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Personalised skills matching
This use case would allow to answer needs such as :
- As a person, I would like to be able to easily interconnect the different competence actors that concern me, to pool data, to be able to visualize all of my competences and their level of validation and then to be able to easily valorize them externally and to be offered relevant training and jobs.
- As a person, I would like to be able to value skills that are not only issued from the school or academic environment: jobs, professional, voluntary and artistic experiences also bring me skills that are useful in my personal and professional evolution.
- As a training organization, I would like to be able to access the precise profile of a person's skills and to be able to trace this skill and its acquisition in order to offer the right training at the right time to the person.
- As an employer, I want to be able to access a person's precise skill profile and be able to track that skill and its acquisition to offer the right job to the person.
- As an organization (employer, training, community), I would like to be able to access aggregate skills data on a territory to establish precise statistics on the needs and prediction of skills in order to orient my recruitment policy, the financing of my training courses or the development of new training.
Check out a demo of such a use case here:
This use case enables stakeholders to provide people and organizations with a portal to easily access all these services in an interconnected way:
- People can use different app providers to define their profile (skills, hobbies, personality, preferences, etc)
- They can share this data from multiple sources with app providers to help them identify the best career move (next title, job, sector) and the skills gap
- They can identify which career move is best for them and share their skills gap with AI providers that match them with training catalogs, content providers to get the right learning recommendations
- Recommendations of career moves and job / training offers can be easily integrated into any interface of the ecosystem, showing the relevant information to people where they are
- People can share their full profile and plan with the relevant stakeholders to put it into place (coaches, managers, training providers, etc)
- All the while they have full control over their data and who can access what
These portals can be adapted and used by people in different situations:
- high school pupils looking for what higher education to get / what sector to get into
- jobseekers looking for an opportunity
- employees looking to upskill or reskill
The portal can be adapted to specific contexts, for instance:
- to an employers skills ontology, organigram, learning content to match employees with career mobility options and upskill them accordingly
- to a university / training provider training catalog to match students / alumni with particular trainings
- to a region’s in demand jobs and skills to orient jobseekers towards recruiting jobs and industries
- Allowing people to gather and share a full skills profile across all organisations of the ecosystem (edtechs, orientation services, higher ed, training orgs, employers, etc)
- Pooling data to offer better services to people (employment, training, education, etc.)
- Matching people with the right training opportunities
- Creating ethical networks of personal data
- Enabling the individual to receive personalized lifelong learning
- Providing interoperability of skills data
People:
- get innovative employment and orientation services
- can share their full profile with relevant stakeholders
Universities / training providers:
- contribute their training catalog and skills ontology
- match their offers with relevant profiles
- provide students with innovative employment and orientation services
- get precise student profiles
Employers:
- contribute their job offers/descriptions, skills ontology, learning content, organigram
- match their offers with relevant profiles
- provide employees with innovative upskilling and career mobility services
- get precise employee profiles
High schools
- provide pupils with innovative employment and orientation services
- get precise pupil profiles
Employment agencies:
- provide jobseekers with innovative employment and orientation services
- get precise jobseeker profiles
Edtechs / AI Providers:
- provide their services and their data to the ecosystem
- get more users and clients
- provider better personalized services thanks to better data access
Infrastructure providers:
- provide services and building blocks to enable data sharing (consent, contract, interoperability, data visualization, decentralized processing, etc)
- get organizations to use their services
Orchestrator:
- provide the ecosystem portal
- coordinate governance, use cases and business model discussions in the ecosystem
- get part of the value generated by the ecosystem through commissions, fees, etc
Prometheus-X already unites an international ecosystem of stakeholders committed to implementing this use case through specific data ecosystem portals that serve their needs.
Training organisations / universities:
- Edunao with possibly over 10 Higher Ed institutions and Corporate Training centers
- Training organizations and universities mobilized through Reskill 4 Employment Sweden (Astra Zeneca)
Employers:
- NOKIA
- Employers mobilize through Reskill 4 Employment Finland
- Employers mobilize through Reskill 4 Employment Sweden
- Employers mobilized through Grande École du Numérique
High Schools:
- Académie de Rennes (112 high schools)
- Edunao with the French Ministry of Education
Employment agencies / orientation actors:
- Actors mobilized through Grande Ecole du Numérique
- Actors mobilized through the Paris Region
- Actors mobilized through Antares
- Actor mobilized through University of Koblenz
Edtechs / AI providers:
Infrastructure providers:
- Visions
- HeadAI
- Inokufu
- Mindmatcher
- Edunao
Orchestrator & portal provider:
In order to make such a use case a reality, different building blocks are needed. Prometheus-X is developing them:
- consent agent: to suggest to people the apps / organisations that best fit their needs
- Skills data interop: to allow the translation of profiles into competences, to ensure interoperability between the different repositories and data models concerning competences, to allow the tracing of the recognition and validation of a competence.
- AI metadata enrichment: algorithms capable of extracting from raw data the activity that allowed the acquisition of competencies on the basis of common reference systems (ROME/ESCO/RECTEC...);
- inter-repository translators: algorithms capable of semantically linking skills repositories to each other and to central repositories, thus making it possible to create a first ontology, making it possible to link sectorial skills (for example, to identify the skills of an individual using different repositories)
- distributed data visualisation: to allow results of matchings (jobs, trainings, ressources) to be shown wherever the user is
Last modified 7mo ago