of their ability to share data.

There was significant variability in the extent to which scientists from different research disciplines experienced support or barriers to data sharing. The conditions for data sharing appeared to be most conducive for environmental scientists (since they were most likely to report that their journal publishers encouraged them to publish their data and that their peers supported data sharing) and least conducive for researchers who worked in the field of studies in human society.

Finally, individual attitudes towards data sharing were generally positive. On average, the career benefits associated with data sharing were seen to outweigh the risks and respondents said that they would be willing to share their data to help another researcher. However, they also believed that they did not always have control over the decision about whether to share their data or not.

To understand how these organisational, sector-specific, disciplinary and individual factors influence data sharing, we asked survey respondents whether they would be likely to share their data externally (beyond the project team and client) over the next twelve months. An ordinary least squares regression model was used to test the relationship between researchers’ perceptions of organizational, sector-specific, disciplinary and individual factors and their views on the likelihood of sharing data externally.

The analysis revealed that social factors had the strongest relationship with external data sharing. The regression model revealed that open data culture, peer support for data sharing, type of science, social influence and willingness to share data all explained significant variance in external data sharing. The overall fit of the model (R2adj = .41, p < .001) was significant and indicates that the significant predictor variables explained 41% of the variance in external data sharing behavior.

IMPLICATIONS

These findings should be interpreted with caution because common method variance effects and non-independence in the data may have inflated these relationships. There are also some indications that the strength of these relationships varies, depending on which area of the organization respondents work in, which means that tailored strategies and a federated approach to data governance will be needed.  Nevertheless, the survey provides important insight into data attitudes and practices in CSIRO. First, it reveals that staff understand the value of data re-use but that they are also aware of important factors (e.g., ethics, privacy concerns, contractual arrangements) which constrain data sharing. Staff in some research units and industry sectors (e.g., researchers working for government rather than industry) have more freedom to operate than others when it comes to data sharing.  Finally, the results of our modelling suggest that organisational culture and norms (both within the organisation and within research disciplines) represent important levers for influencing organisational data practices.


Biography:

Senior social researcher in the CSIRO’s Data61, Claire’s research focuses on understanding the opportunities and challenges associated with our increased reliance on digital technology across a range of contexts – in our homes and businesses, in our jobs, in vocational education and training, in regions and in later life. She also explores how social, organisational and institutional factors influence data practices and thus our opportunities for data driven innovation.

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