1

Van syntax portfolios naar

Semantische uitwissselbaarheid van gestructureerde

èn ongestructureerde arbeidsmarkt-informatie

luk vervennesynergetics nv

2

Een veelkoppig monster

• Individu als “de nieuwe stakeholder in zijn eigen processen” (Life Management)

• Van syntax naar semantiek• Markten, jobs evolueren steeds sneller• Competenties: duizend bloemen bloeien• Top-down vs bottom-up• …

Server

CORP.

Client

Server

GOV.

Client

Server

Service Provider

Client

Industry / Sector specific Processes & Services

Base Infrastructure forRegion & Sector-wideUser-centric / User-drivenEcosystems

1. Personal Infrastructure2. Semantic Coordination3. BI Infrastructure4. eContent gateway5. Matching Infrastructure6. Trust & Security (+TTP)

Organising the communalityAssure & Promote Labour Market Mobility:1. Governance (PPP)2. Communality Based Infrastructure & Services3. Semantics 4. Trust & Security

Regional Employability Ecosystems

L a b o u r M a r k e t s beyond the client/server paradigm

Personal Infrastructure Cloud

4

1. Bouwen op wat we hebben

(NEN norm)

TaaS

Syntactic & Semantic Conformance for NEN ePortfolio

Application Profiles

Testing as a Service

Luk Vervenne – Dr. Ingo Dahn

Application Profiles

• Standards are too general – I don’t need all that fuzz

• Standards are too restricted – they don’t let me do what I want

• Solution: Application Profiles!

Make My Day!Make My Profile – it‘s easy!

• Making mandatory what I do want• Making optional what I tolerate• Remove what I don’t need• Add what I need

• Next step: • Convince your industry sector • Agree• Share

Making My Profile – Oh so tricky!

• My own extensions • Mixing and matching many profiles• All referenced files must :• exist• validate against another profile or one of a few…

• And…• you have to find out which one to use…• the imsmanifest.xml must exist !!

Prerequisites of Profiles

• A community of stakeholders

• Acquaintance with:• their needs…• their willingness to agree…• their willingness to implement!!!

• STEPS: Success of application profile depends on implementers, data providers and data consumers

YOU BETTER HELP THEM!!

Conformance Testing

• Test so that data conforms to YOUR profile• Problem:• Each profile requires a specific test system• Test system development is expensive

• Solution:• Capture profile in machine readable form• Configure generic test system

Profiling: SchemaProf

Creating a Test Service

SERVICE

Running the Tests

Survey Report

Detailed Reports

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2. En wat met niet-gestructureerde data?

(competentiebeschrijvingenberoepsbeschrijvingen

ervaringenvacatures

…)

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Purpose: Semantic Comparison of Labour Market Data

Compare real-world employability & employment data versus Reference Data of Competences, Occupations, Qualifications, …

Allows the meaningful search, assessment or match of experience, professional activities, skills & competences by using :• Domain Semantics (Annotated Reference framework data) • Linguistic Semantics (Unstructured data using NL processing) • Created individually (personal employability data)• Created at company level (vacancies, job profiles, …)

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Approach

• Knowledge management• Knowledge encoding (knowledge bases)• Knowledge-based data processing

• Annotation• Comparison• Interoperation• Inference

• (Natural Language) Data processing• Interpret data dynamically• Capture data individuality and specifics

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Data, Knowledge & Semantics

1. Data : experience, goal, competence, preference, hobby, training, job, task

2. Knowledge : frameworks, expert rules, models, ontology

3. Semantics : compare Data + Knowledge for semantic operations: • Data management• Knowledge management• Knowledge-based data management• Data-oriented knowledge management

Two kinds of Semantics are involved:

Precompiled: Static, knowledge-based operation

= knowledge semantics

Extracted : Dynamic, in real-time in data management

= data semantics

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EDU

GOV

COMPANY

SERVICEPROVIDER

PROCESCENTRIC

PERSONAL DATA

PERSONAL EMPLOYABILITY

(SEMANTIC META-)DATA(Content + VOCs)

e-PORTFOLIOS

HR-PROCESSES

LEER-DOSSIER

DATA

PDS

ePortfolio

SOA

GAT

EWAY

Import

Export

TRANS-FORMATION

engineCRUD WS

Webinterface CRUD WSCreate, Read,

Update, Delete

WS

EuroPassEuroCV

HR-XML GermanCV, iProfile UK

Linked-In

NL Portfolio

eGovCitizen data

Integration with (legacy) systems

1

2

3

10%

20%

70%

Social Network

Data Mobile context

dataConsumerData

Personal HealthData

Personal Finance

Data

New M a r k e t s

Personal Data Infrastructure

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23

EDU

GOV

COMPANY

SERVICEPROVIDER

PROCESCENTRIC

PERSONAL DATA

PERSONAL EMPLOYABILITY

(SEMANTIC META-)DATA(Content + VOCs)

