This page is designed for data managers new to DataSHIELD. It assumes that your systems operator has succesfully completed the steps described here and therefore have either an Armadillo or Opal server running.
The key tasks for a data manager are:
Armadillo and Opal are two types of DataSHIELD server. Armadillo is built and maintained by Molgenis, and was designed as a light-weight server specifically to implement DataSHIELD analysis. Opal is built and maintained by Obiba, and is a server which supports DataSHIELD analysis and also contains many additional features.
Both solutions share core functionality, and can be administered either using a user interface or R. However, the steps involved will be different. Full documentation can be found here:
Armadillo documentation
Opal documentation
For both Armadillo and Opal, most tasks can be completed via the UI. However, for more complicated tasks or tasks that need to be repeated, it can be more efficient to do these using R. The Armadillo R package for data managers is molgenisArmadillo, whilst the opal R package is called opalr. To learn more about R and how to install it along with these packages, see this page.
For researchers to be able to use DataSHIELD, you first need to upload your data to your local server. This can be done either using the user interface (Armadillo, Opal) or via R (Armadillo, Opal). If the data needs to follow a specific format defined in dictionaries you can use dsUpload (R) which is a collection of tools used to upload data into DataSHIELD backends (Armadillo, Opal).
As a data owner, you might upload many tables or resources to your server. However, individual researchers may only need access to a subset of this data for their research. Rather than giving researchers access to all of their data, it may be the policy of your institution to give access only to the subset of data required. Subsets of data can be described as 'views', and can also be created either via the user interface (Armadillo, Opal) or R packages (Armadillo, Opal )
To ensure data security, users are normally only allowed access to the subset of data which is relevant to their project, and for a set period of time. Managing which users have permission to access which projects can be done in the UI for both Armadillo and Opal.
As a data manager, you also control which DataSHIELD packages are installed on your server. To make this process easier, analysis profiles have been created. These are docker images which consist of bundles of R and DataSHIELD packages which are commonly used in research. Analysis profiles are handled using the UI in both Armadillo and Opal.