1.
ENCORE
Commons 4.0 License BY-SA-NC
July 2022 - June 2025
ENRICHING CIRCULAR USE OF OER FOR EDUCATION
Mapping the skills of the future
Artificial Intelligence and Human Expertise to Foresee Green, Digital and
Entrepreneurial Skill

2.
Filippo Chiarello, Ph.D
I am an assistant professor of Strategic and
Competitive Intelligence at the University of Pisa.
My research interests include Natural Language
Processing, Innovation Management and Human
Resources Management. I’m proudly part of
Business Engineering 4 Data Science (B4DS)
Research Team and I am the project coordinator of
the ENCORE project.

3.
INTRODUCTION
The digital era is changing the role of educators, that are
moving towards becoming education and experiences
designers. Furthermore, pedagogical contents are now
distributed and accessible, ready to be used for the creation of
courses to answer students’ needs for everchanging skills.
The ENCORE (ENriching Circular use of OeR for Education)
project aims to support this change, by contributing to the
teaching and recognition of the skills most affected by macro-
trends (digitalization, climate change and post-COVID economic
recovery challenges).
ENCORE will implement a data-driven phase and a expert-driven
phase, to reuse Open Educational Resources (OER), and support
educators in teaching and learning design.

4.
PARTNERS
• UNIPI
• CHA
• UNISA
• UNIPD
• VAL
• BMU
• ADE
• OREC
• KFRU
• HOU
• ULS
• FBK
• EADTU

5.
CHALLENGES
ENCORE aims at facing the following challenges:
(1) help the students and workers to acquire the skills to face
economical, ecological and technological challenges;
(2) mitigate the skills mismatch between the demand of companies
and the supply of educational institutions;
(3) support educators to be aligned with the ever-evolving
landscape of relevant skills;
(4) support educators to face the evolution of the educational
context with proper pedagogical approaches;
(5) facilitate students in the certification of the skills they acquire
through non-standard pedagogical approaches

6.
OUR
WORKFLOW
With the ENCORE project, the partners want to
develop courses to teach skills that will help students
face the macro-trends of digitalization, climate change
and post-COVID economic recovery challenges.
The project is thus focused on three macro skills:
• Green Skills (G), knowledge, skills and attitudes
linked to the transition to a circular and greener
economy;
• Digital Skills (D), knowledge, skills and attitudes
linked to the confident, critical and responsible use
of, and engagement with, digital technologies for
learning, at work, and for participation in society
and;
• Entrepreneurial & Intrapreneurial Skills (E),
knowledge, skills and attitudes linked to the
capacity to act upon opportunities and ideas, and
transform them into value (financial, cultural or
social) for others (source EntreComp).

7.
OUR WORKFLOW

8.
Vito Giordano, Ph.D
Vito Giordano is a research fellow at the School of
Engineering, University of Pisa. His research
focuses on the use of Natural Language
Processing techniques for studying technological
and Organizational-related phenomena.

9.
OUR WORKFLOW

10.
OUR WORKFLOW

11.
Objective
Identify the knowledge, skills and attitudes that are
relevant in the context of Green, Digital and
Entrepreneurial skills

12.
Approach
Questionnaire on
GDE Skills
Skills Panorama
Text Mining on
Scientific
literature

13.
TABLE OF CONTENT
Categorising ESCO skills on GDE skills
Paper retrieval; Skill extraction with NER; Results Cleaning; Unwrapped GDE
skills
Enhancement and revision of the identified skills by the
companies
Questionnaire; Future Skill Prospect of Skills Panorama
Skill2Esco
Skill2Esco methodology; Skills to suggest to ESCO
1
2
3

14.
TABLE OF CONTENT
Categorising ESCO skills on GDE skills
Paper retrieval; Skill extraction with NER; Results Cleaning; Unwrapped GDE
skills
Enhancement and revision of the identified skills by the
companies
Questionnaire; Future Skill Prospect of Skills Panorama
Skill2Esco
Skill2Esco methodology; Skills to suggest to ESCO
1

15.
Questionnaire on
GDE Skills
Skills Panorama
Text Mining on
Scientific
literature
1. Categorising ESCO skills on GDE skills
M e t h o d o l o g y

16.
Questionnaire on
GDE Skills
Skills Panorama
Text Mining on
Scientific
literature
1. Categorising ESCO skills on GDE skills
M e t h o d o l o g y

