PROJECT SUMMARY

Data capacity and collaboration for ADM in the community sector

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

The project works toward a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector. The aim is to develop models for responsible data practices suitable for addressing the goals and challenges faced by the NFP sector, and assess and advance data literacy and expertise to improve ADM outcomes.

This project takes an innovative approach to addressing challenges in data collaboration and developing data capability across the not-for-profit (NFP) sector. Through participatory methods, it integrates technical approaches to responsible data management in computer science, legal approaches to data sharing, and social science approaches to data capability building and ‘data and AI for social good’.

The project works toward a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector. The aim is to develop models for responsible data practices suitable for addressing the goals and challenges faced by the NFP sector and assess and advance data literacy and expertise to improve ADM outcomes.

Phase One of the project worked with a range of not-for-profit organisations to establish the key challenges and opportunities in the sector for using data and ADM to address disadvantage in the community.

This research phase resulted in an Interim report: ‘Building Data Capacity in the Not-for-Profit Sector’. Our research has shown that data capability involves fostering effective and responsible data practices across three integrated dimensions: data access and infrastructure, data skills and data governance. Insights from Phase One were used to co-design a NFP specific Data Capability Framework and test the Framework through three participatory workshops throughout Phase Two.

Phase Two of the project applied participatory methods to generate a Data Capability Framework designed to support the Not-for-Profit sector.

As social and community services rapidly digitise, they are generating more data than ever before. Co-designed with organisations from across the sector, the Data Capability Framework for the Not-for-Profit Sector sets out a pathway for developing effective and responsible data practices across three integrated dimensions: data access and infrastructure, data skills and data governance. This work lays the foundations for safe, responsible and inclusive automated decision-making and AI use across the sector.

The Framework distils the challenges and successes of organisations we have worked with. It represents both the factors that underpin effective data capability and the pathways to achieving it. In other words, as technologies and data science techniques continue to change, data capability is both an outcome to aspire to, and a dynamic, ongoing process of experimentation and adaption.

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