Introduction to metadata on Pennsieve

In order to maximally leverage scientific and clinical data, it is critical for researchers to provide detailed and contextual metadata. The Pennsieve platform includes advanced infrastructure to link scientific data to complex metadata schemas. Users can define custom metadata schemas and leverage this to query, explore, and interact with data in context.

Metadata support on the platform is based on the ability to create user-defined data models. Models can be interpreted as the nouns of a dataset (i.e. Subject, Experiment, Study, Diagnosis) and are used to describe the datasets in terms that are meaningful to the user. Each model has properties that describe that model (i.e. properties of a Subject may include Age, Height, Weight, Gender, etc.). In addition, users can define relationships that might exist between records of particular models. For example, a particular Patient X can be enrolled in Study Y.

Finally, metadata records can be linked to files in the dataset. This allows the user to create complex metadata records describing specific files. Or, for example, users can link metadata records describing experimental settings, and associate these settings with the file-output of an experimental trial.

Metadata schemas and records can be created using the web-interface, but all functionality is also made available programmatically in our client tools. See the rest of this section and the developer documentation for more information.