| | 39 | == Task 4: Explore suitable ontologies for features using Zooma == |
| | 40 | ==== Primary goal: see if we can cleanup feature descriptions by annotation with ontologies and thus improve searchability ==== |
| | 41 | * put all features we have through Zooma for automated ontology assignment - despoina |
| | 42 | * evaluate this list with an expert - rolf? |
| | 43 | * see if we can use that to reannotate data that was not automatically annotated |
| | 44 | * do an experiment with users to see if this improves searchability - despoina |
| | 45 | |
| | 46 | == Task 5: Convince biobanks to use the catalogs also locally for their data == |
| | 47 | ==== Primary goal: harmonize the way that all biobanks manage their data so it is more easily integrated ==== |
| | 48 | * use lifelines as example |
| | 49 | |
| | 50 | Beyond original remit (so not only metadata but also data!) |
| | 51 | |
| | 52 | == Task 6: Explore use of DataSHaPeR to map between studies == |
| | 53 | ==== Primary goal: see if we an make pairwise rules between features such that data of two studies could be merged ==== |
| | 54 | * need way to express mapping algorithms, can collaborate with P3G/DataSHaPER - despoina & morris |
| | 55 | * integrate DataSHaPER rules into the catalog |
| | 56 | * expand the catalog with some real data in collaboration with lifelines? |
| | 57 | * test wether the rules work |
| | 58 | NB this is in preparation of the BioSHARE project. |
| | 59 | |
| | 60 | == Task 7: Exlpore use of DataSHIELD method == |
| | 61 | ==== Primary goal: DataSHIELD allows meta analysis between projects by calculating statics locally and then sharing them between projects ==== |
| | 62 | See: http://ije.oxfordjournals.org/content/early/2010/07/14/ije.dyq111 |
| | 63 | |
| | 64 | * create a web service to calculate statistics locally |
| | 65 | * have a federated interface to bridge local data into the meta analysis |
| | 66 | * setup one of the catalogs as being the 'master' to collect and integrate the results |
| | 67 | |
