How do we interpret the Degree of interest graphs?

Harder than it seems

… because it affects the data model level itself.

To do this cleanly, we need to instantiate a new type of entity: let’s call them pseudocodes. They can be associated to an annotation, like ordinary codes, but do not constitute a semantic interpretation of the primary data. They are just a bookmark.

An annotation would have the usual fields (annotation_id, entity_id, entity_type, quote, tag_id etc.) but also a pseudotag_id one. You could retrieve content bookmarked with research question by a database search, but GraphRyder would ignore pseudocodes and build all views just with the codes.

If you think that some codes could be born as real ones and then become pseudo (or viceversa) in the course of the study, then we could implement a different solution: a Boolean field like pseudo in the code entity. The dashboard would know to include codes only if pseudo == True .

UPDATE: no, taxonomy terms are not a content type and we cannot customize them with extra fields. A workaround is a naming convention: for example pseudo:research question. Them we insert an IF condition in the code that discards all codes whose name begin with pseudo: . Not very elegant though.

@melancon | @Jason_Vallet : any thoughts?

Another solution would be to use browser or online bookmarks!

Notice how this collaborative, data-oriented way of doing ethnography is forcing you to clean up your way of working, You have to enforce logical consistency from an early stage. I think this is likely to be a boon (though it can be annoying).