Open Data Day Activities

Today is International Open Data Day, which was first proposed in 2010. To do my part, we will discuss a few open data-related items. Namely, what can you do to make this day a success?

Logo of the Open Knowledge Foundation (based in London), who offer a host of Open Data Day acitivities.

1) You can host some of your unpublished data (whether they are linked to publications or not) at an open data repository. You can do this through a general repository such as Dryad or Figshare, or a specialized repository such as Open fMRI [1].

* another part of publishing data is the need for annotation and other metadata. This is a barrier to opening up datasets, but the benefits of doing so may outweigh the initial investments [2].

2) You can join a open access communities such as data.world, a new social media network that allows people to share datasets of all types and sizes.

3) You can commit to creating more systematic descriptions of your research methods (e.g. the things you do to create data). This can be done by creating a set of digital notes or protocol descriptions [3], and making them open through Jupyterhub and protocols.io [4], respectively.

4) You can host your own virtual Hackathon. Unsure as to how you might do this? Then you can earn any (or all) in a series of three badges (Hackathon I, Hackathon II, Hackathon III) created in conjunction with the Open Worm Foundation.

5) You can petition or get involved with municipal and state/provincial governments to ensure their committment to open public data.

Of course, there are other things you can do, and more innovation is needed in this area. Have some ideas or planning an event of your own. Let me know, and I will invite you to the Orthogonal Lab's new Slack channel on Open Science.


NOTES:
[1] This choice, of course, depends on the field in which you are working. I used this example because fMRI data seems to have good community support for data sharing. Consult the Open Access Directory to learn more about the specifics for various disciplines.

For more information about data sharing in the field of neuroimaging, please see: Iyengar, S. (2016). Case for fMRI Data Repositories. PNAS, 113(28), 7699-7700.

[2] Based on a paper recently posted to the bioRxiv, and based on some material from a recent talk. For more information, please see: Alicea, B. (2016). Data Reuse as a Prisoner's Dilemma: the social capital of open science. bioRxiv, doi:10.1101/093518.

[3] Olson, R. (2012). A short demo on how to use IPython Notebook as a research notebook. Randal S. Olson blog, May 12.

[4] In terms of witing better and more accessible protocols, please see the following examples:

Protocols.io (2017). How to make your protocol more reproducible, discoverable, and user-friendly.
February 25. dx.doi.org/10.17504/protocols.io.g7vbzn6

Daudi, A. How to Write an Easily Reproducible Protocol. American Journal Experts, http://www.aje.
com/en/arc/how-to-write-an-easily-reproducible-protocol/, Accessed February 27, 2017.