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Immerse: A Personalized System Addressing the Challenges of Migrant Integration

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IMMERSE: A PERSONALIZED SYSTEM ADDRESSING THE CHALLENGES
OF MIGRANT INTEGRATION
Dimos Ntioudis, Eleni Kamateri, Georgios Meditskos, Anastasios Karakostas,
Florian Huber, Romeo Bratska, Stefanos Vrochidis, Babak Akhgar§, Ioannis Kompatsiaris
Information Technologies Institute - Centre for Research and Technology Hellas,
{ntdimos, ekamater, gmeditsk, stefanos, akarakos, ikom}@iti.gr;
SYNYO GmbH, florian.huber@synyo.com;
ADITESS - Advanced Integrated Technology Solutions & Services Ltd, rb@aditess.com;
§Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research -
Sheffield Hallam University, b.akhgar@shu.ac.uk
ABSTRACT
This paper presents IMMERSE, a system that offers a num-
ber of ICT-enabled services to address the challenges of mi-
grant integration, focusing on: (i) covering migrants’ needs
for validated information, (ii) addressing migrants’ specific
socio-cultural, economic and legal aspects, and (iii) improv-
ing migrants’ access to labour markets. IMMERSE is mainly
designed to cover information needs of migrants that can be
either general information and guidance or personalised infor-
mation based on their specific needs, skills and interests. IM-
MERSE is validated with a case study example which demon-
strates the functionality of the job matching service. As future
work, IMMERSE will be deployed across three pilot loca-
tions, namely, Spain, Italy and Cyprus, realizing different in-
stantiations of the final system, adapted to the specific needs
of each pilot location.
Index TermsMigrants, Refugees, ICT tools, Integra-
tion, Semantics, Job Matching, Recommendation
1. INTRODUCTION
Factors such as autonomy, perception, culture and history
shape the dynamics and experiences of migrants, and high-
light the complexity of the migration process [1]. This com-
plexity also indicates the diversity in the integration process,
which is also influenced by the economic, social, political
and cultural factors that exist in a given destination coun-
try. However, a recent study established that migrants seem
to share the same concerns [2]. More precisely, the issues
of (1) integration and discrimination, (2) employment and in-
capacity support, and (3) education are the three top-ranked
themes among migrants of varying experiences and different
age groups, genders, migration routes and immigration status.
MIICT is a EU-funded research project that is conceived
with the goal of designing, developing and deploying ICT-
enabled tools that address the challenge of migrant integra-
tion. To realise its objective, MIICT is grounded on the prin-
ciples of a human-center design approach that put the impli-
cated actors at the center of the design, development and de-
ployment process. Based on this, multi-disciplinary migrant-
related stakeholders, such as migrants, refugees, asylum
seekers, public sector services, NGOs (Non-Governmental-
Organisations) and other interest groups, are actively involved
in the design, development and deployment process of the
IMMERSE system to ensure the identification of needs and
requirements from the perspectives of migrants, public sector
services and NGOs.
In service of this goal, MIICT proposes the development
of the IMMERSE system, which stands for ”Integration of
Migrants MatchER SErvice”. IMMERSE provides a series
of sustained and improved inclusion services that capture the
specific socio-cultural, economic and legal contexts of mi-
grants and foster them to overcome key challenges they en-
counter when they arrive in the destination country. At the
same time, the IMMERSE acts as a firewall for migrants re-
ducing the potential for discrimination and bias, and ensuring
responsible and liable content provision by third parties.
The remaining of the paper is organised as follows: Sec-
tion 2 presents state-of-the-art ICT tools for migrant integra-
tion. Section 3 describes the proposed IMMERSE solution
and its core services. Section 4 provides an overview of the ar-
chitecture of the IMMERSE system and its core components.
Section 5 presents a case study that validates the application
potential of the proposed solution and finally, in Section 6,
conclusions and future work are discussed.
2. OVERVIEW OF ICT TOOLS FOR MIGRANTS
ICT tools play a vital role in the integration and social inclu-
sion of migrants and refugees. They can be used to support
migrants in several activities and to overcome the difficulties
978-1-7281-1485-9/20/$31.00 c
2020 IEEE
they might encounter when they come in the destination coun-
try, ranging from learning the language of the new country,
acquiring job-related skills, accessing education and job op-
portunities, assimilating with the wider community, and so
on. In the literature, there are several studies presenting how
ICT tools can respond to the challenges faced by migrants
[3, 4]. Below, we review existing ICT-enabled tools initiated
by European and national projects, NGO organisations and
private companies.
