Table Of ContentData for Social Good
Non-Profit Sector Data
Projects
Jane Farmer
Anthony McCosker
Kath Albury
Amir Aryani
Data for Social Good
Jane Farmer • Anthony McCosker
Kath Albury • Amir Aryani
Data for Social Good
Non-Profit Sector Data Projects
Jane Farmer Anthony McCosker
Social Innovation Research Institute Social Innovation Research Institute
Swinburne University of Technology Swinburne University of Technology
Melbourne, VIC, Australia Melbourne, VIC, Australia
Kath Albury Amir Aryani
Swinburne University of Technology Social Data Analytics Lab
School of Social Sciences, Media, Film Swinburne University of Technology
& Education Melbourne, VIC, Australia
Melbourne, VIC, Australia
ISBN 978-981-19-5553-2 ISBN 978-981-19-5554-9 (eBook)
https://doi.org/10.1007/978-981-19-5554-9
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Acknowledgements
We pay our respects to the traditional custodians of the lands on which
we work and acknowledge their Elders, past and present.
We would like to acknowledge funders of our research on data for
social good, including the Australian Research Council (ARC) for
Linkage Infrastructure Equipment and Facilities, grant no. LE200100074;
Data Co-operative Platform for Social Impact; the ARC Centre of
Excellence for Automated Decision Making and Society, grant no.
CE200100005; ARC Discovery Project, grant no. DP200100419;
Victoria State Government; Australian Red Cross; Lord Mayor’s
Charitable Foundation; and City of Greater Bendigo Data Co-op
partners.
We would like to acknowledge the contribution of the Regional
Innovation Data Lab (RIDL) at Griffith University, Queensland,
Australia, and the Visualisation and Decision Analytics (VIDEA) Lab at
the University of Canberra, Australia.
v
Contents
1 I ntroduction 1
The Non-Profit Sector and Data 4
Making Good Use of Data 7
Starting to Think About Data Capability 13
Navigating Data Harms by Involving Citizens 15
Key Takeaways from This Chapter 20
References 21
2 Case Studies of Data Projects 27
Case Study 1: Outcomes of Family Violence Policy—A Public
Sector Collaboration 29
Project Goal 29
Project Description 29
Collaborating Partners 31
How the Project Began 31
Summary of Datasets Used 32
Methods 33
Findings 34
Outcomes and Lessons Learned 36
vii
viii Contents
Case Study 2: Re-using Operational Data with Three Non-
Profits 38
Project Goal 38
Project Description 39
Collaborating Partners 39
How the Project Began 40
Summary of Datasets Used 41
Methods 42
Data Analysis 43
Findings 44
From the Before and After Interviews 46
Outcomes and Lessons Learned 47
Case Study 3: City of Greater Bendigo Data Collaborative 48
Project Goal 48
Project Description 49
Collaborating Partners 49
How the Project Began 50
Summary of Datasets Used 51
Methods 51
Data Analysis 52
Findings 53
From the Before and After Interviews 54
Outcomes and Lessons Learned 57
Summary 58
Key Takeaways from This Chapter 60
References 61
3 Data Capability Through Collaborative Data Action 63
Understanding Data Capability 64
A Collaborative Data Action Methodology 67
Finding Your Data Collaborators 74
Responsible Data Governance 76
Data Ethics and Consent 79
Data Sharing for Collective Gain 83
Key Takeaways from This Chapter 84
References 85
Contents ix
4 Activating for a Data-Capable Future 89
Sectoral Benefits of Non-profits with Data Capability 90
Data Capability and Organisational Competence 90
Data Capability and Field-Building 91
Data Capability and Social Justice Activism 92
Three Stages of Non-profits’ Data Capability 93
Data Analytics as Business as Usual 94
Getting Started 94
Moving Beyond a Data Project: Next Steps 98
Innovations to Solve Data Challenges 100
Research Reflections and Next Steps 103
Our Research Reflections 103
What Next in Research? 105
Key Takeaways from This Chapter and Conclusions 107
References 108
Appendix: The Data Innovation Ecosystem and Its Resources 113
G lossary 121
I ndex 125
About the Authors
Kath Albury is an Australian Research Council Future Fellow
(2022–2025) in the Department of Media and Communication at
Swinburne University of Technology. She is an Associate Investigator in
the Australian Research Council Centre of Excellence for Automated
Decision Making and Society, and a programme leader in the Social
Innovation Research Institute. Kath’s research investigates the intersec-
tions of digital technologies and platforms, digital literacy, data capabili-
ties and sexual health and wellbeing. She is a co-author of Everyday Data
Cultures (2022).
Amir Aryani leads the Social Data Analytics (SoDA) Lab at Swinburne
University of Technology. The lab applies data analytics techniques for
insights into health and social challenges. His expertise is in data model-
ling, information retrieval techniques and real-time data analysis. Amir
has partnered on projects with the British Library, ORCID (US),
Netherlands Data Archiving and Network Analysis (DANS) and German
Institution for the Social Sciences in Germany (GESIS). His funding
sources include the Australian Research Council, the Australian National
Health and Medical Research Council, and the US National Institutes of
Health. He has published in journals including Nature Scientific Data
and Frontiers in Artificial Intelligence and Applications.
xi
xii About the Authors
Jane Farmer is Director of the Social Innovation Research Institute at
Swinburne University of Technology, Melbourne, Australia. Her back-
ground is as a researcher in rural health service and workforce innovation,
community engagement and social enterprise. She has a keen interest in
academic-practice research partnerships, innovative research methods,
transdisciplinary studies and translating research into practice. Her other
books include Social Enterprise, Health and Wellbeing (2021), Remote and
Rural Dementia Care (2020) and Community Co-production (2012).
Anthony McCosker is Deputy Director of the Social Innovation
Research Institute and is a Chief Investigator and Swinburne Lead for the
Australian Research Council Centre of Excellence for Automated
Decision Making and Society. His research addresses digital inclusion,
participation and inequality and explores the impact of new communica-
tion technologies, particularly in relation to health and wellbeing and
social inclusion. Current research addresses the social issues related to
automation and machine vision technologies and media and the need for
community-led approaches to data and analytics. He is author or co-
author of numerous articles and books, including Everyday Data Cultures
(2020), Automating Vision: The Social Impact of the New Camera
Consciousness (2020) and Negotiating Digital Citizenship (2016).
