IDEAS home Printed from
   My bibliography  Save this paper

A New Approach to Building a Skills Taxonomy


  • Elizabeth Gallagher
  • India Kerle
  • Cath Sleeman
  • George Richardson


This paper presents a new data-driven approach to building a UK skills taxonomy, improving upon the original approach developed in Djumalieva and Sleeman (2018). The new method improves on the original method as it does not rely on a predetermined list of skills, and can instead automatically detect previously unseen skills. This 'minimal judgement' approach is made possible by a classifier that automatically detects sentences within job adverts that are likely to contain skills. These 'skill sentences' are then grouped to define distinct skills, and a hierarchy is formed. The resulting taxonomy contains three levels and 6,685 separate skills. The taxonomy could be used as a base for developing the first UK-specific skills taxonomy, which domain experts would then refine and extend. It could also be used to spot regional skill clusters, and for rapid assessments of skill changes following shocks such as the COVID-19 pandemic.

Suggested Citation

  • Elizabeth Gallagher & India Kerle & Cath Sleeman & George Richardson, 2022. "A New Approach to Building a Skills Taxonomy," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-16, Economic Statistics Centre of Excellence (ESCoE).
  • Handle: RePEc:nsr:escoet:escoe-tr-16

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    big data; cluster analysis; job market; labour demand; machine learning; nlp; online job adverts; sentence embeddings; skills; skills taxonomy;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nsr:escoet:escoe-tr-16. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ESCoE Centre Manager (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.