Identify walkthroughs of open science publishing from beginning to end: tools, practices, outcomes.

+7 votes
75 views
asked Aug 8, 2015 in Open Science by Savage Henry (105 points)

As we debate the topic, it might be useful to have one or more examples of idea-to-publication workflows. I don't mean just documented code on GitHub or Bitbucket, but an annotated process that includes tools and methods for each step:

  1. Initial idea development, reference management, document storage/collection

This might mean notes on using editing tools (emacs, vim, OpenOffice), formats (Markdown, LaTeX, Org Mode), and management tools (BibDesk, Mendeley, etc.)

  1. Data discovery/collection

This might include lists, and lists-of-lists of open data repositories (ICPSR for social scientists, Data.gov for the US, World Bank Databank, etc.) as well as tools/methods for collection (open data formats, web scraping, etc.).

  1. Code development and storage

I would include under this "code" for statistical analysis even if it is not done in what some would call a programming language (no need to debate this here), such as steps taken for spreadsheets, but also more technical work in R, Python, etc.

There are some good examples of how to use Git (this and this), but nothing that works this into the entire publishing workflow.

  1. Paper development/construction and revision tracking

I don't have a good sense for how prevalent the use is for tools that combine disparate tools into one document (knitr, Sweave, etc.), but I feel like these would be important things for someone to see as part of combining everything in a single, easily-shared and open framework.

There are plenty of great tutorials and whatnot for each step. But I'm asking if there are any good cases where a researcher has provided a guide through their whole process for a single work.



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commented Aug 18, 2015 by Alexander Konovalov (135 points)
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1 Answer

+4 votes
answered Aug 9, 2015 by Daniel Mietchen (1,165 points)

No precise guides of the kind you are asking for, but some pointers from chemistry and mathematics:

Jean-Claude Bradley has repeatedly written (in his blogs and elsewhere) about his team's workflows in experimental chemistry, but I can't find such a write-up right now, and he is sadly not with us any more to comment.

He gave lots of talks on the topic, though, and this one provides an overview of his tool chain, which largely consisted of general-purpose platforms that he just adopted for chemistry. His proposals to build something more "chemistry literate" did not get funded.

A similar effort in open-notebook chemistry was written up and paved the way for the still ongoing Open Source Malaria project, which has a background write-up, and its key people are usually quite responsive.

In mathematics, the poster child is the Polymath project, which basically just used blogs and a wiki. A good and publicly accessible summary is in Michael Nielsen's TEDx talk about it.



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