Transforming Health Research Collaboration to Actionable Insights
This presentation demonstrates the findings of the "Data CoP for Health and Wellbeing , a collaborative project that aims to transform research information into insights on research-industry collaborations within the health sector. By creating a secure, cloud-based environment on Azure, organisations information is hosted and converted into an augmented collaboration graph, and other visualisation and decision support products. This process connects siloed information across multiple health organisations, creating a comprehensive research collaboration network. A key objective is to create capabilities at research institutions and their partners to collect, connect, and generate actionable insights from their research-industry collaborations. This work leverages persistent identifiers beyond academic publications, leading to a better understanding of the required information systems for similar analyses in research institutions and their industry partners. Furthermore, the project enriches funding information by integrating research information from participants. This integration unlocks access to information on many grants (e.g. NHMRC, NIH), philanthropy funding, industry, and government contracts. Central to our project are data workshops, where we collaborate with subject matter experts to generate valuable insights. These insights are visualised through data dashboards, both private and public, that animate the collaborative data derived from these workshops. Public dashboards contribute to the Australian Research Data Commons (ARDC) Research Link Australia platform, enhancing transparency and accessibility. Funded by ARDC and partnered with the Research Graph, DHCRC, Orygen, HRI (University of Canberra), HEAL Network, Infoxchange, and Insights Data Lab at Griffith, this project investigates the infrastructure required to enable such analysis on a larger scale in Australia.
Institutions
- Swinburne University of Technology (AU)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-10-31
- DOI
- https://doi.org/10.5281/zenodo.15293560
- Primary Topic
- Pregnancy and preeclampsia studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00