SHARE has a schema-agnostic approach to aggregate diverse and distributed scholarly metadata in order to build a broadly inclusive open data set about scholarship to power innovation and discovery. In an environment where metadata standards vary widely by discipline or domain, distributed digital assets - while intellectually linked to other objects in the ecosystem - may lack the necessary information to intuit these relationships directly, including strong identifiers for people, institutions, or sources of funding. Aggregating metadata across diverse data sources and repositories is essential for making related content discoverable - especially content that may not currently have first-class status in scholarship. Related contextual objects, beyond publications, support replicability, reproducibility, and reuse. It is impractical to ask each of these diverse data sources to adopt and implement a common metadata format when the incentives for doing so are low. Instead, SHARE is harvesting, normalizing, and linking dispersed assets into an aggregated, open data set of research outputs. This is producing tangible demonstrations of the power of a public goods database to provide notifications or reports of research activity and promote discovery. These demonstrations will entice institutions to enhance their metadata in SHARE or use SHARE to clean and augment metadata in their repositories.
All Science Journal Classification (ASJC) codes
- Library and Information Sciences