Open Access Week came and went last week, and I marked the event on the blog with a post on Open Access. But the Open movement goes far beyond just Open Access: there are lots of different flavors of open, with a select few explored in this post.
First let’s start with Open Notebook Science. This concept throws out the idea that you should be a hoarder, not telling others of your results until the Big Reveal in the form of a publication. Instead, you keep your lab notebook (you do have one, right?) out in a public place, for anyone to peruse. Most often ONS takes the form of a blog or a wiki. The researcher updates their notebook daily, weekly, or whatever is most appropriate. There are links to data, code, relevant publications, or other content that helps readers, and the researcher themselves, understand the research workflow.
The most obvious reason for doing Open Notebook Science is that you can get feedback while you are still working on your research. If you are having problems or are stuck, the community might be able to help you. Another potential benefit is more opportunity for collaboration with others working on similar or related projects. Of course, the altruistic reason for keeping an open notebook is to contribute to the reproducibility and credibility of your research. For more information, check out Carl Boettiger’ great site that tells you more about ONS and contains his own notebook.
Open Science is basically the same concept as open notebook science: you make sure anyone who wants information on your work, your data, or your process can find it easily. You may or may not keep a lab notebook online, however.
Open Source refers to software (it actually refers to lots of stuff, but I’m only going to talk about software here). From Wikipedia:
Open-source software is software whose source code is published and made available to the public, enabling anyone to copy, modify and redistribute the source code without paying royalties or fees.
An important component of the open source software model is the community. Developers and individuals can rally around the code, making it better and working as a group to improve the software.
Open-source code can evolve through community cooperation. These communities are composed of individual programmers as well as very large companies.
The statistical program R is a great example of open source software with an active, strong community.
Open Data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control. Data that is truly open should be released into the public domain (e.g., with a CC-0 license). For those that use the ONEShare repository via DataUp, your data will be open data.
And finally, Open Knowledge encompasses all of these concepts. It’s described as a set of principles and methodologies related to the production and distribution of “knowledge works” in an open manner. In this definition, knowledge can include data, content and general information. To learn more about the OK movement, check out the materials and resources on the Open Knowledge Foundation website.
