As part of NHS primary and secondary care services, the GP and PEDW datasets are structured to include an NHS number.
The concurrency dataset was structured with six observations for each individual representing each of the preceding 6 months.
The dataset is structured to contain a row for each day in the historical file for all influenzalike illness (ILI) visits in the clinic network.
There are more than 240,000 datasets and the data is structured into thirteen different categories ranging from agriculture to transport, science, justice, health and so on.
In this section we show that an EPI volume and a light field are structured datasets.
The final dataset was hierarchically structured with 353,120 births nested in 143 CLSCs.
For instance, the dataset is more structured and the patient population is better defined in post-approval, prespecified populations (e.g. phase 4 clinical trials and prospective observational studies) than in post-approval, non-prespecified patient populations.
Because the dataset is hierarchically structured, and in order to control for clustering of women within countries, a hierarchical linear model with women (first level) nested within countries (second level) was fitted to the data.
This data complexity refers to the extent to which a dataset is intrinsically structured such that classes of treated and control samples can be separated into distinct groups as defined by gene features (i.e. a geometric boundary can be established computationally between classes in a multi-dimensional space).
Both signalling and response datasets were organized in data structures in the form of 5-D cubes using the DataRail software [ 35]; 4 of the dimensions of the cube correspond to the different experimental conditions (cell type, time point, stimuli treatment, inhibitor treatment) and the 5th to the measured readouts (response data and signalling data).
