Should we build a shared visual space for training?

Analyzing and Reusing Data
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Hi everyone!

For a recent neurology conference, I had 30 minutes to explain hereditary movement disorders to a general audience. It took me longer to build this figure than the rest of the talk — and that was intentional, because it was the idea behind everything. I structured my whole presentation around it, and the figure became the “take-home message”. Here it is:

hereditary_movement_disorders_genes (3)
hereditary_movement_disorders_genes (3)1920×1110 88.2 KB

The goal was to show that:

  1. These disorders are very heterogeneous.
  2. Prevalence and genetic contribution can sometimes move in opposite directions.
  3. Knowing both helps decide when to order genetic testing and where to focus research.

That got me thinking — we all create figures like this for talks or publications. What if we had a shared space in Disocurse DCI Resources and Coordination where we could store these training data-visualization material? It could make life easier for others explaining the same concepts, while always acknowledging the author.

I’d love to hear your thoughts, especially from the task-forces data-visualization training

  1. Would something like this be useful?
  2. How could we make it practical and fair in terms of authorship and sharing?
  3. Does anyone volunteer to help lead or coordinate this? get-involved
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we could also share slides too honestly, i am always happy to share my talks and would benefit from others’ goodies as well. i wouldnt expect credit for anything and would be happy for whoever wants to use to benefit from my goodies. it’s not mandated so credit can be flexible with only whoever feels comfortable openly sharing uploading their stuff

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I think this is a great idea!

  1. Yes, absolutely
  2. One idea… maybe something like figshare? It has the option of setting up groups, people can be attributed for their submissions, and they can optionally make DOIs as well
  3. @paularp @vdardov would this be something the visualization task force would be interested in?

@jgottesman What do you think? Would it work to make a figshare group for our community?

Happy to hear other ideas as well!

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Revisiting the figshare vs zenodo idea, OU has a post with some pros and cons:

Pros

Figshare offers free deposits for open data up to 5 GB in file size. They issue persistent identifiers called DOIs for datasets. Users can “version” their data as simply as uploading updated files, and can easily embed Figshare datasets in other websites and blogs by copying and pasting a simple code. Other users can comment on datasets and download citation files to their reference managers for later use.

Figshare offers preservation backed by CLOCKSS, a highly trusted, community-governed archive used by repositories around the world. And you get basic information about the number of views and shares on social media your dataset has received to date.

Zenodo also offers free data deposits and issues DOIs for your datasets. Much like Figshare, the non-profit makes citation information for datasets available in BibTeX, EndNote, and a variety of other library and reference manager formats. Users can add highly detailed metadata for their files – much more than Figshare currently allows – which can aid in discoverability. Other Zenodo users can comment on your files. And best of all, Zenodo makes it easy to sign up with your ORCID identifier or GitHub account (If you don’t have a GitHub account yet, no worries! We’ll cover GitHub next week).

Both repositories have open APIs, making them very interoperable with other systems, and they are both user-friendly and fun to use.

Cons

For some, Figshare’s funding model is a serious drawback; it’s a for-profit company funded by Digital Science, whose parent company, Macmillian Publishing, is the keeper of the Nature Publishing Group empire.

Zenodo’s preservation plan is less robust than Figshare’s, and currently Zenodo can only host files 5 GB or less in size. Zenodo also lacks public page view and download statistics, meaning that you can’t track the popularity or reuse of the data you submit to the archive.