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The MASSIF platform : a modular and semantic platform for the development of flexible IoT services

Pieter Bonte (UGent) , Femke Ongenae (UGent) , Femke De Backere (UGent) , Jeroen Schaballie (UGent) , Dörthe Arndt (UGent) , Stijn Verstichel (UGent) , Erik Mannens (UGent) , Rik Van de Walle (UGent) and Filip De Turck (UGent)
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Abstract
In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated.
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Citation

Please use this url to cite or link to this publication:

MLA
Bonte, Pieter et al. “The MASSIF Platform : a Modular and Semantic Platform for the Development of Flexible IoT Services.” KNOWLEDGE AND INFORMATION SYSTEMS 51.1 (2017): 89–126. Print.
APA
Bonte, P., Ongenae, F., De Backere, F., Schaballie, J., Arndt, D., Verstichel, S., Mannens, E., et al. (2017). The MASSIF platform : a modular and semantic platform for the development of flexible IoT services. KNOWLEDGE AND INFORMATION SYSTEMS, 51(1), 89–126.
Chicago author-date
Bonte, Pieter, Femke Ongenae, Femke De Backere, Jeroen Schaballie, Dörthe Arndt, Stijn Verstichel, Erik Mannens, Rik Van de Walle, and Filip De Turck. 2017. “The MASSIF Platform : a Modular and Semantic Platform for the Development of Flexible IoT Services.” Knowledge and Information Systems 51 (1): 89–126.
Chicago author-date (all authors)
Bonte, Pieter, Femke Ongenae, Femke De Backere, Jeroen Schaballie, Dörthe Arndt, Stijn Verstichel, Erik Mannens, Rik Van de Walle, and Filip De Turck. 2017. “The MASSIF Platform : a Modular and Semantic Platform for the Development of Flexible IoT Services.” Knowledge and Information Systems 51 (1): 89–126.
Vancouver
1.
Bonte P, Ongenae F, De Backere F, Schaballie J, Arndt D, Verstichel S, et al. The MASSIF platform : a modular and semantic platform for the development of flexible IoT services. KNOWLEDGE AND INFORMATION SYSTEMS. 2017;51(1):89–126.
IEEE
[1]
P. Bonte et al., “The MASSIF platform : a modular and semantic platform for the development of flexible IoT services,” KNOWLEDGE AND INFORMATION SYSTEMS, vol. 51, no. 1, pp. 89–126, 2017.
@article{8533438,
  abstract     = {In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated.},
  author       = {Bonte, Pieter and Ongenae, Femke and De Backere, Femke and Schaballie, Jeroen and Arndt, Dörthe and Verstichel, Stijn and Mannens, Erik and Van de Walle, Rik and De Turck, Filip},
  issn         = {0219-1377},
  journal      = {KNOWLEDGE AND INFORMATION SYSTEMS},
  keywords     = {IBCN},
  language     = {eng},
  number       = {1},
  pages        = {89--126},
  title        = {The MASSIF platform : a modular and semantic platform for the development of flexible IoT services},
  url          = {http://dx.doi.org/10.1007/s10115-016-0969-1},
  volume       = {51},
  year         = {2017},
}

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