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Immerse: A Personalized System Addressing the Challenges of Migrant Integration


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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};
ADITESS - Advanced Integrated Technology Solutions & Services Ltd,;
§Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research -
Sheffield Hallam University,
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
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.
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-
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, 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.
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
Pillar Requirement description
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).
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).
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).
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).
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).
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.
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
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.
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-
string string
miict:Job_Post miict:Course_Post
rdf:type rdf:type
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
User Profile
Content Management Semantic Representation
& Integration
User Profiles Service Provider
User Profiles
Provider Offers
Data Repositories
Create Service
User P rofile
Trustworthy Web Sources
Mechanism UI
Mechanism UI
(Triple Store)
Matchmaking Mechanism
Migrant User
Matching Criteria
Service Provider
Decision Support
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,
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.
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.
This work has received funding by the EC under contracts
H2020-822380 MIICT and H2020-870930 WELCOME.
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This paper describes Moin as a user-centered design process to develop a mobile application to foster informal learning through face-to-face communication, supported with contextual language learning features and employing gamification as a motivator. The aim of Moin is to help refugee teenagers to integrate to German culture and specifically to the region of Bremen. The final product requirements are based on the findings from the state-of-the-art, literature analysis and semi-structured interviews. The overall goal of Moin proposes that such a gamified digital application can support forming of local communities that create informal learning of local language and culture and, as a result, support local integration of migrants.
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Social inclusion of recent immigrants is a challenge in many countries for both immigrants and the host communities. To harness the potential of social, situated and opportunistic mobile interactions for the social inclusion of immigrants in a host country, we have developed an Incidental Learning Framework. This supports the design and evaluation of MApp, a suite of smartphone tools and services for recent immigrants. Developed within the European Union's MASELTOV project (, the MApp delivers language learning activities, image-to-text translation, context-aware and interest-based recommendations, local information, game-based cultural learning and social support to immigrants in cities. Preliminary field trials in Vienna, Madrid and London have highlighted issues of mobile literacy, affordability, ethics and privacy challenges, as well as insights into motivations and possible measures of success. Incidental learning implemented on a smartphone app has implications for the relationship between formal and informal learning; new systems of learner support by other immigrants, mentors and volunteers; the design of learning materials that combine immediate assistance with longer term learner development; and potential conflicts between technological affordances, e.g. context awareness and learner tracking, and user preferences among vulnerable groups such as recent immigrants.
The social inclusion of newly resettled refugees is a significant issue confronting both refugees and their host societies. Information and communication technologies (ICTs) are increasingly viewed as a useful resource in programs that provide settlement services or promote participation in society. This paper moves beyond the conventional discussion on the digital divide to explore what people are actually able to do and achieve with ICTs. We draw on an analysis of the use of ICTs for particular purposes by more than 50 resettled refugees to develop an explanation of the process by which ICT use contributes to their social inclusion. We propose that ICT constitutes a resource from which a set of five valuable capabilities is derived: to participate in an information society, to communicate effectively, to understand a new society, to be socially connected, and to express a cultural identity. In realizing these capabilities through ICT use, refugees exercise their agency and enhance their well-being in ways that assist them to function effectively in a new society and regain control over their disrupted lives.
Conference Paper
Refugees undergoing resettlement in a new country post exile and migration face disruptive life changes. They rely on a network of individuals in the host country to help them rebuild their lives and livelihoods. We investigated whether technology could contribute to minimizing the vulnerabilities resettling refugees face. We designed Rivrtran, a messaging platform that provides 'human-in-the-loop' interpretation between individuals who don't share a common language. We report the findings from the deployment of Rivrtran to mediate communication between resettling refugee families in the United States and the American families they are paired with who serve as their mentors. Our findings suggest that scaffolding communication in such a way provides refugees one means of accessing diversified help outside their cultural group. Moreover human-in-the-loop interpretation may help to mitigate the effects of cultural barriers between those communicating. We establish the notion of designing for transient use in the development of systems to scaffold communication for short-term use by resettling refugees.
Conference Paper
When refugees enter their new host countries, they are faced with a variety of challenges and often find themselves relying on others for help. Equipped with only basic technologies, refugees must utilize the little they have to navigate their new environments. Currently, there are no digital systems in place that ease the transition for newly arriving refugees into the USA. In response to this, we have developed Lantern, a cost-efficient mobile service that combines previous generation technology with modern, near field communication capabilities, enabling refugees to learn and navigate within their new surroundings.