17.
Text Mining on
Scientific
literature
1. Categorising ESCO skills on GDE skills
M e t h o d o l o g y
Data mining is an interdisciplinary subfield of
computer science and statistics with an
overall goal to extract from a data set and
transform the information into a
comprehensible structure for further use.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The
elements of statistical learning: data mining,
inference, and prediction. Springer Science &
Business Media.
Text mining is a subfield of Data Mining with
the main goal to extract information from
unstructured textual data.
TEXT MINING
Gupta, V., & Lehal, G. S. (2009). A survey of text
mining techniques and applications. Journal of
emerging technologies in web intelligence, 1 (1),
60-76.
Natural Language Processing (NLP) is a branch of
artificial intelligence (AI) that focuses on how
computers can understand and manipulate human
language (natural language in jargon). It involves
the analysis of textual data and the use of
algorithms and statistical models to interpret and
understand natural language.
Surabhi, M. C. (2013, July). Natural language processing future. In
2013 International conference on optical imaging sensor and
security (ICOSS) (pp. 1-3). IEEE.

18.
Results
Cleaning
Remove noise entities,
validate by expert opinions
and normalize the GDE skills
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
Results
Analyze the Unwrapped GDE
skills
~60,000
Scientific Papers
1. Categorising ESCO skills on GDE skills
M e t h o d o l o g y
Skill
Extraction
Identify the GDE skills related
with the domain under the
analysis using Named Entity
Recognition (NER) techniques

19.
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers

20.
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
Build a Query

21.
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
Description of the GDE fields in the proposal

22.
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
Description of the GDE fields in the proposal
European policies and directives about the
GDE domains
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l

23.
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l

24.
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l
SKILL
DOMAIN

25.
Paper Retrieval
Collect a set of scientific
papers on the GDE domains
from Scopus
~60,000
Scientific Papers
1. Categorising ESCO skills on GDE skills
P a p e r r e t r i e v a l

26.
1. Categorising ESCO skills on GDE skills
S k i l l E x t r a c t i o n w i t h N E R
Skill
Extraction
Identify the GDE skills related
with the domain under the
analysis using Named Entity
Recognition (NER) techniques

27.
1. Categorising ESCO skills on GDE skills
S k i l l E x t r a c t i o n w i t h N E R
Rule based
Gazetteer based
Gazetteer based method
aims to map mentions of
entities within texts to
terminological resources,
such as:
Rule based method uses
lexicons, regular expressions
and lexical information to
express knowledge based
systems able to extract a
certain type of entity.
Nominal Entity Recognition (NER)
Skill
Extraction
Identify the GDE skills related
with the domain under the
analysis using Named Entity
Recognition (NER) techniques

28.
1. Categorising ESCO skills on GDE skills
S k i l l E x t r a c t i o n w i t h N E R
ESCO contains 13890 skills, 3008 occupations, and many qualifications. We selected the concepts in the category
skills. For each skill, the following information are selected: preferred labels, the typical name for a given concept
alternative labels, other format for the same concept Skills are usually define with a verb and one or more noun,
knowledge are usually identified with noun. https://esco.ec.europa.eu/en
O*NET includes a set of variables that describe work and worker characteristics, including skill requirements.
The lexical pattern of those data is aligned with the structure of ESCO concepts. The linkages among the data
included in O*NET have been used to enlarge the lexicon replicating the pair structure of preferred labels-
alternative labels. https://www.onetcenter.org/
EntreComp depicts the entrepreneurial capabilities in a transversal perspective, by defining 3 competence areas,
a list of 15 competences, learning outcomes and proficiency levels. For each competence, the related hint and
threads were selected. The lexical pattern of those data is aligned with the structure of ESCO concepts. The
linkages among the data included in EntreComp have been used to enlarge the lexicon replicating the pair
structure of preferred labels-alternative labels.

29.
1. Categorising ESCO skills on GDE skills
S k i l l E x t r a c t i o n w i t h N E R

30.
1. Categorising ESCO skills on GDE skills
R e s u l t s C l e a n i n g
Results
Cleaning
Remove noise entities,
validate by expert opinions
and normalize the GDE skills
All the skills are manual revised from the
research group for the validation.
We cleaned the results by removing
automatically noise entities
Group together similar skills based on
Semantic Similarity algorithm (BERT)

31.
1. Categorising ESCO skills on GDE skills
R e s u l t s C l e a n i n g
Group together similar skills based on
Semantic Similarity algorithm (BERT)
Extracted Competences Skill Label
Work together
Cooperate
Work in teams
Work in groups
Working in teams
Team-working
Work in teams
Programming
Computer programming
Programming languages
Computer programming

