Figure 1 doesn't make it evident which classes are from DwC and which ones are not. This should be made visually clear in the figure, and mentioned in the figure legend.

Acknowledgement of individual contributors and groups of contributors (such as mailing lists) whose work didn't rise to the level of co-authorship should all be moved to the Acknowledgements section. In the middle of the text they distract.

How so? It it's important, it should be expanded.

I'm not sure I understand what is meant by this. I question though whether the authors have as much choice in "seeing" class instances as the sentence could be made out to say. If this is an OWL ontology (which I understand it is), and instance data are expressed in OWL, then class instances are owl:Individuals, which are entities, not "nodes". I.e., this statement makes me wonder whether the authors' view of their instance data might be in conflict with the very entailments of their OWL ontology.

In contrast to unreal or theoretical data? Probably not. Express more directly what the motivation or driving goal is.

This doesn't make much sense to me. What are the authors trying to say, and why is it important?

Need to explain why this can be a useful thing to do.

The readership of SWJ should not be assumed to have any biodiversity domain knowledge, and hence I suggest that as the first subsection the authors briefly introduce the salient aspects of a canonical biodiversity observation.

This will likely be very confusing to anyone not intimately familiar with biodiversity domain knowledge. Also, it's not obvious why these properties are missing from DwC.

Assuming that it was the authors who made this choice, use active voice.

This needs expanding - obviously it's one of the main motivating use cases for DSW.

I suggest to expand this - it could for the motivating use-cases from which to hang and unroll the unmet challenges, and consequently the goals behind developing DSW.

This section needs to be brought into a proper narrative. In its current form, especially following there is much to draw from the text is more like an enumerated sequence (which isn't even strictly chronological) and lacks a narrative thread that keeps a reader oriented.

expressed as?

Doesn't this apply to any standard, or more broadly informatics product, including the presented here?

became known?

What standards? Surely not any standard?

Isn't the reason more the debate over consensus semantics?

Slightly reworded from initially posted version to be less confusing. Thanks @dwhly.

I notice that it's not clear to what exact piece or event to source this. Perhaps still link to the William Gibson's Wikiquote page, which includes the quote and its provenance?

Is there some insight available into why instructors find it difficult to apply what they have been taught? Is it the imparting of these ideas that needs improvement, or are the ideas not as applicable in SwC as they were thought to be, or is there simply heterogeneity in that some ideas are much easier to apply than others? If the latter, which ones fall into which category?

Aren't you arguing above that diversity of backgrounds and starting skills is a constant challenge? It didn't seem from earlier arguments in the text that simply recruiting along a uniform discipline will address this problem.

How do you know that this is the case? From feedback alone, or are there other kinds of observations or evidence?

As a reader, I feel left hanging by the section ending with this statement. Are there ideas about how this could be done, and to begin with, what were some of problems encountered with the less systematic approach being practiced now? (The preceding text seems to only cite advantages.)

I'm embarrassed to ask what's an xUnit style framework. Spell out what that is, and/or add a reference or URL?

Insert "do" after don't.

If your goal is a high rate of retention and completion, that is. However, widening reach could also be a worthwhile goal. If a single MOOC reaches 10,000 students instead of 800 students reached by 20 physical SwC workshops, even a completion rate of only 10% will still have taught more students with the single MOOC than with the 20 physical workshops. MOOCs clearly aren't a panacea, and they may indeed be ill-suited to the learning objectives of SwC, but that and why this is so needs a little more depth to be convincing.

Is this meant to be "native"?

I think this assertion needs better qualification to be really justified. Obviously, several ways to assess programmer productivity, and also scientist productivity, exist. Hiring and tenure committees regularly assess productivity of scientists. Arguably, the ways this is usually done suffers from various problems such as failing to encompass the full spectrum of products resulting from a scientist's work. Perhaps the author means that it is some of these shortcomings of current productivity assessment methods that effectively prevent measuring the productivity impact of SwC's teachings, but that needs to be spelled out better.

Isn't this somewhat contradicting some lessons learned stated earlier, which seemed to say that for several reasons the SwC curriculum faces impossibly high barriers for integration into university curricula, at least in the current environment. If contrary to expectation this has now become possible, can something be learned from the cases where it has been successfully integrated?

Spell out. Also, how about a URL?

This needs some qualification to fully make sense as following from the preceding sentence. If the tools and approaches SwC teaches are good ones that "work", and SwC uses those tools and approaches itself, how can this be a downside, presuming that those able to contribute material are in fact familiar with those tools and approaches. I can imagine some ways in which this can still be a downside, but for clarity this should be spelled out better.

The biggest problem of a significant rate of no-shows is probably the fact that due to the space limitations other students who would have and benefitted from the course had to be denied because of the no-shows taking the space away. Have other possibilities to deter no-shows been explored (and if so, how effective have they been found)?

If the no-show rate is somewhat predictable (and it sounds like it is), then wait-listed students could be told to show up anyway on the day of the course, because there would likely be enough no-shows to make room for them. Has this been tried, and to what extent does it work?

This whole paragraph doesn't mention the words "brand", "brand recognition", and "brand reputation"; yet it is essentially about those concepts, isn't it? Why not say it directly?

Insert "even" before with.

It's probably not just a question of having instructors, but also of having demand for (and thus acceptance of) the SwC curriculum as useful in increasingly many disciplinary areas.

