JANZZ Highlights: How we started off 2016 successfully

2015 was an exciting and busy year for us, with projects in Europe, South East Asia and the Middle East. The complexity due to the many different languages, cultures and labor markets demanded a lot from our database maintenance team. Therefore, we are all the more proud, to have successfully mastered these projects and to have gained so much knowhow on occupation data. Our team and our central asset, our ontology JANZZon!, have learnt so much.

Occupational classifications

  • We have integrated a major part of the Indian occupational classification NCO-2004. That includes not only occupations in English but also in Hindi.
  • The entry of JSOC 2011 (Japan) and NOC 2011 (Canada) is soon completed
  • We are collecting over 14’000 jobs in Dutch, from the national Dutch classification BO&C. We are also enhancing this data with information from real life job postings.

LinkedIn Skills

As the search for the perfect matching talent or job on LinkedIn becomes more and more important, the significance of the skills you display on your LinkedIn profile increases. The network even advertises that members who register their skills will get four times more profile views. The skills users include on their profile also offer an opportunity to personalize job suggestions, adverts and search results more accurately. On the other hand, companies can search for job candidates according to their job title or skills.

Our ontology already included about 70% of all global LinkedIn skills. In order to achieve our goal “to master occupation data”, we have started to teach our ontology also the remaining 30% of these skills. For we are serious about really knowing all the skills in the world (The same is obviously also true for jobs).

Semantic Technology

Why is it so important, to include all these classifications and skills in our ontology? Why does it, for instance, not suffice that LinkedIn knows all the skills its users register? Our ontology not only registers these terms but it also interlinks them logically. In case of the LinkedIn skills, JANZZ provides significant added value through the interlinking of different languages, which makes LinkedIn’s skills comparable on a global basis. Hence, our ontology JANZZon! offers essential context and intelligent evaluation options for applications such as information systems, matching engines, job portals, CV parsers, statistical analysis and modelling tools and much more. The ontology becomes the means to utilize an enormous amount of data intelligently. Big data becomes smart data.