32.
1. Categorising ESCO skills on GDE skills
U n w r a p p e d G D E s k i l l s
377 464 553
No. unique Skills
804 unique Skills

33.
1. Categorising ESCO skills on GDE skills
U n w r a p p e d G D E s k i l l s : G r e e n S k i l l s
Skill
Relevance
(# Papers)
% of
Papers
Skill
Relevance
(# Papers)
%of
Papers
think creatively 2,300 21.60% waste management 508 4.77%
environmental engineering 1,813 17.03% bioeconomy 486 4.56%
circular economy 1,806 16.96% fossil fuels 476 4.47%
innovation processes 716 6.72% lead others 463 4.35%
packaging engineering 699 6.57% analyse 360 3.38%
electricity 637 5.98% mechanical systems 335 3.15%
electricity principles 637 5.98% characteristics of waste 331 3.11%
energy 587 5.51% business model 305 2.86%
chemistry 559 5.25% monitor assessment 300 2.82%
communication 513 4.82% communication principles 286 2.69%

34.
1. Categorising ESCO skills on GDE skills
U n w r a p p e d G D E s k i l l s : D i g i t a l S k i l l s
Skill
Relevance
(# Papers)
% of
Papers
Skill
Relevance
(# Papers)
%of
Papers
think creatively 5,445 27.34% computer programming 844 4.24%
communication 4,243 21.30% e-learning 748 3.76%
communication principles 3,047 15.30% pedagogy 740 3.72%
packaging engineering 2,192 11.01% mathematics 714 3.58%
computer technology 2,037 10.23% originality 712 3.57%
printed circuit boards testing methods 1,369 6.87% statistics 711 3.57%
hardware testing methods 1,362 6.84% computer science 680 3.41%
in-circuit test 1,362 6.84% lead others 581 2.92%
innovation processes 1,238 6.22% metrology 549 2.76%

35.
1. Categorising ESCO skills on GDE skills
U n w r a p p e d G D E s k i l l s : E n t r e p r e n e u r s h i p S k i l l s
Skill
Relevance
(# Papers)
% of
Papers
Skill
Relevance
(# Papers)
%of
Papers
entrepreneurship 13,466 43.33% lead others 1,263 4.06%
innovation processes 6,633 21.34% environmental engineering 1,167 3.75%
think creatively 5,850 18.82% statistics 1,039 3.34%
originality 3,037 9.77% economics 1,026 3.30%
communication 2,414 7.77% mechanical systems 1,020 3.28%
packaging engineering 1,771 5.70% computer technology 887 2.85%
marketing principles 1,713 5.51% business model 821 2.64%
analyze 1,548 4.98% establish collaborative relations 745 2.40%
leadership principles 1,520 4.89% history 718 2.31%
communication principles 1,313 4.22% collect samples 677 2.18%

36.
TABLE OF CONTENT
Categorising ESCO skills on GDE skills
Paper retrieval; Skill extraction with NER; Results Cleaning; Unwrapped GDE
skills
Enhancement and revision of the identified skills by the
companies
Questionnaire; Future Skill Prospect of Skills Panorama
Skill2Esco
Skill2Esco methodology; Skills to suggest to ESCO
2

37.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
M e t h o d o l o g y
The enhancement and revision of the skills identified in Task 2.1 is performed by:
Questionnaire on
GDE Skills
Skills Panorama

38.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
7 languages

39.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
7 languages

40.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
1. What skills are you missing the most in your
organization?
2. What are the skills you are investing the most
for upskilling/reskilling?
3. What are the skills you are searching for the
most when hiring?

41.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
Dissemination: different approaches have been implemented to
reach a bigger audience for the ENCORE questionnaire

42.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
340 answers

43.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
340 answers 1,492 Skills

44.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
340 answers 1,492 Skills
305
skills are removed
1,184
skills matched to a skill collected in task 2.1
3
skills are news: Industry 4.0; Software development;
Docker

45.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e
340 answers 1,492 Skills
305
skills are removed, because not respecting the format
requested by the questionnaire (e.g., Internet instead
of paper), skills explained too much in general (e.g.,
Agility, Moderation) or not meaningful (e.g., I don’t
know, Nothing)
1,184
skills matched to a skill collected in task 2.1
3
skills are news: Industry 4.0; Software development;
Docker.c
300 unique Skills

46.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e : G r e e n S k i l l s
Skill Relavance Index % of Questionnaires
waste management 190 44.41%
circular economy 159 35.88%
energy efficiency 152 30%
bioeconomy 103 24.71%
ecological principles 51 12.35%
ecology 25 5.59%
manage waste 25 6.47%
promote sustainability 24 5%
electricity consumption 23 5%
renewable energy technologies 18 4.71%
energy 13 3.24%
climate change impact 9 1.76%
solar energy 9 1.76%
assume responsibility 8 4.12%
environmental threats 8 1.76%

