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A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces, / Sanctorum, Audrey; Signer, Beat.

Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019). IEEE, 2019. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference paper

Harvard

Sanctorum, A & Signer, B 2019, A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces, in Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019). IEEE, pp. 1-6, 13th International Conference on Research Challenges in Information Science, Brussels, Belgium, 29/05/19. https://doi.org/10.1109/RCIS.2019.8877048

APA

Sanctorum, A., & Signer, B. (2019). A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces, In Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019) (pp. 1-6). IEEE. https://doi.org/10.1109/RCIS.2019.8877048

Vancouver

Sanctorum A, Signer B. A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces, In Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019). IEEE. 2019. p. 1-6 https://doi.org/10.1109/RCIS.2019.8877048

Author

Sanctorum, Audrey ; Signer, Beat. / A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces,. Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019). IEEE, 2019. pp. 1-6

BibTeX

@inproceedings{5e450a74f1464a138b2b3827305e1bf2,
title = "A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces,",
abstract = "Over the last decade, research on adaptive and distributed user interfaces (DUIs) has increased. We also witness a growing number of Internet of Things (IoT) devices, allowing digital user interfaces (UIs) to communicate with physical objects and vice versa through so-called hybrid user interfaces. There exist various solutions to manage adaptive, distributed or hybrid UIs. However, none of them covers all three aspects and users have to deal with multiple applications and configurations when developing adaptive distributed hybrid user interfaces. We introduce the eSPACE reference framework and conceptual model unifying the domains of adaptive, distributed and hybrid interfaces. While our reference framework has been inspired by the CAMELEON reference framework, the conceptual model is based on the Resource-Selector-Link (RSL) hypermedia metamodel. We propose an approach for adaptive distributed hybrid user interfaces where users can author their user interfaces based on the different levels of abstraction introduced by our reference framework. We further present a use case illustrating the extensibility, flexibility and reusability offered by our unified approach and discuss potential future work.",
author = "Audrey Sanctorum and Beat Signer",
year = "2019",
doi = "10.1109/RCIS.2019.8877048",
language = "English",
isbn = "978-1-7281-4844-1/19",
pages = "1--6",
booktitle = "Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - A Unifying Reference Framework and Model for Adaptive Distributed Hybrid User Interfaces,

AU - Sanctorum, Audrey

AU - Signer, Beat

PY - 2019

Y1 - 2019

N2 - Over the last decade, research on adaptive and distributed user interfaces (DUIs) has increased. We also witness a growing number of Internet of Things (IoT) devices, allowing digital user interfaces (UIs) to communicate with physical objects and vice versa through so-called hybrid user interfaces. There exist various solutions to manage adaptive, distributed or hybrid UIs. However, none of them covers all three aspects and users have to deal with multiple applications and configurations when developing adaptive distributed hybrid user interfaces. We introduce the eSPACE reference framework and conceptual model unifying the domains of adaptive, distributed and hybrid interfaces. While our reference framework has been inspired by the CAMELEON reference framework, the conceptual model is based on the Resource-Selector-Link (RSL) hypermedia metamodel. We propose an approach for adaptive distributed hybrid user interfaces where users can author their user interfaces based on the different levels of abstraction introduced by our reference framework. We further present a use case illustrating the extensibility, flexibility and reusability offered by our unified approach and discuss potential future work.

AB - Over the last decade, research on adaptive and distributed user interfaces (DUIs) has increased. We also witness a growing number of Internet of Things (IoT) devices, allowing digital user interfaces (UIs) to communicate with physical objects and vice versa through so-called hybrid user interfaces. There exist various solutions to manage adaptive, distributed or hybrid UIs. However, none of them covers all three aspects and users have to deal with multiple applications and configurations when developing adaptive distributed hybrid user interfaces. We introduce the eSPACE reference framework and conceptual model unifying the domains of adaptive, distributed and hybrid interfaces. While our reference framework has been inspired by the CAMELEON reference framework, the conceptual model is based on the Resource-Selector-Link (RSL) hypermedia metamodel. We propose an approach for adaptive distributed hybrid user interfaces where users can author their user interfaces based on the different levels of abstraction introduced by our reference framework. We further present a use case illustrating the extensibility, flexibility and reusability offered by our unified approach and discuss potential future work.

U2 - 10.1109/RCIS.2019.8877048

DO - 10.1109/RCIS.2019.8877048

M3 - Conference paper

SN - 978-1-7281-4844-1/19

SP - 1

EP - 6

BT - Proceedings of the 13th International Conference on Research Challenges in Information Science ( RCIS 2019)

PB - IEEE

ER -

ID: 47034269