Bringing data to life: A model for involving lived experience in data-driven research

ObjectiveIt is generally accepted that involving experts by experience is necessary to deliver research that is relevant to community need and to progress the data democratisation agenda. We have piloted and evaluated a model of co-production for data-driven research with seldom heard groups. ApproachIn partnership with the charity Voice of Young People in Care (VOYPIC) and a group of care experienced young people, the Administrative Data Research Centre Northern Ireland (ADRC NI) piloted and implemented a model of co-production in data-driven research. To evaluate the model, interviews were conducted with the young people, staff at VOYPIC, and ADRC NI researchers and public engagement team members. ResultsThematic analysis of interview data identified numerous benefits and barriers to co-producing data-driven research with experts by experience. We offer reflections from three perspectives (the young people, VOYPIC and ADRC NI), as well as a model that can be adapted with different lived experience groups in other data-driven research programmes. Conclusion Experts by experience can be equal partners in most stages of the data research cycle, and there are tangible benefits for all partners and the research itself. However, aligning the aspirational principles of co-production with the realities of delivering data research is challenging and has implications for achieving the democratisation of data. ImplicationsThis session will share real world perspectives on the co-production of data research with seldom heard groups.

Authors

Institutions

Publication Details

Journal
International Journal for Population Data Science
Published
2024-09-10
DOI
https://doi.org/10.23889/ijpds.v9i5.2499
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bringing data to life: A model for involving lived experience in data-driven research

Sarah McKenna, Aideen Maguire, Elizabeth Nelson
International Journal for Population Data Science
Big Data Technologies and Applications
article

Bringing data to life: A model for involving lived experience in data-driven research

Sarah McKenna, Aideen Maguire, Elizabeth Nelson
article en

Abstract

ObjectiveIt is generally accepted that involving experts by experience is necessary to deliver research that is relevant to community need and to progress the data democratisation agenda. We have piloted and evaluated a model of co-production for data-driven research with seldom heard groups. ApproachIn partnership with the charity Voice of Young People in Care (VOYPIC) and a group of care experienced young people, the Administrative Data Research Centre Northern Ireland (ADRC NI) piloted and implemented a model of co-production in data-driven research. To evaluate the model, interviews were conducted with the young people, staff at VOYPIC, and ADRC NI researchers and public engagement team members. ResultsThematic analysis of interview data identified numerous benefits and barriers to co-producing data-driven research with experts by experience. We offer reflections from three perspectives (the young people, VOYPIC and ADRC NI), as well as a model that can be adapted with different lived experience groups in other data-driven research programmes. Conclusion Experts by experience can be equal partners in most stages of the data research cycle, and there are tangible benefits for all partners and the research itself. However, aligning the aspirational principles of co-production with the realities of delivering data research is challenging and has implications for achieving the democratisation of data. ImplicationsThis session will share real world perspectives on the co-production of data research with seldom heard groups.

International Journal for Population Data ScienceVol. 9(5)
Queen's University Belfast (GB), University of Ulster (GB)
Medical Research Council
Openalex Percentile: Top 83%
Big Data Technologies and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.