47.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e : D i g i t a l S k i l l s
Skill Relavance Index % of Questionnaires
analyse big data 198 39.71%
principles of artificial intelligence 191 36.76%
cyber security 162 34.12%
computer programming 121 26.76%
data analytics 65 15.88%
machine learning 47 10.59%
data mining 42 9.12%
Python (computer programming) 42 8.53%
business intelligence 32 10%
operate digital hardware 30 7.35%
project management 22 10%
manage data 15 3.82%
cloud technologies 14 2.35%
analyze 13 3.53%
analyse scientific data 12 2.65%

48.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
Q u e s t i o n n a i r e : E n t r e p r e n e u r s h i p S k i l l s
Skill Relavance Index % of Questionnaires
leadership principles 228 45,88%
work in teams 166 32,35%
think creatively 150 30,88%
negotiate compromises 71 16,18%
marketing principles 69 17,35%
communication 42 9,41%
meet commitments 35 7,35%
moderate in negotiations 23 5%
project management 19 10%
involvement 16 3,53%
think critically 14 2,65%
motivate employees 13 3,24%
assertiveness 11 2,94%
personnel management 11 2,65%
entrepreneurship 10 1,47%

49.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F u t u r e S k i l l P r o s p e c t o f S k i l l s P a n o r a m a
Assessing the relevance of the skills collected in T2.1, updated after the
first step of task T2.2, using the European platform Skills Panorama

50.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F u t u r e S k i l l P r o s p e c t o f S k i l l s P a n o r a m a
The future job prospects indicator compares future number of
job openings in a particular occupation to total employment in
that occupation.
If the number of future job opportunities is high compared to
total employment (for example for scores above 60 it means
that there will be more job openings than number of current
jobs in the occupations), we say that there will be high job
prospects.
On the contrary, if the score is below 40, the job prospects will
be relatively low.

51.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F u t u r e S k i l l P r o s p e c t o f S k i l l s P a n o r a m a
We transfer the index from Jobs to Skills
Job 1 Skill C
Skill A
Skill B

52.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F u t u r e S k i l l P r o s p e c t o f S k i l l s P a n o r a m a
Label
Future Skill
Prospect
capacity building 87
organic chemistry 78
ecotourism 77
communication 75,25
data analytics 74
sustainable development goals 74
social innovation 74
alter management 74
management department processes 74
pharmaceutical industry 73
establish collaborative relations 72,95
sociology 72,5
social sciences 70,7
social justice 70,06
develop food waste reduction strategies 69,75
toxicology 69,67
provide information 69,16
promote sustainability 68,5
climate change impact 68,5
analyse score 68,48
Label
Future Skill
Prospect
capacity building 87
personal development 82
manage feedback 78,24
radiology 78
psychotherapy principles 78
biomedicine 78
writing techniques 77,6
use questioning techniques 77
pathology 75,27
communication 75,25
data analytics 74
sustainable development goals 74
social innovation 74
alter management 74
conflict management 74
management department processes 74
crowdfunding 74
social entrepreneurship 74
manage several projects 74
outplacement 74
Label
Future Skill
Prospect
capacity building 87
personal development 82
manage feedback 78,24
radiology 78
psychotherapy principles 78
biomedicine 78
use questioning techniques 77
ecotourism 77
use computer telephony integration 77
pathology 75,27
communication 75,25
data analytics 74
sustainable development goals 74
social innovation 74
alter management 74
conflict management 74
management department processes 74
crowdfunding 74
social entrepreneurship 74
manage several projects 74

53.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F i n a l O u t p u t : G r e e n
Label Paper Index Questionnaire Index Future Skills Prospect
circular economy 96,87 83,68 45,75
waste management 80,51 100,00 52,74
energy efficiency 71,53 80,00 59,67
bioeconomy 79,94 54,21 63,00
think creatively 100,00 0,00 50,00
environmental engineering 96,92 1,57 49,33
ecological principles 65,39 26,84 61,00
energy 82,37 6,84 55,6
innovation processes 84,93 0,00 60,27
packaging engineering 84,62 0,00 63,00
electricity principles 83,42 0,52 34,67
electricity 83,42 0,00 40,77
chemistry 81,74 0,52 47,46
fossil fuels 79,67 1,57 63,00

54.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F i n a l O u t p u t : D i g i t a l
Label Paper Index Questionnaire Index Future Skills Prospect
principles of artificial
intelligence
70,21 96,46 52,5
computer programming 78,34 61,11 44,11
analyse big data 32,22 100 68,33
cyber security 45,93 81,81 45,50
think creatively 100,00 0,50 50,00
communication 97,10 2,52 75,25
communication principles 93,25 0,00 68,38
computer technology 88,57 1,01 51,45
packaging engineering 89,42 0,00 63,00
data analytics 54,20 32,82 74,00
analyze 80,32 6,56 50,00
machine learning 61,64 23,73 42,00
printed circuit boards testing
methods
83,95 0,00 3,00
hardware testing methods 83,89 0,00 53,00

55.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
F i n a l O u t p u t : E n t r e p r e n e u r s h i p
Label Paper Index Questionnaire Index Future Skills Prospect
leadership principles 77,06 100,00 51,30
think creatively 91,23 65,78 50,00
work in teams 56,03 72,80 50,00
marketing principles 78,31 30,26 62,43
entrepreneurship 100,00 4,38 50,00
communication 81,92 18,42 75,25
innovation processes 92,55 0,87 60,27
negotiate compromises 57,19 31,14 50,00
originality 84,33 0,00 50,00
packaging engineering 78,66 0,00 63,00
analyze 77,25 1,31 50,00
communication principles 75,52 0,43 68,38
lead others 75,11 0,00 50,00
environmental engineering 74,28 0,00 49,33

56.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Questionnaire on GDE Skills Text Mining on GDE Skills
Industry
Perspective
Scientific
Community
Perspective

57.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ1 - Are digital skills needs aligned between industrial and scientific
communities?
RQ2 - Which are the gaps between industrial and scientific
communities perspectives on the skills needs?

58.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Case
Survey
Analysis
Text Mining of
research
literature
Total number
of skills
Example
1 yes yes 193
think creatively, business intelligence, cyber
security, Python (computer programming),
natural language processing
2 yes no 14
industry 4.0, renewable energy
technologies, work efficiently, software
development, docker
3 no yes 271
augmented reality, geographic information
systems, MATLAB, originality, ICT system
programming
Total 478
This is the first evidence of the alignment
between the perceptions of the industrial and
scientific communities.

59.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Label Questionnaire Index Paper Index
principles of artificial
intelligence
96,46 70,21
computer programming 61,11 78,34
analyse big data 100 32,22
cyber security 81,81 45,93
think creatively 0,50 100,00
communication 2,52 97,10
communication principles 0,00 93,25
computer technology 1,01 88,57
packaging engineering 0,00 89,42
data analytics 32,82 54,20
analyze 6,56 80,32
machine learning 23,73 61,64
printed circuit boards testing
methods
0,00 83,95
hardware testing methods 0,00 83,89
𝑫𝒆𝒍𝒕𝒂 𝒑𝒆𝒓𝒔𝒑𝒆𝒄𝒕𝒊𝒗𝒆 = 𝑸𝒖𝒆𝒔𝒕𝒊𝒐𝒏𝒆𝒓 𝒊𝒏𝒅𝒆𝒙 − 𝑷𝒂𝒑𝒆𝒓 𝑰𝒏𝒅𝒆𝒙

60.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e

61.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Scientific Community Perspective
Aligned
Industry Perspective

62.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ1 - Are digital skills needs aligned between industrial
and scientific communities?
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
machine learning 23.74 24.24 -0.50
data mining 21.21 17.21 4.00
project management 11.11 16.73 -5.62
automation technology 3.54 9.45 -5.91
embedded systems 2.02 10.06 -8.04
data protection 1.52 8.36 -6.84
human-computer interaction 1.52 8.12 -6.60
natural language processing 3.03 6.55 -3.52
electronic communication 2.02 7.52 -5.50
graphic design 2.02 6.06 -4.04
customer service 1.52 4.12 -2.60
design hardware 2.53 3.03 -0.50
database management systems 2.02 2.42 -0.40
cybernetics 2.53 1.82 0.71
use IT tools 2.53 1.70 0.83
Aligned

63.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ1 - Are digital skills needs aligned between industrial
and scientific communities?
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
machine learning 23.74 24.24 -0.50
data mining 21.21 17.21 4.00
project management 11.11 16.73 -5.62
automation technology 3.54 9.45 -5.91
embedded systems 2.02 10.06 -8.04
data protection 1.52 8.36 -6.84
human-computer interaction 1.52 8.12 -6.60
natural language processing 3.03 6.55 -3.52
electronic communication 2.02 7.52 -5.50
graphic design 2.02 6.06 -4.04
customer service 1.52 4.12 -2.60
design hardware 2.53 3.03 -0.50
database management systems 2.02 2.42 -0.40
cybernetics 2.53 1.82 0.71
use IT tools 2.53 1.70 0.83
Aligned

64.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ1 - Are digital skills needs aligned between industrial
and scientific communities?
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
machine learning 23.74 24.24 -0.50
data mining 21.21 17.21 4.00
project management 11.11 16.73 -5.62
automation technology 3.54 9.45 -5.91
embedded systems 2.02 10.06 -8.04
data protection 1.52 8.36 -6.84
human-computer interaction 1.52 8.12 -6.60
natural language processing 3.03 6.55 -3.52
electronic communication 2.02 7.52 -5.50
graphic design 2.02 6.06 -4.04
customer service 1.52 4.12 -2.60
design hardware 2.53 3.03 -0.50
database management systems 2.02 2.42 -0.40
cybernetics 2.53 1.82 0.71
use IT tools 2.53 1.70 0.83
Aligned

65.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ1 - Are digital skills needs aligned between industrial
and scientific communities?
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
machine learning 23.74 24.24 -0.50
data mining 21.21 17.21 4.00
project management 11.11 16.73 -5.62
automation technology 3.54 9.45 -5.91
embedded systems 2.02 10.06 -8.04
data protection 1.52 8.36 -6.84
human-computer interaction 1.52 8.12 -6.60
natural language processing 3.03 6.55 -3.52
electronic communication 2.02 7.52 -5.50
graphic design 2.02 6.06 -4.04
customer service 1.52 4.12 -2.60
design hardware 2.53 3.03 -0.50
database management systems 2.02 2.42 -0.40
cybernetics 2.53 1.82 0.71
use IT tools 2.53 1.70 0.83
Aligned

66.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Label
Relevance for
Questionnaire
Relevance
for
Papers
Delta
perspective
analyse big data 100.00 1.82 98.18
cyber security 81.82 6.18 75.64
principles of artificial
intelligence
96.46 50.79 45.67
data analytics 32.83 12.73 20,10
Python (computer
programming)
21.21 6.30 14.91
operate digital
hardware
15.15 0.61 14.54
business intelligence 16.16 4.24 11.92
Industry Perspective

67.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Label
Relevance for
Questionnaire
Relevance
for
Papers
Delta
perspective
analyse big data 100.00 1.82 98.18
cyber security 81.82 6.18 75.64
principles of
artificial intelligence
96.46 50.79 45.67
data analytics 32.83 12.73 20,10
Python (computer
programming)
21.21 6.30 14.91
operate digital
hardware
15.15 0.61 14.54
business intelligence 16.16 4.24 11.92
Industry Perspective

68.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Label
Relevance for
Questionnaire
Relevance
for
Papers
Delta
perspective
analyse big data 100.00 1.82 98.18
cyber security 81.82 6.18 75.64
principles of artificial
intelligence
96.46 50.79 45.67
data analytics 32.83 12.73 20,10
Python (computer
programming)
21.21 6.30 14.91
operate digital
hardware
15.15 0.61 14.54
business intelligence 16.16 4.24 11.92
Industry Perspective

69.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
computer technology 1.01 96.73 -95.72
think critically 0.00 64.73 -64.73
statistics 1.01 51.64 -50.63
use learning strategies 0.00 48.73 -48.73
transmission technology 0.00 48.12 -48.12
tutor students 0.00 46.18 -46.18
database 0.51 44.85 -44.34
leadership principles 0.51 41.33 -40.82
Internet of Things 3.54 43.64 -40.10
augmented reality 0.00 39.88 -39.88
visual presentation techniques 0.00 39.03 -39.03
computer programming 61.11 100.00 -38.89
robotics 0.51 36.12 -35.61
knowledge management 1.52 35.76 -34.24
virtual reality 0.51 31.64 -31.13
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Scientific Community Perspective

70.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
computer technology 1.01 96.73 -95.72
think critically 0.00 64.73 -64.73
statistics 1.01 51.64 -50.63
use learning strategies 0.00 48.73 -48.73
transmission technology 0.00 48.12 -48.12
tutor students 0.00 46.18 -46.18
database 0.51 44.85 -44.34
leadership principles 0.51 41.33 -40.82
Internet of Things 3.54 43.64 -40.10
augmented reality 0.00 39.88 -39.88
visual presentation techniques 0.00 39.03 -39.03
computer programming 61.11 100.00 -38.89
robotics 0.51 36.12 -35.61
knowledge management 1.52 35.76 -34.24
virtual reality 0.51 31.64 -31.13
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Scientific Community Perspective

