While the UK is one of only three countries with mandatory data submission for national audit, and the data completeness and quality were very high for many data-fields, there are inevitable problems in using an audit database for research and then using that research for audit.
With so many data entry fields and various types of text boxes for those fields, it took much back and forth communication between curators and the software developer to find the best design for data entry and editing.
Every sampling interval Δt, each sensor senses the field and transmits it directly to the FC with probability p. The sensing probability p is suitably chosen in order to let the FC acquire sufficiently many data for field reconstruction.
As many of the data fields as possible were either multiple choice or numeric.
Concrete perspectives with new approaches are often lacking, while many data from other fields could allow drawing more perspectives and feeding the debates and discussions.
There aren't many data, because a field such as materials science is hard to parse.
The data format closely follows that of the Smithsonian's GVP database with many of the same data fields and codes, although the underlying structure of LaMEVE is not identical.
Each MetaboCard entry contains more than 110 data fields many of which are hyperlinked to other databases (KEGG, PubChem, MetaCyc, ChEBI, PDB, Swiss-Prot, and GenBank) as well as to GeneCard IDs, GeneAtlas IDs and HGNC IDs for each of the corresponding enzymes or proteins known to act on that metabolite.
The system has been adopted by many data providers in the fields of genomics and proteomics.
Additionally, many of the important data fields in Supplementary file 1 are conclusions rather than data (e.g., "yes", "never-paused", etc).
