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Ten simple rules...

Posted by Rafael Martinez-Feria

Rules for the Care and Feeding of Scientific Data

In this article, Goodman et al. (2014) provide discussion on why it is important to “care for and feed” research data. This is an easy read with much insight and practical advice for ensuring that data and associated analyses continue to be of value and to be recognized. This advice is offered as 10 rules scientists can follow:

• Rule 1. Love Your Data, and Help Others Love It, Too
• Rule 2. Share Your Data Online, with a Permanent Identifier
• Rule 3. Conduct Science with a Particular Level of Reuse in Mind
• Rule 4. Publish Workflow as Context
• Rule 5. Link Your Data to Your Publications as Often as Possible
• Rule 6. Publish Your Code (Even the Small Bits)
• Rule 7. State How You Want to Get Credit
• Rule 8. Foster and Use Data Repositories
• Rule 9. Reward Colleagues Who Share Their Data Properly
• Rule 10. Be a Booster for Data Science

My take:

The rule are you most likely to follow: Rule 5

I just love the idea of including the data and code that support my conclusions on a paper. Tables and figures within papers tend to be space-limited so I would go for the supplemental materials. Also, I think most publishers offer some sort of data repository service along with the doi of the paper. But perhaps your database is too big to be included in an excel file along with the paper. So you could instead self-publish your data using a service such as Dataverse (RULE 2) and cite it on your paper, but I would do this soon prior publication. Of course, the data shared has to have a certain level of cleanliness. Do everyone a favor removing missing data or outliers. I think that summaries of data (e.g. average values by treatment instead of by plot) would be also appropriate to share.

The rule do I think may never follow: Rule 4

Well, this is not entirely true. It is a MUST to share your workflow in the Materials and methods section of a paper. In papers about cropping systems modeling (my field), the M&M sections is almost **all ** a description of the workflow. So using other software to document your workflow may be a large investment of time for a process that you may have to anyway do it “manually” when you are writing. I am not sold on this one.

The rule I would really like to follow, but I know deep down that I’d fail: Rule 6

This one is tricky.Don’t get me wrong. I will try my best to get into the habit of publishing my code + data in online repositories. This will not only be so others can see how I go about analyzing my data, but also for the benefit of my future self of keeping my code + data organized and tidy. However, making data and analysis public can be a contentious issue among collaborators (I usually use other’s data in my work), so I foresee some limitations to doing this in the future.

Reference:

Goodman A, Pepe A, Blocker AW, Borgman CL, Cranmer K, Crosas M, et al. (2014) Ten Simple Rules for the Care and Feeding of Scientific Data. PLoS Comput Biol 10(4): e1003542. doi:10.1371/journal.pcbi.1003542