Frameworks for Evaluating Digital Sustainability in the NIH HEAL Data Ecosystem
Heather Barnes
Distributed research data ecosystems such as the NIH HEAL Data Ecosystem (HDE) lack a singular, cohesive framework for assessing their long-term sustainability. Research data ecosystems like the HDE provide a central data-discovery portal (similar to a data catalog); however, ecosystem architecture design relies on independently-managed data repositories with disparate architectures and governance frameworks. These types of systems tend not to fit neatly into existing digital sustainability frameworks such as the NDSA Levels of Preservation. In addition, most digital preservation literature tends to focus on the sustainability of *centralized* data archives rather than *distributed* data ecosystems. We propose that the sustainability of distributed research ecosystems may be evaluated by integrating concepts from existing digital preservation assessment frameworks standards that, in combination, address many of the digital sustainability factors that apply to organizational, repository, and dataset levels of granularity within a distributed system. We experiment with two such possible frameworks. First, the Digital Preservation Coalition’s Rapid Assessment model includes several metrics that cover organizational/repository *architecture and governance* and could be extended to apply to a distributed data ecosystem. Second, the relatively recent FAIR data principles provide guidance for evaluating ecosystem practices at the *dataset level*. This exploratory paper aims to spark discussion and additional research around how best to create and implement efficient frameworks for evaluating digital sustainability in a data ecosystem that depends on non-centralized architecture and governance.
governance, resourcing, and management for dp scaling up