In one of our recent posts, we explained the difference between an ontology and a taxonomy. Although choosing an ontology over taxonomies is an important step towards smart and accurate matching, it is not the only aspect to consider. Even if you are only interested in a monolingual ontology, but even more so with multilingual ones, localization is another key feature. For high performance and satisfactory matching results, it is simply not enough for the ontology to cover your language of choice, especially not if that language is spoken in several countries. The system needs to truly understand context, including regional or national variations in occupational, legal, educational and linguistic matters. For instance, certain occupations may require official certifications or authorizations in one country, but not in another. And most often these certifications will have different names depending on the country they are issued in. A certain job title may be widely used in one country, and completely uncommon in another, e.g., joiner in the UK, Australia and New Zealand – a type of carpenter. This term is practically not used in the US (even though the largest US trade union for carpenters is called the United Brotherhood of Carpenters and Joiners of America).
Of course, this issue is not just limited to job titles and authorizations. It is also essential to understand implicit skills, i.e., those not mentioned in a job description or candidate profile but that can be derived from other information such as education and training. And required education must be factored in as well. Suppose, for instance, you are located in a Spanish-speaking country and looking to hire someone with a bachelor’s degree, i.e., who has completed undergraduate university studies. In Peru, you may ask for a Bachiller. However, in Colombia, this term will give you matches with candidates who have the equivalent of a high school degree: a Bachiller Académico or a Bachiller Técnico. If you ask for a Licenciado, another common term in Spanish-speaking countries that often corresponds to a bachelor’s degree, your Colombian candidates will have a degree more or less equivalent to a Bachelor of Education in the US.
To avoid unsatisfactory to outright useless matching results, an ontology must be carefully enriched with country-specific information such as linguistic variations, localized job titles, mapping of national classification systems and details from the country’s education system including names of degrees and diplomas, and – ideally – curricula and taught skills. This may require extensive work by subject matter experts familiar with the country in question. But it is an investment well worthwhile that will dramatically improve matching results and all associated services such as career counseling, education/job matching platforms, labor market analytics and more, as well as enhance usability of interactive services and features, for instance, with smart suggestions and typeaheads that actually make sense to the users.
You may have already found out the hard way that using standard taxonomies like ESCO does not really work in your country. If not, don’t do it. Go straight for a well-localized ontology. At JANZZ.technology, this is one of our key services for new country clients and we have successfully implemented localizations of our ontology JANZZon! for countries across the globe. If you want to enhance your system with the extensive knowledge from the world’s largest multilingual job and skills ontology, or learn more about our highly performant ontology-driven products and technologies, feel free to contact us at email@example.com.