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- Publisher Website: 10.1177/20539517221099882
- Scopus: eid_2-s2.0-85132628865
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- Scopus: 8
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Article: Developing data capability with non-profit organisations using participatory methods
Title | Developing data capability with non-profit organisations using participatory methods |
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Authors | |
Keywords | co-design data capability Data literacy expertise non-profit participatory methods |
Issue Date | 2022 |
Citation | Big Data and Society, 2022, v. 9, n. 1 How to Cite? |
Abstract | In this paper, we explore the methodologies underpinning two participatory research collaborations with Australian non-profit organisations that aimed to build data capability and social benefit in data use. We suggest that studying and intervening in data practices in situ, that is, in organisational data settings expands opportunities for improving the social value of data. These situated and collaborative approaches not only address the ‘expertise lag’ for non-profits but also help to realign the potential social value of organisational data use. We explore the relationship between data literacy, data expertise and data capability to test the idea that collaborative work with non-profit organisations can be a practical step towards addressing data equity and generating data-driven social outcomes. Rather than adopting approaches to data literacy that focus on individuals – or ideal ‘data citizens’ – we target the organisation-wide data settings, goals and practices of the non-profit sector. We conclude that participatory methods can embed social value-generating data capability where it can be sustained at an organisational level, aligning with community needs to promote collaborative data action. |
Persistent Identifier | http://hdl.handle.net/10722/345259 |
DC Field | Value | Language |
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dc.contributor.author | McCosker, Anthony | - |
dc.contributor.author | Yao, Xiaofang | - |
dc.contributor.author | Albury, Kath | - |
dc.contributor.author | Maddox, Alexia | - |
dc.contributor.author | Farmer, Jane | - |
dc.contributor.author | Stoyanovich, Julia | - |
dc.date.accessioned | 2024-08-15T09:26:13Z | - |
dc.date.available | 2024-08-15T09:26:13Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Big Data and Society, 2022, v. 9, n. 1 | - |
dc.identifier.uri | http://hdl.handle.net/10722/345259 | - |
dc.description.abstract | In this paper, we explore the methodologies underpinning two participatory research collaborations with Australian non-profit organisations that aimed to build data capability and social benefit in data use. We suggest that studying and intervening in data practices in situ, that is, in organisational data settings expands opportunities for improving the social value of data. These situated and collaborative approaches not only address the ‘expertise lag’ for non-profits but also help to realign the potential social value of organisational data use. We explore the relationship between data literacy, data expertise and data capability to test the idea that collaborative work with non-profit organisations can be a practical step towards addressing data equity and generating data-driven social outcomes. Rather than adopting approaches to data literacy that focus on individuals – or ideal ‘data citizens’ – we target the organisation-wide data settings, goals and practices of the non-profit sector. We conclude that participatory methods can embed social value-generating data capability where it can be sustained at an organisational level, aligning with community needs to promote collaborative data action. | - |
dc.language | eng | - |
dc.relation.ispartof | Big Data and Society | - |
dc.subject | co-design | - |
dc.subject | data capability | - |
dc.subject | Data literacy | - |
dc.subject | expertise | - |
dc.subject | non-profit | - |
dc.subject | participatory methods | - |
dc.title | Developing data capability with non-profit organisations using participatory methods | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1177/20539517221099882 | - |
dc.identifier.scopus | eid_2-s2.0-85132628865 | - |
dc.identifier.volume | 9 | - |
dc.identifier.issue | 1 | - |
dc.identifier.eissn | 2053-9517 | - |