I have heard concerns and objections some people have with R's syntax and way of doing things. But every language (including Python) has its detractors, and I don't think the particular concerns with R are necessarily widely known let alone understood. So I would suggest to either delete this clause (is it really needed for the argument?), or if chosen to be left in place, to substantiate it, at least by giving a reference to a fuller discussion of R's problems.

What does typically mean? 80-90% of all SwC enrolled students, or on average 80-90% of those enrolled in a workshop? I.e., how much variance is there between workshops?

The figures suggest a tapering off in the recent past. Is this more likely a fluke due to limited or censored data, or is there a trend showing?

Hope is nice but not a good basis on which to base scientific conclusions. Do you have evidence that suggests that neither fraction of people is significant with respect to those enrolled and attending both days? Evidence that both fractions of people has stayed relatively constant over time, and not changed more recently?

Typo (one instead of two 'l')

I'd find it really useful to spell this out a little more. What are our other costs? Instructor travel and expenses, room rental? What tasks do the coordinators perform, how does this scale? Or in other words, presumably there is a division between costs of operating that benefit from economies of scale, and those that do not. More insight into this division would be quite helpful as a lesson learned.

I'm curious as to why 2 days. The lessons learned stated earlier seem to say that attention drops after 3 days, not 2 days. Why was the decision made to shorten to 2 days, not 3 days?

Is there no link or other reference available?

The difference in wording suggests that the Mozilla Foundation's backing didn't come in the form of a grant. Can it be spelled out (at least broadly) what that support consisted of?

For readers who aren't already fully on board with this, It would help to better set up the argument. Why is scaling up the model desirable or necessary? What is enough people? Couldn't funding also come from a single or few sources? Many courses are sustained by student tuition; how would this likely not work for SwC?

I think it's worth to qualify this statement in respect to the goals. As the paragrapgh goes on, it could be said that In some definition the MOOC format has worked (for example, compared to retention and completion rates of other MOOCs); the failure that the author reports presumably means chiefly that the goals laid out for a SwC course weren't met by the MOOC format.

Is there evidence or references for the factors the author enumerates constituting the major driving causes? More specifically, the list is conspicuously missing the explosion of data that had swept, and has continued to sweep into almost every scientific discipline. Data richness is enormously powerful for science, yet wrestling insight from it at this scale invariably and pervasively requires computational processing. Maybe this is part of the dozens of other innovations, but I would still argue that the data deluge has constituted a primary rather than a marginal driver of this landscape change.

Spell out at first use.

The backstory to what motivated (or necessitated?) the large consortium of funders is missing here. However, given the last paragraph in this section, it seems there would be interesting aspects of it that would help make setting up the argument. Does the large consortium reflect primarily wide buy-in to SwC's utility, or primarily the difficulty of obtaining enough funding from any one institution or partner? The last paragraph suggests it's the latter, but it's not clear.

Perhaps it's primarily the real problems of their own that provide the motivation for having the time (to learn about addressing them). I.e., percentage-wise, how many students does SwC get today who take the course primarily because they have time, and who do not yet have real problems of their own for which they hope to learn solutions?

More importantly perhaps, does this not also point out a path for justifying the inclusion of SwC-inspired teaching units into undergraduate CS curricula? While for some (or most?) academic research career paths the relevance of version control mastery is perhaps less obvious, it's a qualification nearly all of industry ask of CS graduates applying for a software engineer position.

I'm not convinced that one isn't mostly or entirely a consequence of the other. Open source and collaborative development also was far less widespread in scientific software development before many of the barriers to that were significantly reduced by distributed version control such as Git, and usability and social coding focused resources such as Github. If the tools and file formats that are most widely used are simply refractory to collaboration, it's not a surprise if then a culture of collaboration is rare.

If this is the main driver behind this kind of course not finding interest at university CS programs, is the situation then different at teaching-focused schools, such as small liberal arts colleges? There are small liberal arts colleges with strong CS programs; have they indeed been more welcoming to adopting SwC into their curricula?

Based on context, it would be the SwC workshop or material. I suggest to reword so it is clear that it actually refers to the practices and tools being taught by SwC.

Perhaps this would be beyond the scope of the paper as a commentary, but it would be interesting to see whether this is then different at decidedly interdisciplinary programs, for example programs interfacing computational biology / computer science / math.

Remove parentheses.

I suggest that the authors highlights the major ways in which these courses differ from the SwC courses run today. As written now, deducing that from the two lessons learned is left as an exercise to the reader, and only those already familiar with SwC will know that indeed today's SwC workshops do differ in these ways.

Change parentheses to comma. The parenthetical phrase is important to make sense of the sentence. (And if similar contextual information can be given about Brent Gorda, i.e., information that helps to understand why he was invited, I suggest that be added to, as his current affiliation fails to explain that.)

This seems more an example to me than a restatement of run before they could walk. Thus, this should be e.g. (or spelled out for example).

Researchers at-large, or researchers who participated in a Software Carpentry workshop?

Assuming that learning binds to at least some of what we taught as well, the comma is extraneous. Or add a comma after and applying.

Are they not in fact taught, even if only indirectly, that programs are typically not revisited again once passed on (to the course instructor, for example), and hence thinking about maintainability is wasted effort?

Do you mean the complement to those doing HPC? The phrase strikes me as needlessly cryptic. And are you sure that scientists developing HPC software are exempt from the trend you describe?

Is there a reference for this form of the Iron Triangle? Googling the phrase only turns up the well-known project management Iron Triangle, and its adaptation to software projects. The latter has Resources, Scope, and Time at its corners, not hardware, algorithms, and programming.

Pineal foramen absent