This is an area in which I’m very interested. I think it should be possible to build some tooling that would make it easier to construct such articles.
One dimension could be an abstraction layer over common datasets; if I could just pick and choose data sources that would make it easier to plug together. Currently data sourcing and cleaning is a bit opaque. This seems quite hard to solve in general, but if you could get a critical mass on a far interchange format, maybe public datasets would start using it. Otherwise someone in the community needs to curate wrapper layers on top of those public datasets.
Another aspect is the graph tooling/authoring; for this to really take off we’d need a “Wordpress for interactive articles”, basically some GUI tool or plugin to let non-technical users build these visualizations easily. I actually think this is pretty tractable.
The biggest hurdle i can see is more sociological; most people don’t think in terms of models. But at the margin perhaps better tooling could make “model curious” people better at this mode of thinking.
Interactive articles is one of those things that everyone wants to do but very few have the time or the incentive. Nevertheless, I think
a. publications like Distill have a solid place in the future of research dissemination.
b. this will not remain a niche but be more widely adopted (further in my concluding paragraph).
c. interactively will allow the reviewers and readers connect better to the key ideas in a submission and feel more confident in accepting good work, however crazy it may sound.
d. in the same way a certain language style hinders our thought, our limitations in expressivity via PDFs can be overcome.
e. transparency + interactivity of results should notably improve the arguable "reproducibility crisis"
My apprehensions are however with regards to the tooling. Research visualization use-cases will almost always tend to be ad-hoc (well, because it is research). It is extremely hard for me to imagine a set of tools that will be general as well as easily usable. There has to be a trade-off. I always think about TikZ [1] or even matplotlib [2] in this regard. Both of them are extremely powerful systems but often find themselves struggling in the trade-off between ease of use and flexibility. I don't think it is the fault of either systems themselves, it is just the nature of this kind of work. Although, I'd be remiss if I don't mention the advances Vega [3] has brought. In general, I think we do have reasonably expressive systems available today for interactive content, only that custom use-cases require a non-trivial effort to get meaningful results, as the article notes. As a result, I do not think better tooling is what is going to shift the needle here, unlike what the article notes in the challenges section.
The change has to come from the way incentives and incentives alone are structured. I care more about investigating deeper into a line of research rather than disseminating research in the most accessible manner at every tiny milestone (a published PDF paper). While I care about disseminating research, I care more about getting all the "insider knowledge" about a method before I go around acting as the evangelist. And this takes time, as any researcher would acknowledge. This is what motivates researchers in the first place. The dissemination is a less systematic part of science and involves people problems beyond any single researcher or organization. Consequently, it is also the part where researchers are least invested in.
In this sense, I think interactive publications like Distill will evolve to be more like Foundations & Trends (FnT) [4] than your usual fast-paced conference with bleeding edge ideas. FnT is extremely well-written, broad scoped and I've enjoyed every issue I've read. There is a market for something between a broad survey and a deep reference textbook. Like both, it takes years to distill knowledge to be accessible. Distill-like publications are poised to fill this gap. This is certain to be much more than just a niche art. But hoping distribution as widespread as cheap (in terms of the writing effort) PDFs seems like wishful thinking. Of course, this in no way means the pursuit of such idealized systems is in vain as history reminds us every time.
One dimension could be an abstraction layer over common datasets; if I could just pick and choose data sources that would make it easier to plug together. Currently data sourcing and cleaning is a bit opaque. This seems quite hard to solve in general, but if you could get a critical mass on a far interchange format, maybe public datasets would start using it. Otherwise someone in the community needs to curate wrapper layers on top of those public datasets.
Another aspect is the graph tooling/authoring; for this to really take off we’d need a “Wordpress for interactive articles”, basically some GUI tool or plugin to let non-technical users build these visualizations easily. I actually think this is pretty tractable.
The biggest hurdle i can see is more sociological; most people don’t think in terms of models. But at the margin perhaps better tooling could make “model curious” people better at this mode of thinking.