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README.md

Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design

This folder contains all supportive material related to the paper "Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design", which is published in the Special Issue on Semantic Web Meets Health Data Management of the Semantic Web Journal. This paper can be accessed via this link.

Contents

In the paper, DIVIDE is explained through a running homecare monitoring example. This example is also used for the paper's evaluations.

This folder contains three subfolders:

  • ontology: This folder contains all files of the Activity Recognition ontology, used for the running homecare monitoring example, that is discussed in the paper. This is a snapshot of the DAHCC ontology, complemented with an ontology file KBActivityRecognition.ttl that represents all extra definitions related to the knowledge-driven activity recognition. All files in this folder together represent the Activity Recognition ontology. This ontology is also used for the paper's evaluations.
  • evaluations: This folder contains supportive material related to the evaluations performed in the paper.
  • eye-implementation: This folder contains some more details concerning the implementation of the initialization and query derivation of DIVIDE with the EYE reasoner.

Moreover, this folder contains the different versions of the paper that have been submitted to the Special Issue on Semantic Web Meets Health Data Management of the Semantic Web Journal.

  • paper_v1_submitted_2022-05-01.pdf: This PDF represents the original version of the paper, that was submitted on 1 May 2022. It contains additional details about the DIVIDE methodology and the use case scenario, that have been removed in the first revision of the paper.
  • paper_v2_submitted_2022-09-30.pdf: This PDF represents the revised version of the paper, that was submitted on 30 September 2022 and accepted on 12 January 2023.

The published version of the paper is available via this link.

The implementation of the DIVIDE central services can be found in the src/divide-central folder of this repository.

Citation

If you want to cite this paper, please use the following citation (APA style):

De Brouwer, M., Steenwinckel, B., Fang, Z., Stojchevska, M., Bonte, P., De Turck, F., Van Hoecke, S., and Ongenae, F. (2023). Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design. Semantic Web, 14(5), 893–941. doi:10.3233/SW-223281

When using BibTeX, use the following entry:

@Article{divide_swj,
  author  = {De Brouwer, Mathias and 
             Steenwinckel, Bram and 
             Fang, Ziye and 
             Stojchevska, Marija and 
             Bonte, Pieter and 
             De Turck, Filip and 
             Van Hoecke, Sofie and 
             Ongenae, Femke},
  journal = {Semantic Web},
  title   = {Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design},
  year    = {2023},
  number  = {5},
  pages   = {893--941},
  volume  = {14},
  doi     = {10.3233/SW-223281},
}

Contact

The main contact person directly involved with this research is Mathias De Brouwer. In case of any remarks or questions, you can email [email protected] or create a GitHub issue.