The unique, multilingual and most comprehensive job and skills ontology. Worldwide.
Our job and skills ontology JANZZon! is the largest multilingual encyclopedic knowledge database in the area of occupation data (in particular, jobs, job classifications, hard and soft skills, training/qualifications, etc.) currently available. Both data-driven and expert consultation taxonomies are integrated into JANZZon! Amongst others, it covers O*Net, ESCO, DISCO II and UK skills taxonomy from Nesta. The occupation data is updated on a regular basis. JANZZon! follows the OECD Principles on Artificial Intelligence (AI).
Via JANZZjobsAPI, you can connect to JANZZon! as a DaaS solution for your application.
JANZZon! is, for example, ideal for applications in the following areas:
- Job and training information systems
- (Job/skills) matching engines
- CV parsers and CV databases
- ATSs, CRM, ERP and other applications in the area of personnel recruitment
- Job portals, including social networks, career pages and aggregators
- Applications in the area of government labor market and placement measures
- Statistical analysis and modelling tools
- Full-text analysis and search tools
Thanks to its already extremely large number of poly-directional concepts, our job and skills ontology JANZZon! is able to generate unique conceptual relationships and facilitates previously unknown intelligent possibilities in the following areas:
- Data enhancement and indexing, including context and (syntactical and/or content based) request completion for full-text searches and CV parsers
- Multilingual semantic skills and job matching
- Automatic allocations of and between different classification systems
- Use of complex and unstructured data in the areas of gap analysis and benchmarking
- Various evaluations and applications in the areas of statistics, data modelling and big data
Finally turn your big (occupation) data into smart data with JANZZon!
Selected key figures for the JANZZon! job and skills ontology
|Number of hours invested in development to date||> 800,000|
|Available languages (in progress or completed)||60+|
Arabic, Azerbaijani, Basque, Bengali, Bulgarian, Catalan, Chinese (traditional, simplified), Croatian, Czech, Danish, Dutch (including Flemish), English, Estonian, Finnish, French, Galician, German (3 localized versions: Germany, Switzerland, Austria), Greek, Hausa, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Khmer, Korean, Latvian, Lithuanian, Malay, Maltese, Maori, Northern Sami, Norwegian (Bokmål, Nynorsk), Oromo, Pashto, Persian/Farsi, Polish, Portuguese (Portugal, Brazil), Romanian, Russian, Serbian, Slovak, Slovenian, Spanish (Castilian, several Latin American variants), Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, Yoruba,…
|Number of concept nodes||> 2.6 million|
|Number of occupation/profession concepts||> 140,000|
|Number of capability/skill concepts||> 1 million|
|Number of specialization concepts||> 57,000|
|Number of function concepts||> 24,000|
|Number of soft skills/social skills concepts||> 157,500|
|Number of training/qualifications concepts||> 700,000|
|Number of nodes and relations||> 1.5 billion|
|Number of terms (all languages)||> 450 million|
|Standard classification systems (in progress or completed)||> 160|
|Number of occupation classes||7|
Private knowledge graphs in connection with our job and skills ontology JANZZon!
Within JANZZon!, there are various options for covering your very individual needs and requirements in a simple, cost-effective and sustainable manner. For example, JANZZon! also allows for specific private ontologies / knowledge graphs to be configured and integrated. Terms that are important to you can also be incorporated, regularly updated and maintained (e.g. organization-specific functions, product names and versions, abbreviations, certifications and diplomas, special thesauri).
Furthermore, it is possible to influence the use, prioritization and context of specific concepts. For instance, it is possible to use country-, company- or language-specific descriptions of terms, while you can also define special spellings or preferred terms in your applications as default settings. These may include job titles like «joiner» or, depending on the area, «carpenter».
Alongside the standardized occupation classes (OCs 1 to 7) and their weightings and relations available in JANZZon!, for example, different solutions are also possible in accordance with your requirements.
Build or buy?
Benefits of and reasons for using JANZZon! as a cloud solution.
A recurring and important question in the area of taxonomies and knowledge graphs is whether it is better to develop and maintain your own ontology or whether it makes sense to purchase one at some point or use one. This question is not only relevant to those companies which have already attempted to develop their own knowledge graphs, but which, due to a shortage of specialist knowledge, are no longer able to develop it further or, for example, are unable to maintain it as a result of insufficient resources and/or financial means. In recent years, hundreds of thousands of often very expensive digital graveyards with varying scopes have emerged in the area of occupation data. In most cases, ontologies are already outdated on the day of purchase and no longer up to date. This is particularly true if you are looking to cover extremely heterogeneous and dynamic fields of knowledge such as occupation data. Most ontology solutions are not even suitable for modern applications such as skills and/or job matching.
In almost all cases, the facts thus invariably argue in favor of a solution such as our job and skills ontology JANZZon!. JANZZon! provides you with a secure, sustainable and cost-efficient cloud solution that nevertheless allows you to use almost all options for the desired applications and areas of use. You also benefit from the wisdom of crowds: from the many other users of JANZZon! in different languages, sectors and specialist areas as well as from the ongoing enhancements and updates they make. Additionally, the use of a unique combination of the Mechanical Turk method and current machine-learning approaches enables us to continually enrich our job and skills ontology with updates and upgrades. All this without having to make available the, in most cases, extensive resources yourself and within the framework of clearly structured price plans tailored to the volume and scope of your usage.
Below you can find sample applications of our DaaS solution JANZZon! Of course, other functions and applications that have not yet been implemented are possible. We would be happy to check new ideas and areas of use with you.
