Effective Data Curation for Occupation Related Data: How We Are Dealing with NAICS and ISIC.

The North American Industrial Classification System (NAICS) and the International Standard Industrial Classification (ISIC) are two landmarks on our way to master occupation data. The way we are curating the data from these two classifications is exemplary of our approach to put a deep understanding of jobs, skills and industries at the center of our recruitment/employment solutions. Hence, we felt it would be about time to give you a little more insight into how we deal with occupation related data, showing you the inherent complexity of the labor market and the difficulty in preparing occupation related data in a way that it can go on to drive some of today’s most powerful applications. For example public employment services, applicant tracking systems, statistical tools or job boards. Solutions that help alleviate some of today’s hardest problems on the global labor market.


The two industrial classifications are fairly complex structures in themselves. They also show a different approach to the classification of industries. When looking at an industry like street construction for example, NAICS lists a total of 38 different activities under “Highway, street and bridge construction”, among which you will find airport runway construction, highway line painting, pothole filling and guardrail construction. ISIC on the other hand is less detailed; it sums up the same industry in only three bullet points: asphalt paving of roads, road painting and installation of crash barriers and traffic signs. While ISIC contains less detailed information about activities, the underlying structure of the two classifications is the same. The International Standard Industrial Classification has provided guidance to countries in developing national activity classifications, hence most national taxonomies took over its general structure and filled it with country specific activities.

How JANZZ.technology enriches data from standard classifications

Now, what do we do with the thousands of activities and industries in these classifications? We connect each of the terms within the classifications with terms that are already in our ontology JANZZon!: not only related industries, for example other types of civil engineering in the case of “street construction”, but also occupations, skills, specializations and educations that belong within the realm of a particular industry. Also SSIC, the Singapore Standard Industrial Classification, adopts the basic framework and principles of ISIC. Including each of these industrial classifications into our ontology means having a greater level of detail and comprehensiveness at our fingertips than any of the taxonomies could provide on their own.

NAICS and ISIC street construction

Not only industries and activities are curated like that but also skills, educations, job titles etc. All these “data trees” are again interconnected. “Street construction” is related for example with the “road construction engineer”, the “roller driver”, “infrastructure planning” and “road surface marking”.

Sometimes, the denomination of skills, industries and specializations can be the same: for instance, “street construction” could also be a skill or specialization of a construction worker. In these cases, NAICS, ISIC and SSIC intersect with taxonomies of skills and competencies such as ESCO. Our ontology curation team adds these intersections and thereby creates yet more cross-relations and thus makes the ontology even smarter.
On the one hand, the ontology enriches the data from the standard classifications by establishing meaningful connections between occupations, skills, industries and so on. In multiple languages at that. On the other hand, another layer of detail is added to the taxonomies by including also real life data: data from job boards for instance. For taxonomies like NAICS and ISIC have become important tools for comparing statistical data on economic activities but the denominations used are not necessarily the ones used in CVs or jobs postings. By adding a wealth of synonyms, we make the data harvested from the taxonomies fit to be used not only for statistical purposes but also for job matching.
Finally, the effective curation of occupation related data is not only ensured by the breadth and detail of data that is entered into our ontology JANZZon! but also by the industry specific expertise of our team. Establishing meaningful relations between occupations, skills and education requires human experts in order to guarantee the high quality of the knowledge base. In a time when machine learning, smart algorithms and predictive analytics are often held as ubiquitous solutions to everything, we put a deep understanding of occupations, skills and industries back at the center of solving some of today’s hardest labor market issues.

JANZZ Mindsetter – Interview with Dr. Chia-Jung Tsay

JANZZ Mindsetter is about critical mindsets. It provides space for critical voices to offer insights into HR, recruiting, digital transformation, labor market issues such as gender and minority discrimination and many more topical issues.

Dr. Chia-Jung Tsay on biases against strivers

Dr. Chia-Jung Tsay (UCL School of Management) studies the psychological influences on decision making and interpersonal perception, and how expertise and biases affect professional selection and advancement. Dr. Tsay’s work has been published in leading academic journals and featured in media outlets including the BBC, Economist, Harvard Business Review, Nature, and NPR, and in television programs, radio stations, and newspapers across 48 countries. For us, she answered three questions regarding her latest work titled “Naturals and strivers: Preferences and beliefs about sources of achievement“.


How do you position your argument against the idea that hard work and perseverance are key to achieve success?

