Matches in ESWC 2020 for { ?s ?p The paper introduces a tool, StreamPipes, designed to let users create data stream processing pipelines across different data sources. Semantic Technologies are used to power the adapters that connect to each data sources. It is an interesting piece of work and a sound paper but to better fit ESWC I would have like to see more information about the specifics challenges/motivations/value for using Semantic Web technologies here. In particular: * There is no indication of how identifiers can be consistently minted and re-used across sensors. If this is not an issue as no triples is created to connect across sensors, then where is the "Linked" of the linked data? * Following up on that, if the motivation for using JSON-LD and a triple store is the vocabulary (rather than linking resources), then I would argue the vocabulary presented in Listing 1.1 is very shallow semantic wise. It does not seem to be that JSON-LD brings much value there. * And lastly, this issue extends to the rules which are specified and apparently then processed outside of the semantic stack. Why not leverage OWL and the triple store to express and process this? * In terms of related work I would have expected to see a note on DataCube at least. And another on Prov-O eventually. A reference and comparision to https://dl.acm.org/doi/10.1145/1526709.1526788 would also make sense. Lastly, and more broadly, it seems the authors missed the work on semantic enriched IoT done in the context of the project "SpitFire" by Manfred Hauswirth and team. * Next to the interesting user study that validates the pipes system itself, the authors could also have considered adding an ablation study on the impact of taking the triple store and JSON-LD out of the picture. ------------------------ Update after rebuttal ------------------------ I would like to thank the authors for the responses to my question and those of the other reviewers. In the light of these (and trusting that some of those answers will make it through the final version of the paper), I'd like to raise my overall score for the paper and recommend its publication.". }
Showing items 1 to 1 of
1
with 100 items per page.
- Paper.136_Review.2 hasContent "The paper introduces a tool, StreamPipes, designed to let users create data stream processing pipelines across different data sources. Semantic Technologies are used to power the adapters that connect to each data sources. It is an interesting piece of work and a sound paper but to better fit ESWC I would have like to see more information about the specifics challenges/motivations/value for using Semantic Web technologies here. In particular: * There is no indication of how identifiers can be consistently minted and re-used across sensors. If this is not an issue as no triples is created to connect across sensors, then where is the "Linked" of the linked data? * Following up on that, if the motivation for using JSON-LD and a triple store is the vocabulary (rather than linking resources), then I would argue the vocabulary presented in Listing 1.1 is very shallow semantic wise. It does not seem to be that JSON-LD brings much value there. * And lastly, this issue extends to the rules which are specified and apparently then processed outside of the semantic stack. Why not leverage OWL and the triple store to express and process this? * In terms of related work I would have expected to see a note on DataCube at least. And another on Prov-O eventually. A reference and comparision to https://dl.acm.org/doi/10.1145/1526709.1526788 would also make sense. Lastly, and more broadly, it seems the authors missed the work on semantic enriched IoT done in the context of the project "SpitFire" by Manfred Hauswirth and team. * Next to the interesting user study that validates the pipes system itself, the authors could also have considered adding an ablation study on the impact of taking the triple store and JSON-LD out of the picture. ------------------------ Update after rebuttal ------------------------ I would like to thank the authors for the responses to my question and those of the other reviewers. In the light of these (and trusting that some of those answers will make it through the final version of the paper), I'd like to raise my overall score for the paper and recommend its publication."".