71.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
computer technology 1.01 96.73 -95.72
think critically 0.00 64.73 -64.73
statistics 1.01 51.64 -50.63
use learning strategies 0.00 48.73 -48.73
transmission technology 0.00 48.12 -48.12
tutor students 0.00 46.18 -46.18
database 0.51 44.85 -44.34
leadership principles 0.51 41.33 -40.82
Internet of Things 3.54 43.64 -40.10
augmented reality 0.00 39.88 -39.88
visual presentation techniques 0.00 39.03 -39.03
computer programming 61.11 100.00 -38.89
robotics 0.51 36.12 -35.61
knowledge management 1.52 35.76 -34.24
virtual reality 0.51 31.64 -31.13
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Scientific Community Perspective

72.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
Label
Relevance for
Questionnaire
Relevance
for Papers
Delta
perspective
computer technology 1.01 96.73 -95.72
think critically 0.00 64.73 -64.73
statistics 1.01 51.64 -50.63
use learning strategies 0.00 48.73 -48.73
transmission technology 0.00 48.12 -48.12
tutor students 0.00 46.18 -46.18
database 0.51 44.85 -44.34
leadership principles 0.51 41.33 -40.82
Internet of Things 3.54 43.64 -40.10
augmented reality 0.00 39.88 -39.88
visual presentation techniques 0.00 39.03 -39.03
computer programming 61.11 100.00 -38.89
robotics 0.51 36.12 -35.61
knowledge management 1.52 35.76 -34.24
virtual reality 0.51 31.64 -31.13
RQ2 - Which are the gaps between industrial and research
perspectives on the skills needs?
Scientific Community Perspective

73.
2. E n h a n c e m e n t a n d r e v i s i o n o f t h e i d e n t i f i e d s k i l l s b y t h e c o m p a n i e s
C o m p a r i s o n I n d u s t r y v s S c i e n t i f i c C o m m u n i t y p e r s p e c t i v e
A total of 478 different digital skills were identified, with some overlap between the perspectives of the industry and research, but
also some discrepancies. Digital skills such as “machine learning”, “data mining” and “natural language processing” have a similar
relevance for both industrial and scientific community perspectives.
However, there were some skills that were seen as important by one group but not the other, which suggests that there are
differences in the views of companies and researchers on the importance of certain digital skills.
On one hand, companies tend to focus more on (1) skills related to cutting edge technologies, such as “cyber security”, “principles
of artificial intelligence” and “analyse big data”; and on (2) skills with a high level of detail with respect to researchers, as for
instance the use of “Python”.
On the other hand, the analysis of scientific publications allows us to consider more abstract skills, such as “computer
programming” or “knowledge management”, and also transversal skills (such as “think critically” and “leadership principles”) to face
the digital transformation.

74.
TABLE OF CONTENT
Categorising ESCO skills on GDE skills
Paper retrieval; Skill extraction with NER; Results Cleaning; Unwrapped GDE
skills
Enhancement and revision of the identified skills by the
companies
Questionnaire; Future Skill Prospect of Skills Panorama
Skill2Esco
Skill2Esco methodology; Skills to suggest to ESCO
3

75.
3. Skill2Esco
S k i l l 2 E s c o m e t h o d o l o g y
Find GDE skills that can be incorporated within the ESCO database

76.
3. Skill2Esco
S k i l l 2 E s c o I m p a c t
Skill2Esco allows:
1. policy makers to continuously update the ESCO database
2. scholars to explore novel skills in GDE domains
3. managers to plan future hiring, upskilling, and reskilling process

77.
3. Skill2Esco
S k i l l 2 E s c o m e t h o d o l o g y
New
Alternative
Label
New Skills
Automatic similarity
matching using BERT
Manual revision of
similarity matching
Manual definitions of
Skills comparison OUTPUT

78.
3. Skill2Esco
S k i l l 2 E s c o m e t h o d o l o g y
Automatic similarity
matching using BERT
Non-matched concept Top 4 most similar ESCO skills
Semantic
Similarity
zoom
mount optical components on frames 0,54
take pictures 0,54
cameras 0,53
Havok Vision 0,52
youtube
social media management 0,49
Internet of Things 0,48
select video shots 0,47
apply social media marketing 0,46
working with others
instruct others 0,76
communicate professionally with colleagues in other fields 0,75
cooperate with colleagues 0,73
motivate others 0,73
work together
work in teams 0,80
develop working procedures 0,75
carry out work-related measurements 0,75
work efficiently 0,74

