PROJECT SUMMARY

Diverse group of people using digital devices

Data for Social Good: Non-profit sector data projects

Focus Area: Social Services
Research Program: Data
Status: Completed

It is widely understood that the non-profit sector is at the frontline in addressing issues of social equity and inclusion. While the sector and the communities it serves stands to benefit greatly from the turn to data and analytics, it is often under-equipped.

This project draws on a range of social good data projects with non-profit organisations, including the Building Data Capability and Collaboration project, and provides a foundational methodology for the ADM+S Centre’s goals in reconfiguring data practices for responsible, ethical and inclusive ADM. It centres on a methodology of ‘collaborative data action’ that helps to build capability and improve data governance to produce data insights and innovation.

The open access Data for Social Good: Non-Profit Sector Data Projects book and associated workshops provide non-profit CEOs, managers, practitioners and board members with feasible strategies for getting into data analytics or assessing and building their organisation’s data capability. It also informs researchers as it reflects on where practice-embedded research has arrived and provides thoughts about future research directions.

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PUBLIC RESOURCES

A Data Capability Framework for the not-for-profit sector

Target audience: Not-for-profit sector

As the NFP sector undergoes digital transformation it has great opportunity to generate social value from data through its use in analysis, decision making and social innovation. Sector-wide data capability measurement and fostering data communities of practice are essential if the sector is to maximise data for social good and minimise potential harms in the fast-approaching context of a data-driven and automated society.

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Towards Resilient Communities: Data capability and resource mapping for disaster preparedness

Target audience: Disaster management organisations, Communities

Access to quality data is vital for informing decision-making before, during and after emergency events. As more data becomes available, new artificial intelligence (AI) tools such as machine learning and generative AI are extending the possibilities for data-driven disaster resilience. To work toward this outcome, the ADM+S team worked in collaboration with experienced members of Australian Red Cross to better understand the challenges and potential of data-driven decision-making for community disaster resilience.

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