DataSHIELD support is freely available in the DataSHIELD forum by the DataSHIELD community. Please use this as the first port of call for any problems you may be having, it is monitored closely for new threads.

DataSHIELD bespoke user support and also user training classes are offered on a fee-paying basis. Please enquire at datashield@newcastle.ac.uk for current prices. 

#load libraries
library(DSI)
library(DSOpal)
library(dsBaseClient)

builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1",  url = "http://192.168.56.100:8080/",
               user = "administrator", password = "datashield_test&",
               table = "CNSIM.CNSIM1", driver = "OpalDriver")
builder$append(server = "study2", url = "http://192.168.56.101:8080/",
               user = "administrator", password = "datashield_test&",
               table = "CNSIM.CNSIM2", driver = "OpalDriver")

logindata <- builder$build()

connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")

DSI::datashield.logout(connections)

In the default method of generating a DataSHIELD histogram outliers are not shown as these are potentially disclosive. The text summary of the function printed to the client screen informs the user of the presence of classes (bins) with a count smaller than the minimal cell count set by data providers. 

Note that a small random number is added to the minimum and maximum values of the range of the input variable. Therefore each user should expect slightly different printed results from those shown below:

The functions ds.contourPlot and ds.heatmapPlot use the range (minimum and maximum values) of the x and y vectors in the process of generating the graph. But in DataSHIELD the minimum and maximum values cannot be returned because they are potentially disclosive; hence what is actually returned for these plots is the 'obscured' minimum and maximum.