79.
3. Skill2Esco
S k i l l 2 E s c o m e t h o d o l o g y
Non-matched concept Top 4 most similar ESCO skills
Semantic
Similarity
zoom
mount optical components on frames 0,54
take pictures 0,54
cameras 0,53
Havok Vision 0,52
youtube
social media management 0,49
Internet of Things 0,48
select video shots 0,47
apply social media marketing 0,46
working with others
instruct others 0,76
communicate professionally with colleagues in other fields 0,75
cooperate with colleagues 0,73
motivate others 0,73
work together
work in teams 0,80
develop working procedures 0,75
carry out work-related measurements 0,75
work efficiently 0,74
Manual revision of
similarity matching

80.
3. Skill2Esco
S k i l l 2 E s c o m e t h o d o l o g y
Manual definitions of
Skills comparison

81.
3. Skill2Esco
S k i l l s t o s u g g e s t t o E S C O
Extracted concept ESCO Skills/Knowledge Preferred Label
NEW Alternative Label proposed for
existing ESCO Skills/ Knowledge
active learning use learning strategies “perform active learning”
bargaining power negotiate price “leverage on bargaining power”
blackboard collaborate collaborate through digital technologies “use blackboard to collaborate”
complex problem solving solve problems “perform complex problem solving”
cooperation establish collaborative relations “cooperate”
data analysis software perform data analysis “use data analysis software”
digital databases database “digital databases”
economy economics “economy”
electronic mail electronic communication “electronic mail”
entrepreneur entrepreneurship “entrepreneur behavior”
entrepreneurs entrepreneurship “entrepreneurs behavior”
google classroom learning technologies “google classroom”
google scholar conduct scholarly research “use google scholar”
harvest harvest crop “harvest”
innovation innovation processes “innovation”
instructing training subject expertise “instructing expertise”
investment develop investment portfolio “make investment”
linux Kali Linux “linux”
loom textile technologies “loom”
manage risk risk management “techniques for managing risk”
memorization memorise information “use memorization techniques”
New
Alternative
Label
76

82.
3. Skill2Esco
S k i l l s t o s u g g e s t t o E S C O
New Skills
15
Extracted concept
NEW Skill / Knowledge
Label Description Skills Type
atlas.ti atlas.ti
A computer-assisted qualitative data analysis software that facilitates analysis of
qualitative data for qualitative research, quantitative research, and mixed methods
research. Software used for scientific research and analysis that generate deep insights
from qualitative data analysis.
knowledge
bootstrap bootstrap
Bootstrap is a free and open-source CSS framework directed at responsive, mobile-first
front-end web development.
knowledge
data acquisition systems data acquisition systems
The types of systems that allow one to measure or control the physical characteristics of
something in the real world.
knowledge
dropbox dropbox File hosting service. knowledge
educational software educational software
Educational software is a term used for any computer software which is made for an
educational purpose.
knowledge
geogebra geogebra
Mathematics learning and teaching software that provides tools for the study of geometry,
algebra and analysis.
knowledge
github github Provider of Internet hosting for software development and version control using Git. knowledge
inductive reasoning inductive reasoning
Inductive reasoning is a method of reasoning in which a body of observations is
considered to derive a general principle.
knowledge
modeling software modeling software A computer program to build simulations or other models. knowledge
rss rss
RSS is a web feed that allows users and applications to access updates to websites in a
standardized, computer-readable format.
knowledge
simulation software simulation software
A program that allows the user to observe an operation through simulation without actually
performing that operation.
knowledge
verilog verilog A hardware description language (HDL) used to model electronic systems. knowledge
youtube youtube Online tool to communicate and share video contents. knowledge
learn to learn pursuit lifelong learning
The ability to pursue and persist in learning, to organize one's own learning, including
through. effective management of time and information, both individually and in groups.
This competence includes awareness.
skill
social orientation show social orientation
Social orientation designates how a person is aware of, relates, and adapts to other
people.
skill

83.
Conclusion
Data
It is important to collect data to support the decision-making process with objective
evidence
Method
We should rely on structured methods to analyse the data and leading the decision-making
process
Results
Technical expert knowledge should need to interpret the insights resulted from the analysis

84.
THANK
YOU
For more information visit our website
www.project-encore.eu
This Photo by Unknown Author is licensed under CC BY
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect
those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor
EACEA can be held responsible for them.
vito.Giordano@phd.unipi.it
filippo.chiarello@unipi.it