e-PORTFOLIOS

HR-PROCESSES

LEER-DOSSIER

DATA

UWV

SHL

CINOP/ECVET

SBB

SEMANTICKNOWLEDGE

BASE

(PARTIAL) REFERENCE

FRAMEWORKS

SHARED SEMANTIC

KNOWLEDGE BASE

EVIDENCE

VACANCIES

SKILLS & COMPETENCES

VDAB

U N I F I E D S E M A N T I C M A T C H I N G ESCO

KNOWLEDGE

SEMANTICS

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The European need for semantic interoperability

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FEDERATION

Beyond Asset Descriptions

: Data & SemanticsThe Employability data from : (1) Candidates (employabilityPortfolio™, CVs, EuroPASS, HR, educational, Recruiting or Public or Private Employment Systems (2) Vacancies are indexed & correlated against vocational/occupational qualification and competency catalogues.

This demo is based on the French ROME 2.0 catalogue. However such National catalogues (NOS/SSC) can be enriched with information from other European catalogues.

All vocational categories and qualifications and their respective competency / skills profiles are correlated.

A competency profile is required for the performant execution of professional/vocational ”activities”

Each activity is abstracted using concepts and their relations

VACANCY CANDIDATE

ROME : Adult OCCUPATIONAL

Classification

‘ESCO’ skills & competencies & occupations

ACTIVITYABSTRACTIONS

ONTOLOGY consists ofBEHAVIORAL / SKILLS

SEMANTICS

COLO : Graduate VOCATIONAL Qualifications

©Synergetics 2012 All rights reserved

Activity Semantics

• Competency framework (ROME CATALOG)• Semantic Activity abstractions

1

2

3

click

1 Job Category2 Associated competencies3 Semantic entities & relations

Competency ANALOGY: similarities

Activity Semantics• Job categories• Competencies

belonging to a job category

Compare similarities between 2 competencies

Score on 1 CommonRelation

©Synergetics 2010 all rights resverved

Competency GAP analysis : differencies

Compare differences between 2 competencies

Score on 1 CommonRelation

Activity Semantics• Job categories• Competencies

belonging to a job category

©Synergetics 2010 all rights resverved

Find candidatesSpecify vacancies

©Synergetics 2010 All rights reserved

1. Select ranking threshold2. Select (in)experienced candidates

3. Select the job offer to start the search

Find candidates

Results OverviewSemantic Ranking

according to “presence” of relevant competencies

All animals are equal!

Click to visualise the competency

Visualise the profile

1. Click the ‘bar icon’, multiple selections are allowed

2. Graphic representation of the “activity semantics” of the competency (indicators)

3. Select graph type

©Synergetics 2010 all rights resverved

Find your candidateVisualise the semantic differences of the

7 competencies from the 9 selected candidates

©Synergetics 2010 All rights reserved

…but some are more equal than others 7 competencies

9 selected candidates

Conclusion

• The “Activity Semantics” extraction method makes use of Natural Language Technology :• Abstraction : Extract universal semantics from different competenvy

descriptions• Interpretation : Skills and Competency extraction from

employabilityPortfolios™, texts, CVs, vacancies and … Regional Employability Platform enabled systems!

• For this demo we used (anonymised) real life data from 13.000 candidates and 13.000 vacancies.

• The Activity Semantics method is based on its own ABAS Ontology• Semantic annotation & enrichment of existing ESCO and other European

occupation, vocation, qualification and competency frameworks (ROME, COLO, NOS, UKCES, SSC, QCF, …etc)

• This semantic method allows for considerable refined decision making when searching for the right candidate or vacancy, based upon a set of required or desired competencies.

©Synergetics 2010 All rights reserved

Semantic DNA

The Technology• Semantic metadata

• Interpretation• Input: Textual data• Output: Semantic DNA

• Comparison• Input: Semantic DNAs

• Output: Scores of Similarity, Difference, Equivalence. These are the basis for semantic matching• Robust text understanding technology

• Language parsing and interpretation• Customisable and optimisable• Languages (French, English currently, Dutch coming up)

Use of Competence DNA

• Operation• Extraction of competence semantics• Semantic comparison of competences

• Customization by competence frameworks• Knowledge bases of competence frameworks• Language capability, based on knowledge bases

• Comparison of competences:• free2ref• free2free

Text Editor for Input

Text Input

Semantic DNA

Semantic comparison

Example free2free comparison