Structuring visual exploratory analysis of skill demand

Abstract

a b s t r a c tThe analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology-and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users' analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on.

Development of a Job Advertisement Analysis for Assessing Data Science Competencies

“…A weakness of the Debortoli et al (2014) approach is that no information about the connections between competencies was provided, and no tools or products were considered, though soft skills were taken into consideration. Dadzie et al (2018) made a visual exploratory analysis of skill demand. An analytical methodology was used to conduct the exploration and analysis.…”

“…But it is essential to have competency frameworks that are up-to-date, as workforce skill needs are changing, e.g. through upcoming trends (Dadzie et al 2018). Therefore, a more dynamical approach is needed.…”

“…A suitable approach is the job advertisement analysis approach, which makes it possible to continuously record new competency requirements of the workforce. Job advertisement analysis approaches are gaining attention (Almaleh et al 2019;Boselli et al 2018;Khaouja et al 2019;Khobreh et al 2015;Lima, Bakhshi, et al 2018;Wowczko 2015;Zhao et al 2015) especially in the field of analyzing data science competencies (Dadzie et al 2018;Djumalieva, Lima, Sleeman, et al 2018;Debortoli, Müller, and Brocke 2014;Murawski and Bick 2017;E. Sibarani et al 2020;Silveira et al 2020;Shirani 2016).…”

An Open and Data-driven Taxonomy of Skills Extracted from Online Job Adverts

“…For example, propose SARO -an ontology that connects information from job postings to ESCO skills. Authors tested automatically implementing SARO for extracting data from online vacancies for data scientists and performed a trend analysis for selected skills (Dadzie, Sibarani, Novalija, and Scerri, 2017). Boselli et al (2017) also used relationships between ESCO occupations and skills to represent them in a bipartite knowledge graph, which enriches skills identified by experts for a given occupation with data from actual job adverts.…”

Analyzing the relationship between information technology jobs advertised on-line and skills requirements using association rules

“…It also specifies the means to identify their skills and assist them to improve their knowledge by predicting training programs. The study of [32] employed a visual exploratory discovery and analysis approach to determine the demand for jobs, skills specific to a domain or industry sector, and additional non-domain skills required to fill a job role. Meanwhile, the works of [33] explored the significance of key skills to employers, their perceptions of the availability of these skills in the labor force, and employer's knowledge and use of key skills required for the job.…”