= BBMRI =
=  =
== Theme 1: fill the database ==
==== First goal: get !LifeLines features included in BBMRI biobank. ====
 * get BBMRI catalog running : (done)

 * import the Excel (done)

 * biobank is a kind of panel

 * Lifelines is one of the biobanks

 * Get from Joris is a Excel export (done)

==== Next goal: import more biobank information which we get from our BBMRI-EU colleagues ====
== Theme 2: start with 'semantic molgenis' ==
==== First goal: link MOLGENIS to external ontology ====
 * first enhance N3 file with external mapping:

 * then test if we use that ontology in SPARQL query

 * if works: then update the MOLGENIS model + generator

==== Next step: investigate ontologies that should be linked ====
 * how about biobankers list of Marco Roos?

 * disease ontology?

 * material ontology?

=== Actions ===
 * Connect to Pedro to investigate his 'semantic molgenis' work?

 * Connect to BBMRI-EU to request more data?

== (Notes) ==
 * look into data 
 * cross links —> protein underlying peaks ?
 * biobanks : phenotypic information e.g lifelines project data : annotate question : ARE there other data set in the world? —> merge into lifelines data …
 * next step : come up with an "algorithm" that does the mapping . Let's assume we have 2 studies , we would like to merge and export the results  . 
 * it's not really an algorithm , but more of a "correspondence " rule …If we have 2 questions - "Are they compatible "? or if not what kind of conversion should be done in order to match each other? So then we'll have a meta study ..for each biobank —> mapping 
 * So we have available 5 biobanks —> project on a single parameter —> bigger statistical analysis  . 
 * How to model it ?
 * RDF rules?
 * parameter in one biobank / corresponding parameter in the other biobank ?
 * a potential pilot would be like to 

 1. take 2 pheno DBs , 
 1. fill with lifelines data ,
 1. query that merges the set —> maybe a sparql query ?
 1. different question