DIGITAL CAREER NAVIGATOR
A system that will help citizens to find out which competencies they lack to advance their careers towards more desired and demanded jobs and which training opportunities can fill this gap
DIGITAL CAREER NAVIGATOR
A system that will help citizens to find out which competencies they lack to advance their careers towards more desired and demanded jobs and which training opportunities can fill this gap
Only 20 Percent of Employees Have The Skills Needed For Both Their Current Role And Their Future Career
Imbalance of the labor market as a result of the global challenges and the technological revolution.

Some occupations and competencies become highly demanded, while others become less demanded or disappear altogether.

This leads to problems for different stakeholders.
Only 20 Percent of Employees Have The Skills Needed For Both Their Current Role And Their Future Career
Imbalance of the labor market as a result of the global challenges and the technological revolution.

Some occupations and competencies become highly demanded, while others become less demanded or disappear altogether.

This leads to problems for different stakeholders.
Problems for
the key stakeholders
Job seekers
  • Lack of job opportunities
  • Need for new competencies to find a new job or to switch to a more interesting and prospective position
Employers (Industry)
  • Struggle for candidates in demanded areas of competency
  • Need for requalification of loyal employees in disappearing areas
Public (city) employment services
  • Imbalance of the labor market
  • Unemployment
Training providers
  • Lack of promotion
  • Insufficient market understanding
Solution
Training opportunities recomendations

Digital Career Navigator (DCN) can recommend training opportunities (courses, providers) based on personal citizens' skills and competencies gap analysis and job market demands.


Automatic competencies detection

AI Algorithms automatically detect competencies by linking documents and taxonomy entries and thus ensure accuracy and usability.
Solution concept
DIGITAL CITY PLANNER PLATFORM Knowledge: 1. Frameworks and methodologies 2. Classifications and ontologies 3. Architecture & process patterns 4. Data models 5. Values of indicators (Collect Package Share) City knowledge graph Knowledge services: 1. Reusable building blocks 2. Recommendations 3. Inference (reasoning) 4. Benchmarking 5. Smart search (Analyze Design Plan) City-specific models & solutions. We apply Enterprise Architecture, Knowledge Management and System approaches.
DIGITAL CITY PLANNER PLATFORM Knowledge: 1. Frameworks and methodologies 2. Classifications and ontologies 3. Architecture & process patterns 4. Data models 5. Values of indicators (Collect Package Share) City knowledge graph Knowledge services: 1. Reusable building blocks 2. Recommendations 3. Inference (reasoning) 4. Benchmarking 5. Smart search (Analyze Design Plan) City-specific models & solutions. We apply Enterprise Architecture, Knowledge Management and System approaches.
Approach
All provided materials are mapped into common competencies taxonomies, which allows for quick finding of gaps and recommending training opportunities
Approach
All provided materials are mapped into common competencies taxonomies, which allows for quick finding of gaps and recommending training opportunities
Novelty
The technical novelty consists in the combination of 3 innovation elements
Application of cutting-edge natural-language processing algorithms
It links skill taxonomies with job-seekers' profiles, workforce demand info and descriptions of training programs by detecting the required competencies in semi-structured texts
Automated extension of the existing
taxonomies
The suggestion of new taxonomy elements via the analysis of semi-structured work experience, job and/or course descriptions
Usage of knowledge graphs and semantic technologies
It allows to represent and integrate the information
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