The data conservancy instance: Infrastructure and organizational services for research data curation

Digital research data can only be managed and preserved over time through a sustained institutional commitment. Research data curation is a multi-faceted issue, requiring technologies, organizational structures, and human knowledge and skills to come together in complementary ways. This article provides a high-level description of the Data Conservancy Instance, an implementation of infrastructure and organizational services for data collection, storage, preservation, archiving, curation, and sharing. While comparable to institutional repository systems and disciplinary data repositories in some aspects, the DC Instance is distinguished by featuring a data-centric architecture, discipline-agnostic data model, and a data feature extraction framework that facilitates data integration and cross-disciplinary queries. The Data Conservancy Instance is intended to support, and be supported by, a skilled data curation staff, and to facilitate technical, financial, and human sustainability of organizational data curation services. The Johns Hopkins University Data Management Services (JHU DMS) are described as an example of how the Data Conservancy Instance can be deployed.