Introduction to and motivation for open science
Open science has many aspects some equal it with reproducible research and some with open access. Some equal open science to Science 2.0 or to science. We can say that open science consists of the following components: open data (sharing of data with minimal restrictions), open formats (storing data and text in a known well-defined way), open standards (availability of definitions and their practical usability), open source (vendor-independent software available for modification, reuse, and distribution), open hardware (blueprints for devices and other physical object), open methodology (openness about all used methods and workflows), open peer review (reviewable process of judging scientific work), open access (availability of scientific work, especially journal articles), open educational resources (availability and reusability of teaching materials). Some authors add additional items and some remove from the list or use different, narrower or broader, definitions. There are different reasons for doing open science. The main group of reasons is represented by the following set of (often loosely defined) terms: replicability, repeatability, recomputability, reusability, and reproducibility.
This topic covers open science terms and motivation for open science. Software and source code plays major role in several aspects of open science. In the rest of the class, we will focus on software tools, open source, and several other related concepts and tools. Some tools will be general, some focused on the geospatial domain.
Get ready to use you computers during the class to try out things as we will be discussing the different topics and learning the individual tools. We will introduce and install the necessary software throughout the semester. Most of the software we will use (locally or remotely) is open source, so no university licensing or sign up for trial versions is required. Exception are some cloud services which are not completely open source, but allow any user a free registration and provide an easy way to for the users to leave the cloud.
- When will ‘open science’ become simply ‘science’? by Mick Watson, published in Genome Biology (2015)
- The evolution of open science Elsevier interview with Dr. Stephane Berghmans (2015)
- What, exactly, is Open Science? by Dan Gezelter from The OpenScience Project (2009)
- What is open science? by Eva Amsen at F1000Research Blog (2014)
- Open science in archaeology by Marwick et al. (2017)
- Plain Text Science
- Replication frustration by Pete Etchells in The Guardian
- Badges awarded at Open Science Framework
- What the Tech Industry Has Learned from Linus Torvalds by Jim Zemlin at TEDxConcordiaUPortland (2013)
- How to get tenure while practicing open science by Titus Brown at OpenCon Community Webcasts (2016)
- Rethinking research data by Kristin Briney at TEDxUWMilwaukee (2015)
- Sharing research data by Kevin Ashley from Digital Curation Center (2015)
Short and other texts
- Open Science published by National Institutes of Health
- What is Open Science? published by Elsevier Journals
- Credit Is Due (The Attribution Song) movie and song by Nina Paley
Introduction paragraph: Write a sentence or two introducing yourself to the class. Include your experience with any part of open science. You can incorporate this with the text described below.
Summary paragraph: Review some of the resources above and post a summary of two (or more) Texts or Long videos on the course message board. This summary should be only one or two paragraphs and should give overview of what you learned from the resources and how can this change how you do research. Additionally, think about this text as a help to other students who did not see this particular resource or are deciding if it is worth to read it.