There’s a lot of great research out there that suggests that differences in achievement likely reflect deliberate effort and persistence, rather than only innate talent. So it’s interesting that we may have little awareness that we actually have a preference for the natural, and we even sacrifice objective qualifications to hire the natural – and yet it may well be the consistent and persevering individual who achieves more in the long run.

Why are we willing to give up better-qualified candidates in order to hire those believed to be naturals?

Delving into how/why the naturalness bias develops is of great interest for future research. One possibility is that we have a preference for potential over even demonstrated achievement. It is also possible that natural talent is attributed more to stable internal characteristics, and thus be perceived as an immutable, more authentic, and more certain path to success.

Your research suggests that our bias for natural talent is unconscious. How do you think this bias could be circumvented then, e.g. in recruiting?

Further work would be necessary to reveal more specific levers through which we may attenuate the effects of the naturalness bias. If the way in which this bias functions overlaps with those of more established biases, we may consider several possible solutions at the point of performance evaluation. These solutions might include ensuring more precise and tangible metrics of assessment, confronting evaluators with highly achieving exemplars of both naturalness and striving, allowing evaluators to have the time and cognitive resources to fully consider the metrics that are important and valued for actual performance, or simply filtering out any candidate application materials that reference sources of achievement.

JANZZ Mindsetter – Interview with Dr. Wen Hua

JANZZ Mindsetter is about critical mindsets. It offers space for critical voices to offer insights into HR, recruiting, digital transformation, labor market issues such as gender and minority discrimination and many more topical issues.

Dr. Wen Hua on gender issues in the Chinese Job market

Dr. Wen Hua has rich experience in research and international development in the field of gender. She obtained the M.Phil. Degree in Social Anthropology at University of Bergen of Norway in 2005 and received the Ph.D. in Anthropology at the Chinese University of Hong Kong in 2010. She was a visiting fellow of Gender Research Programme at Utrecht University of Netherlands in 2007. She has published several papers on gender issues in English and Chinese journals. She is the author of Buying Beauty: Cosmetic surgery in China, published by Hong Kong University Press 2013.


Why do more and more Chinese women undergo cosmetic surgeries despite a plethora of reports on the possible side effects?

Since the reforms in the early 1980s, Chinas has been one of the fastest growing economies in the world. The uncertainty and instability created by the drastic and dramatic economic, socio-cultural and political changes in China have produced immense anxiety that is experienced by women both mentally and corporeally. The economic reform has resulted in fierce competition in the job market and produced much pressure on young women to get an edge to stand out in the fierce job market. Meanwhile, despite dramatic social changes, some traditional gender norms that prize women’s beauty over ability remain remarkably unchanged, which leads people to value women’s physical appearance in the workplace. The rapid social transitions lead people to grasp every opportunity presented, and cosmetic surgery is therefore viewed by some women as an investment to gain “beauty capital” for one’s future life in a rapidly changing and fiercely competitive society.

How does beauty matter in job recruitment in China?

In my book, I argues that some women view “Being good-looking is capital,” that is, an attractive appearance as a set of tangible and portable personal assets that are convertible into financial or social capital that can give them an edge in the fierce job market, where occupational segregation of female labor in the service industry and employment discrimination based on gender, appearance, height and age widely exist. In the past decade, it was not unusual that we saw that besides education background and work experience, job advertisements specified gender, age, marriage status, and even height and appearance such as “above-average looking,” “good-looking,” or “height over 1.65 meters.” Female job applicants, especially young graduates who already have fewer opportunities than their male counterparts, have to face more prejudice and discrimination based on appearance during their job-hunting. Within these fewer opportunities, when age and appearance matter, it is not surprising why some Chinese women regard beauty as a capital in the brutal competition for jobs.

What could be done in order to reduce the pressure on graduates to undergo cosmetic surgery?

Over the years, I saw that job advertisements, which require specific gender, age, marriage status, height and physical appearance, are less and less to be seen openly in job adverts. But I think that discrimination in employment still exists in China’s workplace. The discrimination has changed from overt to recessive, while the situation might be even worse because hidden prejudice and discrimination against women is harder to avoid and punish. According to the Third Survey of Chinese Women’s Social Status in 2010, more than 72 percent of women had a perception of “not being hired or promoted because of gender” discrimination. I think that to safeguard women’s rights and interests, the authorities should put more effort and effectively punish gender discrimination in employment, which can also reduce the pressure of graduates to undergo cosmetic surgery.