Enable Discovery

Why?

Including connections in metadata is vital for enabling the discovery of research outputs and resources. By establishing links between related resources, such as citations and references, metadata helps researchers discover relevant and interconnected resources. These connections enhance research exploration, help reporting, and facilitate the advancement of knowledge.

What?

DataCite offers advanced tools that leverage the metadata provided to enable discovery, analytics, and reporting capabilities. By working with metrics and relational metadata files, DataCite facilitates the visibility of research impact within its discovery system DataCite Commons. Providing analytics dashboards, DataCite Commons empowers researchers and organizations to gain insights and make informed decisions based on comprehensive and interconnected metadata.

In addition, the Data Citation Corpus, developed by DataCite, provides you with a centralized and comprehensive repository of data citations from diverse sources, enabling you to monitor data citations.

The DataCite Usage Tracker is an easy-to-implement tool for usage metrics, creating reports for repositories.

How?

Metadata is essential for the discovery of research outputs and resources. In particular, connection metadata plays an important role in increasing the visibility and impact of each resource. The best way to set up connections is to use persistent identifiers PIDs for resources (DOIs), people (ORCID iDs), and organizations (ROR IDs), as they support global metadata standards. In addition to the use of PIDs in connection metadata, the accuracy, completeness, and relevance of descriptive metadata make research outputs more visible and easier to find. PIDs and metadata together form the PID Graph, which is powered by the DataCite GraphQL API. DataCite Commons provides a public web search interface to the PID Graph.

The DataCite Usage Tracker is a hosted service that collects repository usage stats using a Javascript tracker (not log file processing). It generates SUSHI reports for repositories and never stores any personally identifying information.