JANZZon! – application example 1: web portal for career videos
Improving the (multilingual) search and matching functions of a web portal for career videos
A web portal with video profiles of professionals in various fields, intended mostly for young users who want to inform themselves in greater detail about a specific profession or wider career opportunities, required improvements of the search and matching functions, above all in the fields of data enhancement, synonyms and related search terms/occupations/concepts. Multilingual functions were previously not possible.
Improvements made possible by JANZZ.technology
A simple link via JANZZjobsAPI has realized a sustained improvement in the search and matching functions, for example through an extended glossary and by supplementing the required occupation data and terminology with synonyms, related occupations and professions as well as translations of the terminology drawn from the comprehensive job and skills ontology JANZZon! in real time. Over 60 languages are currently available for JANZZon! with many more to come.
Solution and methodology
- Detailed discussions with the project managers allowed for a clear conceptualization of the process, and areas with the greatest potential for improvement could easily be identified
- The data request protocol for JANZZjobsAPI was drawn up and implemented within a very short period
Accomplishment and results for the client
Substantially improved (semantic) search and matching results in terms of quality and relevance, including in the context of related terms and concepts, which could not have been achieved with conventional full-text functions and matching engines. Stable and inexpensive link via JANZZjobsAPI for real-time enquiries. This has also proven effective in terms of the performance of large quantities of database enquiries. In addition, the link to our job and skills ontology JANZZon! ensures that clients receive the very latest HR and career data at all times, thanks to the systematic maintenance and continuous expansion provided by JANZZ.technology. Possible future JANZZon! applications could concern the improved semantic and multilingual matching of existing video tags.
JANZZon! – application example 2: semantic search
Improved semantic search queries thanks to profound background knowledge
In contrast to conventional full-text searches, the semantic search with the help of JANZZon! uses extensive contextual and background knowledge in order to identify the right datasets and to filter out datasets that most conventional search engines would wrongly list in the search results.
The extensive contextual knowledge provided by our job and skills ontology JANZZon!, for example, allows the search to relate «knowledge of investments» with «knowledge of asset management» and also «Microsoft Word» with «word processing» or «office application software». In addition, search queries also include synonyms and, if desired, designations and terms from other languages. This means that in addition to «CEO», terms such as «Geschäftsführer/-in», «Geschäftsleiter/-in» or «Managing Director» appear, but no mismatches such as «Assistant to the CEO» or «Secretary to the Managing Director».
The results and the precision of semantic search and matching processes are dependent upon the scope and depth as well as the quality and comprehensiveness of the applied contextual and background knowledge and upon the deployed ontology.
An extensive and multi-layered job and skills ontology such as JANZZon! also covers above all «real everyday language use» of users in the various applications, industries and languages. Without this widest-possible coverage, which sometimes also includes highly «creative user terminology», an ontology cannot be successful in the long term. Over the last decade, for example, the term «Employee for Copies and Archive» has reappeared as «Executive Document Manager», or «Cleaners» have been renamed «Facility Managers» – not to mention curious new job titles such as «Data Ninja», which could be a data engineer, a data analyst, a data manager or more.
Moreover, many occupations, even very traditional ones, have been given more up-to-date designations in recent years. However, these are often peculiar titles that are rarely used in other contexts. For this reason, common and conventional terms such as «Butcher» or «Nurse» need to continue to be recognized, and not merely new titles such as «Meat Processing Professional» or the generic term «Healthcare Professional». Because JANZZon! is also fed to a large extent by the thousands of entries made by real users and based on sources such as real job offers in all industries, languages and regions or CVs of job seekers, the highest-possible degree of topicality and practicality in terms of search and matching processes is guaranteed. However, as even extremely extensive ontologies such as JANZZon! can of course never comprehensively cover all terms, industries and languages, in specific cases we also deploy classic search mechanisms in the field of full-text search.
The crucial tasks of structuring, continuously expanding and maintianing as well as updating and refining highly complex ontologies such as JANZZon! require expert tools, for example ontology editors, combined with long-standing experience and a comprehensive set of skills within the field of knowledge modelling. Because this work, which tends to be complex and time consuming, can rarely be covered by in-house resources, our cloud solution JANZZon! with its many individual customization options – including integration of entire private ontologies – offers the optimum and most cost-effective solution for your search and matching application.
Some of the key characteristics of JANZZon!
- Semantic, language-sensitive query completion: conventional search engines tend to offer only syntactical query completion; thanks to semantic contextual knowledge, our job and skills ontology JANZZon! is able to provide content-related query completions.
- Synonyms, different spelling (e.g. «-iza» versus «-isa»), abbreviations, hypernyms and hyponyms (parent-and-child concepts), and associated terms (e.g. «same, but different» or «part equivalent» concepts) are also taken into account
- High-performing full-text search as fallback in the event that JANZZon! is unable to provide relevant contextual knowledge
- Intelligent weighting of terms and concepts, for example using occupation classes (currently OCs 1 to 7); structural information is used in order to allocate different weightings to the occurrence of search terms in different areas of the dataset and in different contexts, for example in connection with the required occupation
- REST-based web-service interfaces
If required, JANZZon! can be customized flexibly and in accordance with the individual requirements of specific applications as well as in conjunction with JANZZsme! For a broader overview of the key benefits of semantic searches using JANZZon!, ask for our white paper «Keyword vs. ontology based, semantic Matching» (available in English only).