Matches in ESWC 2020 for { ?s ?p This paper introduces a technique for linking vectorized maps to other RDF datasets that describe geographical entities, converting the geographical data into geo RDF data in the process and enriching individual geographical features with spatiotemporal metadata. The paper describes the approach and reports on preliminary evaluations of the prototype implementation based on a few performance metrics. This is a highly interesting and timely research question, and the proposed method, while not overly novel, seems convincing. The paper is clearly written, easy to follow. I have one concern, that should be easy to fix in a minor revision. The description of the reverse geocoding step should be more elaborate (Section 3.2). It is fairly unclear how ambiguities are resolved. There can be multiple objects in a given geo bounding box, with different types. For instance, polylines corresponding to roads, rivers, as well as areas corresponding to, e.g., buildings, lakes, parking, etc. Is there some typing from the shapefiles in the original vectorized data, and if so, is it used in the disambiguation process. And then, if so again, is it sufficient? For instance, the quality and level of detail of the vector data can also have an influence on the bounding box. Isn't this introducing uncertainty/ambiguity? Also, what happens if the reverse geocoding service returns nothing meaningful? Overall, it is unlikely that this step would yield 100% successful "tagging" of the vector data. How good/accurate coverage can we expect this step to yield?". }
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- Paper.48_Review.0 hasContent "This paper introduces a technique for linking vectorized maps to other RDF datasets that describe geographical entities, converting the geographical data into geo RDF data in the process and enriching individual geographical features with spatiotemporal metadata. The paper describes the approach and reports on preliminary evaluations of the prototype implementation based on a few performance metrics. This is a highly interesting and timely research question, and the proposed method, while not overly novel, seems convincing. The paper is clearly written, easy to follow. I have one concern, that should be easy to fix in a minor revision. The description of the reverse geocoding step should be more elaborate (Section 3.2). It is fairly unclear how ambiguities are resolved. There can be multiple objects in a given geo bounding box, with different types. For instance, polylines corresponding to roads, rivers, as well as areas corresponding to, e.g., buildings, lakes, parking, etc. Is there some typing from the shapefiles in the original vectorized data, and if so, is it used in the disambiguation process. And then, if so again, is it sufficient? For instance, the quality and level of detail of the vector data can also have an influence on the bounding box. Isn't this introducing uncertainty/ambiguity? Also, what happens if the reverse geocoding service returns nothing meaningful? Overall, it is unlikely that this step would yield 100% successful "tagging" of the vector data. How good/accurate coverage can we expect this step to yield?"".