MApp is a mobile application developed by the European
project MASELTOV1. It offers a suite of ICT tools promoting
the social inclusion of migrants, by motivating and supporting
their informal learning during everyday activities in the city
[5]. A similar mobile application is Lantern, presented in [6],
which helps refugees to navigate and learn about their new
environment using Near Field Communication (NFC) tech-
nology. NFC tags are placed to strategic locations by case-
workers and established refugees can leave context-specific
assistance (e.g. pre-recorded messages, text messages etc.).
In the literature, there are also tools that exploit gamifi-
cation and robotic technology to promote migrants’ social in-
clusion. Moin application fosters informal learning and com-
munication with the use of gamification [7]. The app moti-
vates local and migrant teenagers to meet for social events and
provides assistance with contextual language learning using
a variety of gamification elements. Moreover, GeeBot is an
autonomous robotic teaching platform, intended to facilitate
social inclusion and integration of refugee families in hosting
societies, while mitigating cultural and languages barriers [8].
Another mobile application, developed in the frame of the
Italian project Prevenzione 4.0, helps the migrant centres to
provide medical and physiological support to migrants by em-
powering them to access a set of biomedical devices, such as
thermometer, pressure meter, a libra, a glucometer, etc., using
their mobile phones [9]. Using a QR code, the app identifies
the user and automatically registers the measured parameters
in the user’s profile, while it facilitates communication with
operators, such as cultural mediators, physicians, psycholo-
gist, etc.
The need for communication between migrants and be-
tween migrants and their mentors/tutors is also quite evident
in the migrant-related ICT tools. Rivrtran [10] is a representa-
tive example of such a communication application that facil-
itates engagement between refugees who have been accepted
for resettlement and their mentors (i.e., American families).
The tool helps them to articulate their needs better, jointly
formulate goals with their mentors, and initiate communica-
tion.
The LO-MATCH platform [11], developed in the Euro-
pean project MATCH, uses a shared ontology to match job
seekers’ abilities with companies’ needs despite lexical and
semantic differences in their descriptions. The job matching
challenge, which is the domain of interest for the investigated
1www.maseltov.eu, 2012-15
case study in Section 5, has been extensively addressed by
many researchers. For example, Pernici et al. present the
eCompetence Management tool [12] that enables the seman-
tical linking of knowledge objects, skills, and competences
for describing an individual’s profile and matching it with
standard ICT profiles. Based on the previous fact that com-
petences can be expressed in terms of knowledge, skill and
competence concepts, Gatteschi et al. [13] suggest a ranking
algorithm to compare qualifications across European employ-
ers. In another work, authors making use of description logics
present a matchmaking model that deduce both qualified and
under-qualified matches and similarity-based ranking [14].
The outcome of the aforementioned analysis is that there
exist several initiatives and tools attempting to address the in-
tegration and social inclusion challenges of migrants, espe-
cially language and culture learning, employment, communi-
cation, and information provision. However, we haven’t no-
ticed so far a holistic approach that provides a set of tools
addressing the entire process of migrant social inclusion, in-
tegration and accessing the labour market.
3. FUNCTIONALITY OF THE IMMERSE SYSTEM
In order to specify the IMMERSE system’s functionality,
evidence-based case studies, co-creation workshops, partic-
ipant requirement elicitation activities, and previous surveys
have been taken into account. More precisely, end-users from
3 pilot countries, Spain, Italy and Cyprus, were initially re-
quested to outline specific use cases and scenarios, which il-
lustrate the inclusion processes where the IMMERSE services
could bring added value.
Fig. 1. The nine user-centric pillars of the IMMERSE system.
Synthesizing the outcomes of the data collected from the
end-users’ answers, nine challenging sectors were identified
as the core inclusion services, upon which the IMMERSE sys-
tem has to be built. For this reason, these sectors are called
pillars. These pillars were further refined through co-design
and co-creation workshops at the three locations, in-depth in-
terviews and online questionnaires. The outcome of the re-
quirement elicitation process was a list of user requirements
expressing the needs of migrant-related stakeholders related
to each of the identified pillars. These pillars, which also
consist the main entry points of the IMMERSE system, are
depicted in Figure 1.
Table 1. An indicative list of the IMMERSE system user
requirements.
Pillar Requirement description
Lan-
guage
The system enables migrants to search, apply
and provide feedback/rating on various lan-
guage courses and language course providers
to publish the offering courses (M, SP).
Educa-
tion
The system enables migrants to search, ap-
ply and provide feedback/rating on training
courses, designed to meet job market require-
ments, and training course providers to publish
the offering courses (M, SP).
