Opal is OBiBa's core data managment application. This server application provides all the necessary tools to import, transform and describe data. Subject’s identifiers can also be managed at data import and export time.
Thanks to its integration with R , complex statistical analysis and reports can be performed. The implementation of the DataSHIELD process allows advanced statistical data analysis across multiple studies without sharing and disclosing any individual-level data.
Being integrated with Amber and Mica, studies using Opal can seamlessly and securely import data collected with Amber. They can also create web data portals with Mica that query Opal databases to obtain real-time aggregated reports on subject's data.
Secured REST web services are also available allowing to automate server management (Python command line tools) or to access to data (from R or Python, or any tools that are web-capable).
Here are some of the main features of the Opal’s data warehouse technologies:
Resources are datasets or computation units which location is described by a URL and access is protected by credentials. When assigned to a R/DataSHIELD server session, remote big/complex datasets or high performance computers are made accessible to data analysts. Opal provides an interface for managing the access to the resources and assigning them to a R/DataSHIELD server session, in integration with the resourcer R package. When using resources, the Opal installation is very light-weight as no database and no import process is required: the data are accessed where they are originaly located, from the R server.
Opal provides the software infrastructure to create virtual tables called "views" of derived variables that can be persisted on disk or exported into files. Main features are:
Opal provides a state-of-the-art software infrastructure for data encryption, participant identifiers management and user authentication/authorization. Main features are:
Studies's operations involve file management and exchanges. Opal comes with its own file system to facilitate these processes. Main features are:
Opal includes a module enabling data statistical analysis using R. Main features are:
Opal includes a module enabling data statistical analysis using Python. Main features are:
Opal's tables can be queried with SQL:
Opal automatically indexes data imported in its embedded search engine (ElasticSearch ). This allows very fast retrieval and complex querying of the data. Main features are:
Opal is built on REST web services: everything is accessible through an URL. Any client that can make an HTTPs request can be a client to an Opal server. Main features are: