=Paper=
{{Paper
|id=Vol-3905/master1
|storemode=property
|title=An ontology-based approach to support the development of adaptive interface
systems
|pdfUrl=https://ceur-ws.org/Vol-3905/master1.pdf
|volume=Vol-3905
|authors=Alexandre Freitas,Monalessa Barcellos
|dblpUrl=https://dblp.org/rec/conf/ontobras/FreitasB24
}}
==An ontology-based approach to support the development of adaptive interface
systems==
https://ceur-ws.org/Vol-3905/master1.pdf
An ontology-based approach to support the development
of adaptive interface systems
Alexandre Adler Cunha de Freitas1 , Monalessa P. Barcellos1
1
Ontology & Conceptual Modeling Research Group (NEMO), Computer Science Department, Federal University of Espírito Santo
(UFES), Brazil
Abstract
Advances in technology have introduced new challenges to ensure optimal usability for diverse users. Adaptive
User Interface (AUI) systems offer a potential solution by dynamically adjusting the interface to the user. However,
developing these systems is complex, requiring capturing user characteristics and preferences. This paper
provides an overview of a doctoral proposal that proposes OADAPT, an ontology-based approach to support
AUI system development. The approach comprises a knowledge framework about AUI systems (represented
through networked ontologies) and a process that guides the steps to use the ontologies to develop AUI systems.
OADAPT emerged from developing a social network called SNOPI, which automatically adapts its interface based
on users’ needs and characteristics, such as low vision and colorblindness.
Keywords
Adaptive User Interface, AUI System, Ontology, Ontology Network
1. Introduction
In the ever-evolving technological landscape, the development of interactive systems that prioritize
human needs and preferences has become important. Designing these systems with a human-centered
approach is crucial to their success [1]. As our digital society continues to advance, there is a growing
demand for intuitive and user-centric interactive systems that cater to individual needs. This necessitates
the creation of well-designed user interfaces (UI) that facilitate effective communication between users
and the system.
Users differ in a wide range of variables, including demographic characteristics, educational back-
ground, personality traits, cognitive abilities, and personal preferences. Understanding these user
differences is paramount for designing inclusive and user-centric systems, which requires employing
user-centered approaches incorporating Adaptive User Interface (AUI) development. By embracing
these approaches, developers can create systems that are accessible to different users.
Developing AUI systems is a complex and knowledge-intensive undertaking [2]. UI adaptations need
diverse user information. Therefore, it becomes necessary to structure and organize knowledge about
the user and the system to facilitate appropriate adaptations in the UI. In this work, we argue that
using ontologies holds promise in addressing this challenge. Ontologies serve to capture and organize
knowledge, enabling the structured representation of information about interactive systems and users’
characteristics. By employing ontologies, we can gain a deeper understanding of how such systems
function and utilize this knowledge as a foundation for structuring them. Furthermore, ontologies can
help identify the necessary adaptations and support the implementation of mechanisms to enact these
adaptations in real time.
In the literature, some works have explored the use of ontologies to develop AUI systems [3] (e.g., [4],
[5], [6], [7], [8] and [9]). However, the ontologies often are very specific, i.e., they can only be used to
solve a particular problem in the context of the system to which they were created, and are used mainly
at the operational level. This may work for isolated solutions, but systems have been required to be
Proceedings of the 17th Seminar on Ontology Research in Brazil (ONTOBRAS 2024) and 8th Doctoral and Masters Consortium on
Ontologies (WTDO 2024), Vitória, Brazil, October 07-10, 2024.
$ alexandre.a.freitas@ufes.br (A. A. C. d. Freitas); monalessa@inf.ufes.br (M. P. Barcellos)
0000-0002-6622-0722 (A. A. C. d. Freitas); 0000-0002-6225-9478 (M. P. Barcellos)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
more comprehensive and constantly evolve according to the user needs. Isolated solutions are usually
hard to be extended to incorporate new requirements or reused in the development of new solutions.
Therefore, we advocate that ontologies should also be used at the conceptual level to structure
knowledge about the system and user characteristics. Thus, it is possible to provide a general knowledge
representation that can be used as a basis to define UI adaptations and develop AUI systems. We also
argue that, ideally, we should use ontologies from an ontology network (ON), i.e., a set of interconnected
ontologies that provide a comprehensive conceptualization of the domain of interest and have a common
global conceptual structure that helps share their concepts [10]. By doing so, it is possible to constantly
evolve the set of possible adaptations by considering different concepts from the networked ontologies.
In view of the above, in this work, we build networked ontologies and explore them and others from
an ontology network to help develop AUI systems at both conceptual and operational levels. As a result,
we will propose an ontology-based approach to provide knowledge and guidance on how to develop
AUI systems with the support of networked ontologies.
This paper presents an overview of the work and is organized as follows: Section 2 discusses Related
Work; Section 3 describes the Research Method; Section 4 presents Current State of the Research; Section
5 summarizes Next Steps.
2. Related Work
Some works propose the use of ontologies in the development of AUI systems [3]. For example, Bonacin
et al. [4] use a recoloring ontology to develop a functional web prototype that changes the colors of UI
elements automatically for colorblind users. Braham et al. [5], in turn, use ontologies and UI design
patterns to develop a mobile application that supports run-time adaptation of the UI for people with
disabilities. In the work by Stefanidi et al. [7], ontologies are used to support the development of an
AUI system aimed at improving users’ situational awareness. Khan and Khusro [9] used an ontology to
model and store concepts and relationships of an AUI system for visually impaired users on touchscreen
devices. Sala et al. [8] used ontologies for annotations in an automated adaptation system to enhance
the accessibility of public e-services. Fedasyuk and Lutsyk [6] propose an adaptive system to help
people with cognitive disabilities and used an ontology to adapt the functionalities and graphical UI.
All these works focused on the use of operational ontologies and did not follow a systematic process,
which makes it difficult for other people to repeat the process to develop other systems.
Like in the works aforementioned, in our work, we propose to use ontologies to help develop AUI
systems (specifically their software constituent). However, our proposal has some important differences.
First, we argue for the use of well-founded reference ontologies, which are application-independent and,
thus, can be used to develop different AUIs and different systems. Moreover, they can be translated into
operational ontologies to be used at run-time. Second, we propose the use of ontologies of an ON. Thus,
different ON extracts (i.e., ontologies containing different concepts) can be used to develop different
systems. In addition, the set of user characteristics and other concepts represented in the ON can increase
over time (because the ON continuously evolves) enabling one to address new adaptions. Finally, our
proposal (i) provides structured knowledge, by means of networked ontologies, that addresses relevant
aspects of adaptive systems and AUI to support AUI systems development, and (ii) describes the steps
to be followed to use ontologies from an ON to develop AUI systems and. As a benefit, third parties
will be able to use the proposed process and the knowledge to develop AUI systems.
3. Research Method
The methodological approach adopted in this work follows the Design Science Research (DSR) paradigm.
DSR focuses on extending human and organizational capabilities through the creation of novel and
innovative artifacts [11, 12]. It comprises an iterative process that encompasses three cycles: the
Relevance Cycle, Design Cycle, and Rigor Cycle [11]. Several experimental studies will be carried out
during the work. As suggested by Barcellos et al. [13], we organize the studies as learning iterations,
i.e., studies performed in iterations that allow the researcher to learn something about the research, by
providing useful knowledge to understand the problem, develop the artifact, and evaluate or improve it.
Figure 1 provides an overview of the Design Science cycles and learning iterations in this research.
Figure 1: Overview of the Design Science cycles in this research (based on [11, 12]).
4. Current State of the Research
This work aims to explore the use of networked ontologies to support AUI systems development.
The main artifact resulting from this work is an ontology-based approach to support AUI systems
development. The approach must (R1) provide structured knowledge about AUI systems, and (R2) guide
its users on the steps to develop AUI systems by considering the structured knowledge. Hence, we
have developed OADAPT (Ontology-based Approach to Develop AdaPtive inTerfaces), which comprises
(i) networked ontologies added to the Human-Computer Interaction Ontology Network (HCI-ON) [14]
(to meet R1), and (ii) a systematic process (to meet R2).
The first version of the OADAPT resulted from an exploratory study in which we added ontologies to
HCI-ON and used an HCI-ON extract to develop SNOPI (Social Network with Ontology-based Adaptive
Interface) (for further information the reader must refer to [15] and [16]). SNOPI is a social network
centered around academic subjects that automatically adapts its UI according to the needs of low-vision
and colorblind users. After that, OADAPT was used in a case study to evolve SNOPI, producing SNOPI
2.0, which allows for gesture and voice adaptations [17].
Figure 2 shows an overview of the eight-step process of OADAPT. The process comprises eight steps,
five of which are classic software development steps, while three focus on the use of ontologies to
develop AUI systems.
Figure 3 shows a fragment of the knowledge component of OADAPT, i.e., networked ontologies from
HCI-ON. HCI-ON structures knowledge in three layers: (i) foundation layer, containing UFO Guizzardi
et al. [18], the Unified Foundational Ontology [18], which provides the basic concepts and common
Figure 2: OADAPT process.
ground for all the networked ontologies; core layer, containing ontologies addressing HCI core aspects,
such as user, interactive system and interaction; and domain layer, which encompasses ontologies
addressing HCI subdomains, grounded in UFO or core ontologies. The ontologies developed in this
work were integrated into the domain layer.
We have added to HCI-ON four new ontologies (under development): Adaptive Interface Ontology
(AIO), User Profile Ontology (UPO), User Characterization Ontology (UCO), UI Types and Elements Ontology
(UIT&EO). Figure 3 shows a fragment of HCI-ON including concepts from the ontologies developed in
this work. Double red dotted lines separate the core and domain layers. Black dotted lines separate
concepts from different ontologies. Different colors are used to designate different ontologies. For
simplification, we omitted the foundation layer in the figure.
The ON fragment shown in Figure 3 was used to develop SNOPI. Figure 4 provides an overview of
the SNOPI architecture. The UI layer contains the user interface components. The application layer
handles system functionalities. The data layer manages data structure and storage. The semantic layer
uses ontoSNOPI, the operational ontology that implements the ON extract used to develop the tool,
along with rules to adapt the interface based on user characteristics and profile. SNOPI uses networked
ontologies at the conceptual level to structure the system and at the operational level for reasoning
about the adaptations according to the user profile and characteristics.
5. Next Steps
This paper presented an overview of a doctoral research that aims to explore the use of networked
ontologies to support the development of AUI systems. An ontology-based approach called OADAPT
has been proposed.
The results obtained so far are promising, but it is still necessary to refine the process to improve
guidance, extend the networked ontologies to provide more comprehensive knowledge, and make the
use of the ontologies’ concepts to create the UI adaptation rules more explicit. Moreover, it is still
necessary to evaluate OADAPT without the researcher’s intervention (the first author was involved in
the studies performed so far).
Therefore, as the next steps of this research, we plan to use Feature Models [19] to represent the
necessary UI adaptations according to the user characteristics and profile; refine OADAPT process
descriptions by providing examples based on SNOPI experience; extend the networked ontologies
considering some needs already identified, and perform a case study to evaluate OADAPT without the
researcher intervention.
Acknowledgments
This research is supported by the Coordination for the Improvement of Higher Education Personnel -
CAPES Brazil (Finance Code 001) and the Espírito Santo Research and Innovation Support Foundation -
FAPES (Processes 2023-5L1FC, 2022-NGKM5, 2021-GL60J, and T.O. 1022/2022).
Figure 3: HCI-ON fragment involving AUI system concepts.
Figure 4: SNOPI architecture overview.
References
[1] F. Gurcan, N. E. Cagiltay, K. Cagiltay, Mapping human–computer interaction research themes
and trends from its existence to today: A topic modeling-based review of past 60 years, Inter-
national Journal of Human–Computer Interaction 37 (2021) 267–280. doi:10.1080/10447318.
2020.1819668.
[2] E. Yigitbas, K. Josifovska, I. Jovanovikj, F. Kalinci, A. Anjorin, G. Engels, Component-based
development of adaptive user interfaces, in: Proceedings of the ACM SIGCHI Symposium on
Engineering Interactive Computing Systems, EICS ’19, Association for Computing Machinery,
New York, NY, USA, 2019. doi:10.1145/3319499.3328229.
[3] S. D. Costa, M. P. Barcellos, R. d. A. Falbo, Ontologies in human–computer interaction: A systematic
literature review, Applied Ontology 16 (2021) 421–452. doi:10.3233/AO-210255.
[4] R. Bonacin, J. C. d. Reis, R. J. de Araujo, An ontology-based framework for improving color
vision deficiency accessibility, Univers. Access Inf. Soc. 21 (2022) 691–716. doi:10.1007/
s10209-021-00791-6.
[5] A. Braham, F. Buendía, M. Khemaja, F. Gargouri, User interface design patterns and ontology
models for adaptive mobile applications, Personal and Ubiquitous Computing (2021) 1–17. doi:10.
1007/s00779-020-01481-5.
[6] D. Fedasyuk, I. Lutsyk, Tools for adaptation of a mobile application to the needs of users with
cognitive impairments, in: 2021 IEEE 16th International Conference on Computer Sciences and
Information Technologies (CSIT), volume 1, 2021, pp. 321–324. doi:10.1109/CSIT52700.2021.
9648702.
[7] Z. Stefanidi, G. Margetis, S. Ntoa, G. Papagiannakis, Real-time adaptation of context-aware
intelligent user interfaces, for enhanced situational awareness, IEEE Access 10 (2022) 23367–23393.
doi:10.1109/ACCESS.2022.3152743.
[8] A. Sala, M. Arrue, J. E. Pérez, S. M. Espín-Tello, Automated adaptations for improving the accessibil-
ity of public e-services based on annotations, in: C. Ardito, R. Lanzilotti, A. Malizia, H. Petrie, A. Pic-
cinno, G. Desolda, K. Inkpen (Eds.), Human-Computer Interaction – INTERACT 2021, Springer
International Publishing, Cham, 2021, pp. 373–382. doi:10.1007/978-3-030-85610-6_22.
[9] A. Khan, S. Khusro, Blind-friendly user interfaces–a pilot study on improving the accessibility of
touchscreen interfaces, Multimedia Tools and Applications 78 (2019) 17495–17519. doi:10.1007/
s11042-018-7094-y.
[10] A. Sattar, M. N. Ahmad, E. S. M. Surin, A. K. Mahmood, An improved methodology for collaborative
construction of reusable, localized, and shareable ontology, IEEE Access 9 (2021) 17463–17484.
doi:10.1109/ACCESS.2021.3054412.
[11] A. R. Hevner, A three cycle view of design science research, Scandinavian journal of information
systems 19 (2007) 4.
[12] A. R. Hevner, S. T. March, J. Park, S. Ram, Design science in information systems research, MIS
quarterly (2004) 75–105. doi:10.2307/25148625.
[13] M. Barcellos, G. Santos, T. Conte, B. Trinkenreich, P. Matsubara, Organizing empirical studies
as learning iterations in design science research projects, in: Proceedings of the XXI Brazilian
Symposium on Software Quality, SBQS ’22, Association for Computing Machinery, New York, NY,
USA, 2023. doi:10.1145/3571473.3571474.
[14] S. D. Costa, M. P. Barcellos, R. d. A. Falbo, M. V. H. B. Castro, Towards an Ontology Network on
Human-Computer Interaction, in: G. Dobbie, U. Frank, G. Kappel, S. W. Liddle, H. C. Mayr (Eds.),
Proceedings of the 39th International Conference on Conceptual Modeling, Springer International
Publishing, Cham, 2020, pp. 331–341. doi:10.1007/978-3-030-62522-1_24.
[15] A. A. C. de Freitas, M. B. Scalser, S. D. Costa, M. P. Barcellos, Towards an ontology-based approach
to develop software systems with adaptive user interface, in: Proceedings of the 21st Brazilian
Symposium on Human Factors in Computing Systems, IHC ’22, Association for Computing
Machinery, New York, NY, USA, 2022. doi:10.1145/3554364.3559139.
[16] A. A. C. d. Freitas, S. D. Costa, M. B. Scalser, M. P. Barcellos, Using networked ontologies to support
the development of software systems with adaptive user interface, Journal on Interactive Systems
14 (2023) 257–273. doi:10.5753/jis.2023.3256.
[17] V. de O. Risso, Aplicação de uma abordagem baseada em ontologia na evolução de um sistema com
interface adaptativa, 2023. Monography - Federal University of Espírito Santo (UFES), VITÓRIA,
ES - Brazil.
[18] G. Guizzardi, G. Wagner, J. P. A. Almeida, R. S. Guizzardi, Towards ontological foundations for
conceptual modeling: The unified foundational ontology (ufo) story, Applied ontology 10 (2015)
259–271. doi:10.3233/AO-150157.
[19] P. Arcaini, A. Gargantini, P. Vavassori, Generating tests for detecting faults in feature models, in:
2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST),
2015, pp. 1–10. doi:10.1109/ICST.2015.7102591.