JDX: a schema for Job Data Exchange | Sharing and learning: Phil Barker's work

by Phil Barker

[This rather long blog post describes a project that I have been involved with through consultancy with the U.S. Chamber of Commerce Foundation.  Writing this post was funded through that consultancy.]

The U.S. Chamber of Commerce Foundation has recently proposed a modernized schema for job postings based on the work of HR Open and Schema.org, the Job Data Exchange (JDX) JobSchema+. It is hoped JDX JobSchema+ will not just facilitate the exchange of data relevant to jobs, but will do so in a way that helps bridge the various other standards used by relevant systems.  The aim of JDX is to improve the usefulness of job data including signalling around jobs, addressing such questions as: what jobs are available in which geographic areas? What are the requirements for working in these jobs? What are the rewards? What are the career paths? This information needs to be communicated not just between employers and their recruitment partners and to potential job applicants, but also to education and training providers, so that they can create learning opportunities that provide their students with skills that are valuable in their future careers. Job seekers empowered with greater quantity and quality of job data through job postings may secure better-fitting employment faster and for longer duration due to improved matching. Preventing wasted time and hardship may be particularly impactful for populations whose job searches are less well-resourced and those for whom limited flexibility increases their dependence on job details which are often missing, such as schedule, exact location, and security clearance requirement. These are among the properties that JDX provides employers the opportunity to include for easy and quick identification by all.  In short, the data should be available to anyone involved in the talent pipeline. This broad scope poses a problem that JDX also seeks to address: different systems within the talent pipeline data ecosystem use different data standards so how can we ensure that the signalling is intelligible across the whole ecosystem?

The starting point for JDX was two of the most widely used data standards relevant to describing jobs: HR Open Standards Recruiting standard, part of the foremost suite of standards covering all aspects of the HR sector and the schema.org JobPosting schema, which is used to make data on web pages accessible to search engines, notably Google’s Job Search. These, and an analysis of the information required around jobs, job descriptions and job postings, their relationships to other entities such as organizations, competencies, credentials, experience and so on, were modelled in RDF to create a vocabulary of classes, properties, and concept schemes that can be used to create data. The full data model, which can be accessed on GitHub, is quite extensive: the description of jobs that JDX enables goes well beyond what is required for a job posting advertising a vacancy. A subset of the full model comprising those terms useful for job postings was selected for pilot testing, and this is available in a more accessible form on the Chamber Foundation’s website and is documented on the Job Data Exchange website. The results of the data analysis, modelling and piloting were then fed back into the HR Open and schema.org standards that were used as a starting point.

This is where things start to get a little complicated, as it means JDX has contributed to three related efforts.