mydata file

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Main articles
How to start

Starting an estimation for a new species
Setting initial parameter values manually
Estimation options

Important knowledge

Typified models
Data types
Zero-variate data
Univariate data
Weight coefficients
DEB notation

User-defined files


Simplified flow chart estimation.jpg

The mydata file is where one sets the data and corresponding references.

One can either expand upon an existing mydata file or else create a new mydata file from an empty template. In your local DEBtool folder go to DEBtool_M\lib\pet and you will find zipped folders containing empty templates for the 'std' and the 'abj' models ( and respectively. You can extract the template for a mydata file, rename it and then start filling it out.

Using these empty templates is the preferred method to proceed, because errors from having old stuff that was not deleted is extremely common. Go to the AmP species list page to see what data is most common for the type of organism you are working on.

Spend time on finding correspondences between morphological and functional stages as described in the Typified models page to that of your species.

Focus on getting data and seeing what type of label it has (see Zero-variate data and Uni-variate data) to get an overview on the 'data completeness' and also learn the nomenclature. Knowing the nomenclature will give you speed in perusing the AmP species list page and seeing where similar data to yours is found which allows opening up the predict file online and pulling out the right predictions. It also is useful for having standardized and consistent names for the data in the mydata file.

Please see this youtube movie on how to add uni-variate data to a mydata file

File Structure

In the next subsections we present the structure of the mydata file following the order of appearance within the file.


In this section of the file we fill in the metadata of the entry that will be saved into the metaData structure. The fields to be filled are presented in the following table:

metaData fields Description
obligatory fields
phylum taxonomic phylum
class taxonomic class
order taxonomic order
family taxonomic family
species taxonomic species, using underscore to separate genus from species, e.g. Homo_sapiens
species_en english name of the species
T_typical typical body temperature of the organism
data_0 vector with codes for zero-variate data used
data_1 vector with codes for univariate data used
COMPLETE level of the completeness of all the data
author name(s) of the author(s)
date_subm date of submission
email email of the contact author
address institutional address of the contact author
Optional fields
submitting a modified version of an existing entry:
author_mod_1 name(s) of the author(s) updating the entry
date_mod_1 date of modification
email_mod_1 email of the contact author
address_mod_1 institutional address of the contact author
acknowledgement string with acknowledgement text

For curators only:

make sure to add and fill in these fields before submitting to the person responsible for publishing the entry to the web

metaData fields Description
curator name(s) of the curator(s)
email_cur email of the contact curator
date_acc date of acceptance


Data is separated into two types zero-variate and univariate data and are set in that order.

For any type of data the author chooses a field label based on the codes examples for zero-variate and univariate data and sets the following structures:

Data associated
data value of the data
units units of the data (try to always use the standard units)
label label string that will be used for presentation purposes
bibkey reference code for the data

On a bibkey the user can introduce more than one reference.

Language Code
Matlab {'refcode1', 'refcode2'}
R c("refcode1", "refcode2")

Optionally the user can also set a corresponding field in the comment structure for a string with any comment that clarifies the data value. In some cases the data needs information on some auxiliary data to make possible the corresponding prediction using DEB theory. The setting of this type of data is explained in the Auxiliary data section.

Weight setting

Each data point has to be assigned a weight for the estimation procedure. The weights are set in the structure weights.

Usually an automatic assignment is used, but the user can easily overwrite the standard values and present a reason for doing so in a commented line.

Pseudodata setting

Pseudodata is added to the data structure, together with the corresponding units and label.

Plot options

The plot options section is optional. If nothing is set here the graphs for each univariate data set will be automatically plotted separately. Nevertheless the user can use this section to define that some of the data sets should be plotted in the same figure.

Data packing

A technical section that ensures that the data is properly packed to be exchanged between functions.

Discussion points

The user should add strings with "discussion points", that is interesting points on the data or results that another interested person should find important.

These strings are packed in the metaData structure in the field discussion.


Any additional facts that are not used as data can be added here.

Each fact is given a label (usually F1, F2, ...) and they are packed in the metaData structure in the field facts. A reference for each fact should be added to a bibkey field in metaData.


For every bibkey code for data or facts a reference should be listed here using the standard types and fields one can find in the Bibliographic information file in wikipedia.

The references are packed in the field biblist in metaData.

Auxiliary data

Some predictions need not only the DEB model and parameters to be computed, but also auxiliary data. Examples of auxiliary data sometimes needed are presented in the following table:

auxData fields Description
temp temperature
length initial lengths
JX ingestion fluxes
food food availabilty

Warning: make sure the field name of the auxData is not the same as a field name in structure par or cPar .

When auxiliary data is needed, it is set close to the data that it corresponds to. And in the same way as data, not only the value must be provided, but also the corresponding units and label.