Housing The system enables migrants to search, apply
and provide feedback/rating on accommoda-
tion offers (rent/free to share) and accommo-
dation providers to publish their advertise-
ments (M, SP).
Health The system enables specialised volunteer to
register to the system announcing the health-
related voluntary services that they could offer,
such as psychotherapy, healthcare assistance,
etc. Moreover, it enables governmental entities
to search for specialised volunteers (SP, GE).
Trans-
portation
The system enables migrants to access general
information about public transportation, infor-
mation on timetables, buying tickets or issuing
a card (M, SP).
Status The system enables migrants to create compre-
hensive profiles (All).
Social
Integra-
tion
The system enables cultural mediators to reg-
ister to the system announcing voluntary ser-
vices that they could offer, such as transla-
tion/linguistic mediation, cultural mediation,
etc. Moreover, it enables governmental entities
to search for cultural mediators (SP, GE).
Social
Security
The system enables governmental entities to
announce donors (e.g., school supplies) and
invite migrants matching donor’s criteria to
participate. Moreover, it enables migrants to
be informed about specific donors and declare
their interest. (M, GE).
Employ-
ment
The system enables migrants to search, apply
and provide feedback/rating on job offers and
job providers to publish their job vacancies
(M, SP).
Based on the analysis of user requirements, we identified
for the IMMERSE system the necessity to accommodate both
migrants’ and public services’ needs. With respect to the
first target group, the IMMERSE system addresses the pro-
vision of information, which can be broken down into two
categories: general information, addressing migrants’ needs
for accurate and responsible information on general matters
they are interested in, including laws, instructions, adminis-
trative documents, etc., and personalized information, ad-
dressing migrant’s needs for the customization of the inclu-
sion services to match their specific needs and preferences.
Moreover, the IMMERSE system addresses public ser-
vices’ needs for the management and monitoring of migrant
integration process. Especially, it provides the appropriate
mechanisms that enable public services to authorize only
trusted service providers to access the system and provide de-
velopment and volunteering offers.
Table 1 presents an indicative list of user requirements, or-
ganised per pillar. The M,GE and SP letter denotes the actors
interacting with the system at each requirement, which can be
the migrant, the governmental entity (the public service or the
NGO representative) and the service provider.
4. ARCHITECTURE OF THE IMMERSE SYSTEM
To realise the envisioned functionality, the IMMERSE system
deploys a multi-layered architecture, which is composed of a
series of technological components and security mechanisms.
More specifically, the architecture consist of four major com-
ponents: (a) a Content Management System (CMS) module,
(b) a Semantic Representation and Integration module, (c) a
Decision Support module, (d) a User Interface (UI) module
and (e) an Authentication module. Figure 3 shows the infor-
mation flow among these components.
4.1. Content Management
The collection and processing of a widely distributed and het-
erogeneous set of data is controlled by the CMS module. This
data originates from other databases or consist current inputs
put in place by different actors for different services. The
module integrates a repository capable of keeping raw data,
which is stored alongside the data generated and processed
by the system’s services. The module also supports advanced
searching capabilities and maintains extensive system logs
and auditing.
4.2. Semantic Representation and Integration
This module is responsible for the semantic representation
and integration of the data, which is previously acquired by
the CMS module, to the ontological structures of the Knowl-
edge Base (KB). More specifically, it builds abstract repre-
sentations of user profiles, available jobs, development op-
portunities and other offers, modeled as RDF triples, which
are stored in a semantic repository. To achieve this, the mod-
ule employs existing ontologies, which are extended to meet
according to application-specific needs.
4.3. Decision Support
This module performs reasoning on top of the semantically
described data so as to further enrich this information by de-
riving implicit knowledge from the hierarchies of concepts
and their interrelationships. It considers migrants’ profiles on
one hand, consisting of personal information such as skills,
education, needs, expectations etc. and on the other hand,
available offers such as jobs, courses, volunteering offers, ac-
commodation, etc.. The module, that is currently in progress,
will implement a hybrid inference engine, consisting of a set
of mechanisms, such as expressive description logics (DLs),
reasoning rules and content similarity algorithms. Its main
purpose is to dynamically enrich the semantic description of
each user profile with the outcome of the inference engine,
and thus provide to the migrant personalized recommenda-
tions. By this way, IMMERSE offers a personalised view of
the system’s services to match migrants’ specific needs and
interests throughout the 9 pillars.
4.4. User Interface
This module is responsible for handling the user interfaces
and managing the navigation and communication logic be-
hind them. The module closely collaborates with the CMS
and the Semantic Representation and Integration modules in
order to request, collect and display the relevant information
for the end user. It is the main entry point for the IMMERSE
system, from where users can navigate and use the imple-
mented services based on their preferred language and coun-
try location. These interfaces realizes the different instantia-
tions of the system for the three pilot locations ensuring that
MIICT system is customised to a particular pilot location but
retains a degree of commonality to support the plug and play
architecture.
4.5. Authentication
Since the IMMERSE system is going to host sensitive infor-
mation about migrants, it becomes evident from the very be-
ginning that it should be grounded on robust mechanisms that
secure the system, its components and the communication of
data between them. To achieve this, an Authentication module
is utilized that is responsible for protecting the multiple oper-
ations performed within the IMMERSE system. The module
manages both machine-to-machine communication and end-
user communication. Moreover, it is responsible for perform-
ing user management tasks for the creation, modification and
deletion of users and for maintaining the user profile. The
module is also responsible for the implementation of authen-
tication policies, the implementation of user access rights and
the issuing of access and ID tokens for the granting and re-
voking of user permissions.
This module will also enforce the data protection by de-
sign methodology adopted by the design of the IMMERSE
system. According to this, the system enables only pertinent
information to the specific service to be visible by third par-
ties at each time, removing elements, such as gender, ethnicity
and age, in circumstances where they have no relevance.
5. CASE STUDY: THE JOB MATCHING SERVICE
In order to demonstrate the functionality of IMMERSE, we
present a case study addressing the job matching service,
which is one of the inclusion services supported by the sys-
tem. In the frame of this service, the system facilitates both
migrants interested in identifying job offers that match their
skills and interests and job providers that are willing to hire
candidates whose profile is suitable for the job vacancy they
offer. The latter consist of trusted employers who have been
previously authorized to access and use the IMMERSE sys-
tem.
rdfs:subClassOf
seemp:CV_List
seemp:has_CV
seemp:is_CV_of
Literal
foaf:birthday
string
seemp:email
string
string
string
string
seemp:First_Name
seemp:Last_Name
seemp:Gender
string
seemp:Address
string
seemp:Mobile
seemp:Job_Seeker
seemp:Elem
miict:cv_summary
seemp:has_elems
miict:CV_Elem
owl:equivalentClass
miict:Work_Exp_Elem
miict:Lang_Elem
miict:Edu_Elem
rdfs:subClassOf
rdfs:subClassOf
rdfs:subClassOf
seemp:Offered_Work_
Experience
owl:equivalentClass
string
string
string
string
seemp:Position
_held
seemp:Main
_Activities
miict:Work_
Exp_Country
seemp:Name_o
f_the_Employer
seemp:Education
owl:equivalentClass
seemp:Education
owl:equivalentClass
string
string
miict:hasLevel
miict:hasValue
string string
string
miict:education_field
miict:education_level
miict:Organization_Name
miict:recommendation
miict:recommendation
miict:Job_Post miict:Course_Post
rdf:type rdf:type
miict:Housing_Post
rdf:type
miict:recommendation
miict:Migrant
Fig. 2. General layout of the representation model of the mi-
grant’s user profile and qualifications.
After a verification process, a job provider is allowed to
enter the system and create a user profile. Then, s/he starts
describing and publishing a set of job vacancies that s/he of-
fers. The job description defines the minimum competences
for someone in order to be accepted. On the other hand, a
migrant enters the system and creates a user profile. Quickly
after that, s/he starts drafting her/his qualifications specifying
the education level, the language experience, the past work
UI
Authorised
Results
Recommended
Results
Create
Migrant
User Profile
Search/Query
Content Management Semantic Representation
& Integration
Other
material
Migrant
User Profiles Service Provider
User Profiles
Service
Provider Offers
Data Repositories
Create Service
Provider
User P rofile
Publish
Offers
(External)
Trustworthy Web Sources
NGOs
Other
Stakeho
lders
Government
Migrants
&
Refugees
Authorisation
Mechanism UI
Authorisation
Mechanism UI
KB
(Triple Store)
Matchmaking Mechanism
.
.
.
.
.
.
.
.
.
Migrant User
Profiles
.
.
.
.
.
.
.
.
.
Matching Criteria
.
.
.
.
.
.
.
.
.
Service Provider
Offers
Decision Support
Reasoning
(rules)
Query
Execution
Fig. 3. An overview of the IMMERSE conceptual architecture.
experience, and so on. Once the migrant completes with the
description of the profile and qualifications, information is
stored in the CMS module.
For the semantic representation of the user profile and its
job-related aspects, we reused the SEEMP [15] and the FOAF
ontology [16]. The same ontologies were also used for the
modelling of job vacancies. Figure 2 depicts the migrant’s
user profile, which is associated with a qualification class con-
sisting of the following sub-classes:
1. Work experience, providing information about past
jobs, such as location, position, employer, activities etc.
