Review Comment:
For this revision, the authors have taken a significant effort to take into account the reviewers' comments. In particular, I like the idea of introducing additional use cases, but the authors could spend more space on those, since they are quite superficially described. With this, I do not mean that they should conduct yet another user study for those use cases, but discussing which information needs could be better addressed in those scenarios using the space/time visualizations in SPEX would be appropriate.
My main concern, however, still remains. As stated in my review for the previous revision:
>The authors themselves state that their "study was preliminary" and "does not yet allow drawing representative conclusions" - this is not the degree of maturity expected for a journal publication.
I can see that it is difficult and laborious to repeat or extend the user study. On the other hand, the evidence in the paper is not what I expect for a journal publication. In essence: what is shown is that the tool at hand serves a particular use case. It is not shown, however, that it does so better than any state of the art tool. The functional comparison in table 1 also provides no such evidence (cf.: for many tasks, quite a few people are surprisingly effective with a text editor, despite the existence of much more advanced visual toolkits).
In the current state, my feeling is that this work is a very good conference publication, but lacks the significance of a journal article.
Furthermore, the conclusions in section 6.3 are quite weak. Apart from the very small number of participants, many of the observations can also have other causes. For example, the authors state that the participants who were less successful than others also made use of the space/time visualization less often. Although it is not explicitly stated, the text suggests that the reverse should hold, i.e., using those visualizations leads to more successful task completions. This, however, would not be a valid conclusion.
Another point that is questionable is the dataset size, made explicit by the authors in this revision. 3,000 triples is not a very large dataset, my assumption is that this corresponds at most a few hundred maps. There are datasets in the LOD cloud that are by several orders of magnitude larger than that, and that may come with very different challenges (both in terms of user interaction as well as implementation) - in fact, I believe that SPEX could be particularly helpful with such larger datasets, given that it is implemented in a scalable fashion.
Furthermore, I am a bit puzzled that the authors claim that they do not have information about the usage of time and space vocabularies in Linked Open Data. Two standard sources for estimates are
* LODStats, see http://stats.lod2.eu/ (tab: Vocabularies)
* The latest state of the LOD cloud report, http://linkeddatacatalog.dws.informatik.uni-mannheim.de/state/ (section 4.2.1)
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