Learnings from Multi-Source Enduring Linked Data Assets (MELDAS)

Main Article Content

Geoff Neideck


Demand continues to grow for accessible and large scale linked data assets to answer complex cross-sector, and cross-jurisdiction research questions. To meet this demand, a number of Multi-source, Enduring Linked Data Assets (MELDAs) have emerged including the National Integrated Health Service Infrastructure (NIHSI), National Disability Data Asset (NDDA) and Multi-Agency Data Integration Project (MADIP). Using these MELDAs has proven much more efficient than project-specific linkages, and provides consistent national data assets for multiple uses. However, the development of these assets raises new challenges, including complex data models, governance, and access arrangements, and new approaches to analysis.

Objectives and Approach
Through developing the NIHSI Analytical Asset in collaboration with state/territory and Federal Government partners, the AIHW has identified challenges in traditional linkage approaches, which require innovative approaches to ensure high quality linkage. As AIHW commences scoping on new MELDAs, we are taking lessons from building the NIHSI and applying them to future design.

AIHW’s development of MELDAs across jurisdictions and portfolios provides new learnings on how to address advanced real world data integration issues. This review will focus on lessons learnt at the Australian Institute of Health and Welfare (AIHW) working with new data sharing arrangements, applications of technologies and innovative approaches to streamline MELDA processes.

Conclusion / Implications
The learnings from the AIHW development of MELDAs will assist others developing enduring assets to establish effective sharing arrangements, governance and technical solutions to ensure efficient management. These learnings will save time and resources, and prompt further discussion on a gold standard for building MELDAs moving forwards.

Article Details

How to Cite
Neideck, G. (2020) “Learnings from Multi-Source Enduring Linked Data Assets (MELDAS)”, International Journal of Population Data Science, 5(5). doi: 10.23889/ijpds.v5i5.1569.