Scientific projects and data sets organization

Scientific projects and data sets organization

Storage quotas are being allocated on the basis of a scientific project with the need for large storage capacity of planned high-volume producing experiments.

A project may consist of several datasets originating from different types of experiments, and thus being of different data types (in this context the data format as such is of less importance). Common to all datatypes is that each data set will have data processed to different levels:

  • Cancer study project X
    •   Microarray gene expression data
      • Raw data (images, txt files with extracted meassurements)
      • Primary data (normalised and preprocessed data matrices)
      • Analysis data (gene lists and assoicated statistics ++)
    • High throughput sequencing data
      • Raw data (images, base-calling files ++)
      • Primary data (sequence reads)
      • Analysis data (mapped or assembled sequences ++)
  • Meta genomics project Y
    • ....

 

In the interim solution, files must be organized in a hierarchical folder structure enforcing the relations above

 


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