## 3 Discussion and Conclusions
Open Food Facts ontology allows for many ways of integration, including MongoDB dumps, CSV exports, and RDF data export, and also uses JavaScript Object Notation (JSON) to read data. This means data about packaged food can be exported to the Open Food Facts database easily. FoodWiki will also be able to use its mobile app to access the information in the Open Food Facts database, in addition to the Turkish Food, Agriculture and Livestock database. Such integration may also motivate other ontologies that track packaged food at the national level to become accessible from a global platform. FOODS--Diabetes Edition (based on [22]) is an example of such ontologies. It consists of an ontology specifically tailored to Thai food and aims at helping people with diabetes to monitor their food intake through a Web-based system. FOODS covers all kind of Thai food, and not only packaged food items. It similarly uses OWL and can be integrated with Open Food Facts. Furthermore, using the concept of Food Product Ontology [21], the coverage can be extended to help manufacturers, retailers, governments and institutions publish their data related to the food domain in a way that maximizes the reuse of data. Food Product Ontology fosters sharing and collaboration among several stakeholders. The main advantage of Food Product Ontology is that it extends the knowledge to contents and ingredients as described by the manufacturer. Food Product Ontology also uses OWL language to describe the classes and objects of food products. AGROVOC [19] covers a large and mature multilingual thesaurus of all kinds of food. AGROVOC represents a great degree of consensus regarding terminology, and is used by specialized digital libraries and digital repositories for indexing and retrieving data. From this perspective AGROVOC can be considered as the best candidate (basis) for a unified food ontology that has worldwide coverage of all kinds of food. However, the main issue with AGROVOC is that it is accessed and controlled by experts under the administration of UN agencies. This means there is a conceptual difference on how people interact with AGROVOC and Open Food Facts. In Open Food Facts, a passionate individual may instantly scan a barcode of a packaged food item from any place in the world and add it to Open Food Facts database (crowdsourced input). This option is not available in AGROVOC. From this perspective, the direct integration of both ontologies is not possible, but both of them complement each other and each has its merits regarding the approaches employed. They can thus together form a helpful basis for developing a new, universal and more comprehensive food ontology in the future. Critical to the success, scalability and long-term sustainability of the above mentioned \"smart diet assessment and recommendation\" engine will be the quality and accuracy/up-to-datedness of the food products data and the clinical/dietetics evidence in the ontologies powering it. Mechanisms for regular updates (e.g., as medical and dietetics knowledge advances and new research results become available and/or as food manufacturers modify their existing products or release new ones) and for integrity checking/quality assurance (particularly for any crowdsourced input) will become an essential ingredient of such an engine and the associated ontologies. The use of appropriate clinical terminologies (which are themselves ontologies) will also prove indispensable when describing and reasoning with disease conditions and patients' medical profiles in the context of the \"smart diet assessment and recommendation\" engine [14; 15; 16].