Review Comment:
The authors describe how they converted the transcripts of the debates of the European Parliament into RDF. They provide details on different aspects of the conversion process, from the creation of URIs, vocabularies used and how it has been published. The authors also show some numbers showing how many times the data was queried and provide use cases based on people who used the data.
There are a couple of issue with this paper. First, it is not clear how the RDF representation of the data makes it easier for interested parties (mostly non-semantic web experts) to consume and take advantage of this data. Second, the statistics of use only show that the data has been queried, but showing "7.5 thousand times" doesn't mean much; it would be recommended to give some other measure to compare with. Based on the web interface available I would suggest to provide form for political scientists and other researchers to query the data that does not require knowledge of SPARQL.
It is also worth adding a few lines on how this dataset is going to be maintained in the future. Making the code available is something very valuable indeed. A few minor issues are also indicated below:
"The content and provenance of the data and vocabulary are described using the void, prov and omv vocabularies."
Citations?
"The metadata are collected in a single graph on the server and as a turtle file in the well-known directory."
Citation to well-known
"over 5.5 thousand times and the dataset was queried through our service about 7.5 thousand times, of which 3,654 times"
Please be consistent how you present numbers. Also, write something like "more than 5 thousand", decimals look weird in that context
"Dataset quality One way to describe the quality of a Linked Dataset is the star system by Berners-Lee [2]. LinkedEP is a five-star collection"
Please remove that. The 5-star classification does not describe the quality of the data itself, only the format and eventually use of common vocabularies. People can still publish trash data using a 5-star scheme.
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