Meta-Data for a lot of LOD

Updated Review: The paper introduces the LOD Laundromat Meta-Dataset (recently Clean and Linked Open Data - C-LOD Meta-Dataset) that allows to publish comparable Dataset descriptions. This novel vocabulary is disseminated as LOD and offers algorithmically generated information for currently about 38 billion triples in 650,000 documents – all crawled by the LOD Laundromat.
The authors pointed out, that existing datasets, such as LODStats and Sindice, show a lack of comparable meta-data, leave a lot of space for interpretation and/ or ignore information on the meta-data creation process. Therefore, a requirements analysis results in 7 key aspects for the definition of the new LOD Meta-Dataset, which are prioritized afterwards. Key characteristics and novel meta-data properties are introduced, explained in detail and comparatively discussed by delimitations between the introduced dataset and other specifications, such as VoID, Bio2RDF and VoID-ext. The paper concludes with a summery and two possible future works regarding a more efficient creation of the Meta Dataset.
This contribution is relevant to the community and has a high potential usefulness, as it offers a novel way of accessing recent description meta-data on public available datasets that can be used for comparison and analysis purposes. The paper is written well, lucid and comprehensible. The used terminology is technically correct and the specification seems to be valid. The paper structure is well organized and the purpose of this Linked Dataset becomes clear. In contrast to the last version, the paper benefits from better introductions and more evaluation results.
All required information (name, URL, versioning, licensing and availability) are given in the paper and especially stated in the vocabulary that in turn re-uses other established vocabularies – e.g. PROV-O, HTTP and Error Ontology. In terms of the Five Stars of Linked Data Vocabulary Use, the authors classified their vocabulary as 4/5 stars, since this vocabulary is not linked by other vocabularies yet.
Paper strengths:
- Novel LOD Meta Dataset representation for comparison purposes based on a sophisticated requirements analysis
- Clear specification including new properties for statistical evaluations
- Available sources: Vocabulary (Creative Commons 3), code on GitHub and data dumps on a daily updated basis
Paper weaknesses:
- Not re-used by other vocabularies so far (5th star of Linked Data Vocabulary Use)
I would encourage to accept the paper.

This manuscript was submitted as 'Data Description' and should be reviewed along the following dimensions: Linked Dataset Descriptions - short papers (typically up to 10 pages) containing a concise description of a Linked Dataset. The paper shall describe in concise and clear terms key characteristics of the dataset as a guide to its usage for various (possibly unforeseen) purposes. In particular, such a paper shall typically give information, amongst others, on the following aspects of the dataset: name, URL, version date and number, licensing, availability, etc.; topic coverage, source for the data, purpose and method of creation and maintenance, reported usage etc.; metrics and statistics on external and internal connectivity, use of established vocabularies (e.g., RDF, OWL, SKOS, FOAF), language expressivity, growth; examples and critical discussion of typical knowledge modeling patterns used; known shortcomings of the dataset. Papers will be evaluated along the following dimensions: (1) Quality and stability of the dataset - evidence must be provided. (2) Usefulness of the dataset, which should be shown by corresponding third-party uses - evidence must be provided. (3) Clarity and completeness of the descriptions. Papers should usually be written by people involved in the generation or maintenance of the dataset, or with the consent of these people. We strongly encourage authors of dataset description paper to provide details about the used vocabularies; ideally using the 5 star rating provided here .

Compared to the previous version "LOD in a Box: The C-LOD Meta-Dataset", the authors have made significant improvements. The clarity of the writing has improved a lot and the readability of the paper has improved likewise. Various details of the system have been clarified, and its relation to the LOD Laundromat is now much clearer. References are provided for all the works reused in the paper and seem to be much more complete. For this reason, I recommend an accept with the following (very) minor revisions.

MINOR COMMENTS:

* "For example, Bio2RDF ... to from each predicate." How Bio2RDF extends/amends VoID was not clear to me from the text. Please try to explain this better. Also is the information about the number of entities linked to/from a given predicate not already included in the property partitions of VoID in combination with distinct-subject, distinct-object?

* "Firstly, several definitions of meta-data property are ambiguous. As an example we take the VoiD property "void:properties" which ought to denote the number of distinct RDF properties that occur in a dataset. ..." The original authors of VoID clear define what void:properties refers to in both official documents [1,2]: "number of properties – The total number of distinct properties in a void:Dataset. In other words, the number of distinct resources that occur in the predicate position of triples in the dataset." (A similar operational definition is given for "void:classes".) The ambiguity that the authors claim in the paper is thus simply not there in the VoID specification. The answer for the example they give is unambiguously 4. The authors should remove any claims that void:properties is ambiguous or suggesting that it is unclear whether or not properties not appearing as a predicate should be counted (they clearly should not). Instead, you could perhaps argue that it is interpreted incorrectly in some datasets or tools (if you can point to examples). An easier solution would be to point to the fact that "void:entities" is ambiguous for the reasons you mention (which I understand was left that way by design), and that something like "void:uriLookupEndpoint" cannot be determined from the data and typically needs to be specified manually.

* It would be useful to add links for some example Linked Data IRIs to the paper with some description of the naming scheme, e.g.:
http://lodlaundromat.org/resource/dcefd287bd0c7d4efb543c7260b6dcf8
http://lodlaundromat.org/resource/dcefd287bd0c7d4efb543c7260b6dcf8/metrics
http://lodlaundromat.org/resource/dcefd287bd0c7d4efb543c7260b6dcf8/metri...
etc.

TYPOS, etc.:

Throughout:
* "VoiD" -> "VoID" seems to be how the authors stylise it

Abstract:
* "38 billion billion"

Section 3.1:
* "higher level. I.e., it includes" -> "higher level; i.e., it includes"
* "ambigue" -> "ambiguous"

Section 4.1:
* "Considering [that] only" (For readability rather than grammar)
* I hope you don't mind me saying this but as far as large grey rectangles go, I think Figure 1 might be one of the ugliest I've ever seen. In addition, it doesn't contain ticks on the x-axis, the origin isn't clear, it probably doesn't need to span two columns, etc. Could you clean it up just a little bit and make it somehow less depressing to look at?
* Table 1, caption should go above the table I think? Check the journal style. You should also add to the caption something to indicate that only properties computable from an RDF dataset without manual intervention are considered, since VoID contains a bunch of other properties not included (e.g., open search description, link sets, etc.). Also watch the capitalisation in the meta-data property names.

Section 4.4:
"over 650,000 containing" Clarify over 650,000 _what_.

References:
The style of references needs to be cleaned up, especially since this is a journal paper. For example, #1, "LDOW" is not enough details for a workshop. Words such as "rdf" appear in lower-case. Sometimes the publisher (e.g., Springer) is given, sometimes it's not. Sometimes pages are given, sometimes not. On reference #11, the publisher is given as Citeseer. #3 uses "et al." for six authors while #14 lists all ten authors. Also remember to update reference #18 accordingly. In general, clean-up and thoroughly revise the reference style/details.

[1] http://vocab.deri.ie/void
[2] http://www.w3.org/TR/void/