Hi @tard.gabriel , my project idea is to see if I can find a way to import data related to the medical field, in an attempt to help my significant other with her Ph.D. In a simplified way, it is about medical data related to diseases and causes for a disease, but her doctorate is obviously more advanced and goes down to the molecular level, proteins etc.
The way I am starting to implement this is based on, let's say a doctor's observation of a patient's illness (symptom), gathering the attributes of that symptom and in the end linking each symptom (or multiple symptoms) to a disease that it causes.
In a simplified way I can create this, with a single hop in between the "Symptom" node to the "Disease" node and put some properties with associated values on the relationship (CAUSES relationship in the below image).
However, some Symptom attributes are not a single "concept" as in: Fever is a symptom, but it has attributes like how the debut of the fever was, when the debut occurred etc. Also the when part of the debut can be hours or days or weeks old, which are all attributes.
How I envision it, but actually currently I'm just trying to see if I can implement it, is that the Symptom node (Fever) has attribute nodes connected to it (how, when) and the how and when nodes also have attributes of their own (how.sudden, how.gradually, when.days etc.).
At the end of these "leaf" nodes I will have a relationship pointing to a illness.
In reality this is more niched to a certain problem she is trying to solve, but nevertheless I thought that Neo4J is the right technology to use in this type of problem. This would be more like a dataset which can be queried based on her results and see if there is a path from a "symptom" to an "illness".
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