Product categories are based on a hierarchy (ontology) in the system, meaning entities can have relations such as synonyms, parent- and children-entities. This makes the search system smarter and for the user assure easier pathways to target results.
Through examples of product categories, substances, and ingredients it is the easier way to demonstrate the logic of entity ontology and how to use it:
PRODUCT CATEGORIES ONTOLOGY
Product categories are based on a hierarchy (ontology) in the system. The examples below show what this looks like for cereals and milk. With this ontology, it makes it possible to exclude certain associated products (children) and also expand the search to broader “parent” categories when applicable.
A user begins by typing in a specific term in the search bar. From there the system will recommend applicable products or product categories. The user can then select the product(s) and from the dropdown list and add them to the search. Once done, clicking on the product will open the hierarchy as per below.
From this view, the user has the choice of including or excluding items from the list by checking or unchecking them ì, and in that way adjust the results exactly to their needs and target results they are looking for.
In this way, the search is easier, as with one item the subordinated items also included in the search, and there is no need to type all of them individually.
SUBSTANCE ONTOLOGY
Example PFAS substances - parent, children, and synonym relations:
Just as an example idea, we can mention here that by checking and unchecking certain chemical forms of your interest, you can narrow down your search results with less effort than typing them one by one. On the side of that, you have insight or control into the exact terminology that the system includes under one term "PFAS".
INGREDIENT ONTOLOGY
This is specifically developed for Digicomply's ingredient database for food supplements - Nutriwse (for more information please see Food Supplements Compliance Assessment)
It is designed to support ingredient recognition through the complex world of multiple scientific and official names, bridging them with other known, so-called common names, of the heterogeneous groups of ingredients, such as nutrients and their allowed chemical forms, various substances, botanicals and their derivates, probiotics and inactive ingredients as well, including food additives and flavorings.
An example of this data architecture can be imagined as botanicals > plants > Achillea millefolium - where ingredient ontology correlations assure the recognition of this botanical ingredient through its other scientific names, common names, and also associate its relevant derivates, such as essential oil, extract or a tincture, and/or other relevant forms relevant for spect of ingredients, such as powder, concentrate, juice, etc. based on the regulations and other positive or negative lists of relevancy as regards regulatory compliance.