2. Education, providing information about the educa-
tional background, such as level, field, organisation,
etc.
3. Languages, providing information about the language
along with the respective level of knowledge.
Returning to our case study, the storage of a new job va-
cancy published by a job provider or a new migrant profile
to the CMS module triggers the Semantic Representation and
Integration module. The latter, semantically represents job
vacancies and migrant’s qualifications using the aforemen-
tioned ontologies and the annotated data are integrated into
the Knowledge Based.
The representation and integration of the information in
the KB is followed by a set of reasoning mechanisms that en-
rich the initial user profile. Among them, a recommendation
algorithm is performed to calculate the similarity between the
migrant’s user profile and available job offers. To understand
the recommendation algorithm, let us first formalize the state-
ment of the job matching problem.
Let Cbe the set of competencies for all migrants and J
be the set of jobs offered through the system. In addition, let
Sbe the set of skills that a migrant may posses or a job may
require. An instance of a migrant’s competence, cC, is
a subset of Sconsisting of a set of skills from S, thus c=
{skill1, skill2, ...skilln} ← S. Similarly, an instance of a
job offer jJ, consisting of a set of required skills from
S, thus j={req1, req2, ...reqm} ← S. The problem is to
compute the percentage similarity score between cand j:
percentage :cj[0,100]
Table 2 presents an indicative example with pairs of skills
coming from the migrant’s competences (in left column), and
available job offers (in the right column). Moreover, the ta-
ble presents (in the central column) the current logic of the
matching process between the fields.
Table 2. Matching criteria between the migrant’s competen-
cies and available job offers.
Competencies Comparison Job Offer
Past experience Equal Job category
Language Equal Language
Language level Greater or Equal Language level
Age Min Age Max Age
Gender Equal to Gender
Education field Equal to Education
Education level Greater or Equal Education level
The top-N ranked matches are then integrated in the rep-
resentation model of the migrant as recommendations (see
Figure 2). The score is re-calculated and the data models
are similarly informed each time a new job offer is pub-
lished. The personalised recommendations become accessi-
ble through the respective section of the UI.
Figure 4 demonstrates the main interface of the job match-
ing service for the migrant. The migrant can search for vari-
ous job offers that meet their needs selecting available criteria
and review recommendations.
Fig. 4. A user interface of the job matching service.
6. CONCLUSION AND FUTURE WORK
The presented system will be integrated and become oper-
ational in real-world environments across 3 pilot sites, and,
thereafter, it will be tested and evaluated for a period of 6
months. The results of the evaluation will further refine the
developed services. With respect to the job matching service,
we plan to advance the recommendation algorithm taking into
account the migrant’s history data and job offer’s free text in
order to further improve the personalized experience offered
by the IMMERSE system.
7. ACKNOWLEDGEMENTS
This work has received funding by the EC under contracts
H2020-822380 MIICT and H2020-870930 WELCOME.
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... In the urban studies, there are some research studies that show the use of digital technologies to create a different use of public space such as public art intervention, public display, city gamification and innovative urban services for convivial food consumption [17]. In the field of inclusion, some research has already been conducted on the use of technology, in forms of application and websites for the integration of immigrants in new countries [18]. But in our knowledge, there are no examples of urban design solutions dedicated to multicultural inclusion. ...
Chapter
Cities worldwide increasingly reflect the cultural diversity of a globalized society as the result of the immigration of people with different backgrounds. The social and cultural barriers evocate an inequality access and, mostly, use of urban spaces in contemporary cities. On the other hand, at the same rhythm of these socio-cultural changes, the cities are undergoing the radical changing by information and communication technologies to improve the various aspects of the cities such as: the quality of life for their citizens, the local economy, environment, and interaction with government, in an increasingly smart perspective. These technological and socio-cultural changes can find a common and fertile ground in urban spaces with the approach of inclusive design. The development of product-service systems, that derives from the progressive growth of digital technologies, applied in the urban environment, have the potential for further studies, research and projects in terms of design for inclusion of cultural diversity. In our knowledge, there is still a lack of design solutions aimed to multicultural inclusion in urban areas through the use of digital technologies. Based on Research through Design methodological approach, the tools of human-centered design and service design thinking were used for the development of a pilot case, M-eating, an EU-funded research project. M-eating is conceived with the goal of designing digital technologies-embedded urban furniture system aimed at facilitating social inclusion, multicultural dialogue and conviviality. The present paper concludes with a holistic and new approach for design for inclusion of cultural diversity in urban space.
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