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Matches in ESWC 2020 for { ?s ?p The paper describes the Open Data management solution "Piveau", which is a framework for publishing, harvesting, and managing dataset descriptions. The framework is deployed at the European data portal, which is impressive in size and functionality. Current Open Data publishing frameworks, such as CKAN or OpenDataSoft, only partially support RDF metadata (e.g., only export of RDF, flat data schema, etc.). The proposed solution, "Piveau", clearly demonstrates the advantages of using semantic web technologies for the Open Data use case: The solution is very well-thought and scalable (as shown with the application in the European data portal). In particular, the section on the impact of SW technologies (6.3) is an interesting read and gives us a list of open issues which have to be tackled to support such solutions. While I really like the work and, in my opinion, it clearly should get accepted, I have some points that could help to improve the paper: * The difference between datasets and metadata descriptions was not always clear. In my opinion you could make more clear that the e.g. the importer collects metadata descriptions (and not datasets). A clarification/definition of terms at the beginning and a consistent use throughout the paper (dataset vs data vs metadata) could help to make this easier to understand. * Why do you compare to uData? While it is clear that CKAN is the most popular software for Open Data publishing, I was missing an argument why you select uData (and not OpenDataSoft, Socrata, DCAN, etc.) * To what extent are there actually links to other resources? Import of existing (e.g. JSON-based) dataset description makes it obviously not Linked Data. It could be mentioned in your critical assessment that the technology alone is not enough to get from Open Data to Linked Open Data. * While you discuss already related works with respect to management solutions, you could also include SW-based approaches which aim at harmonized/integrated Open Data metadata, e.g. [1, 2]. [1] Brickley, Dan, Matthew Burgess, and Natasha Noy. "Google Dataset Search: Building a search engine for datasets in an open Web ecosystem." The World Wide Web Conference. ACM, 2019. [2] Neumaier, Sebastian, Jürgen Umbrich, and Axel Polleres. "Automated quality assessment of metadata across open data portals." Journal of Data and Information Quality (JDIQ) 8.1 (2016): 2. p.3: recent efforts focusses on -> focus on". }

• Paper.60_Review.2 hasContent "The paper describes the Open Data management solution "Piveau", which is a framework for publishing, harvesting, and managing dataset descriptions. The framework is deployed at the European data portal, which is impressive in size and functionality. Current Open Data publishing frameworks, such as CKAN or OpenDataSoft, only partially support RDF metadata (e.g., only export of RDF, flat data schema, etc.). The proposed solution, "Piveau", clearly demonstrates the advantages of using semantic web technologies for the Open Data use case: The solution is very well-thought and scalable (as shown with the application in the European data portal). In particular, the section on the impact of SW technologies (6.3) is an interesting read and gives us a list of open issues which have to be tackled to support such solutions. While I really like the work and, in my opinion, it clearly should get accepted, I have some points that could help to improve the paper: * The difference between datasets and metadata descriptions was not always clear. In my opinion you could make more clear that the e.g. the importer collects metadata descriptions (and not datasets). A clarification/definition of terms at the beginning and a consistent use throughout the paper (dataset vs data vs metadata) could help to make this easier to understand. * Why do you compare to uData? While it is clear that CKAN is the most popular software for Open Data publishing, I was missing an argument why you select uData (and not OpenDataSoft, Socrata, DCAN, etc.) * To what extent are there actually links to other resources? Import of existing (e.g. JSON-based) dataset description makes it obviously not Linked Data. It could be mentioned in your critical assessment that the technology alone is not enough to get from Open Data to Linked Open Data. * While you discuss already related works with respect to management solutions, you could also include SW-based approaches which aim at harmonized/integrated Open Data metadata, e.g. [1, 2]. [1] Brickley, Dan, Matthew Burgess, and Natasha Noy. "Google Dataset Search: Building a search engine for datasets in an open Web ecosystem." The World Wide Web Conference. ACM, 2019. [2] Neumaier, Sebastian, Jürgen Umbrich, and Axel Polleres. "Automated quality assessment of metadata across open data portals." Journal of Data and Information Quality (JDIQ) 8.1 (2016): 2. p.3: recent efforts focusses on -> focus on"".