“PLOS has released a preprint and supporting data on research conducted to understand the needs and habits of researchers in relation to code sharing and reuse as well as to gather feedback on prototype code notebooks and help determine strategies that publishers could use to increase code sharing.
Our previous research led us to implement a mandatory code sharing policy at PLOS Computational Biology in March 2021 to increase the amount of code shared alongside published articles. As well as exploring policy to support code sharing, we have also been collaborating with NeuroLibre, an initiative of the Canadian Open Neuroscience Platform, to learn more about the potential role of technological solutions for enhancing code sharing. Neurolibre is one of a growing number of interactive or executable technologies for sharing and publishing research, some of which have become integrated with publishers’ workflows….”
“Lab notebooks are good for writing down procedures, observations, conclusions and for drawing flow charts and diagrams by hand. However, in order to accommodate the increase of digital data collected, researchers have taped instrumentation and computer printouts onto the pages of their notebooks, or cross-referenced larger data sets by recording file names and locations in the notebook.
An ELN (electronic lab notebook) is a software tool that in its most basic form replicates an interface much like a page in a paper lab notebook. In this electronic notebook you can enter protocols, observations, notes, and other data using your computer or mobile device. This offers several advantages over the traditional paper notebook.
The number of available ELN tools is increasing and the functions of each are quickly changing. As a result, it may be confusing to evaluate all of the advantages and limitations of each when looking for the right solution for your project.
The Electronic Lab Notebook Matrix has been created to aid HMS researchers in the process of identifying a usable Electronic Lab Notebook solutions to meet their specific research needs. Through this resource, researchers can compare and contrast the numerous solutions available today, and also explore individual options in-depth….”
“In a recent article, I explained why open source isa vital part of open science. As I pointed out, alongside a massive failure on the part of funding bodies to make open source a key aspect of their strategies, there’s also a similar lack of open-source engagement with the needs and challenges of open science. There’s not much that the Free Software world can do to change the priorities of funders. But, a lot can be done on the other side of things by writing good open-source code that supports and enhances open science.
People working in science potentially can benefit from every piece of free software code—the operating systems and apps, and the tools and libraries—so the better those become, the more useful they are for scientists. But there’s one open-source project in particular that already has had a significant impact on how scientists work—Project Jupyter….”
“Perhaps the paper itself is to blame. Scientific methods evolve now at the speed of software; the skill most in demand among physicists, biologists, chemists, geologists, even anthropologists and research psychologists, is facility with programming languages and “data science” packages. And yet the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.
What would you get if you designed the scientific paper from scratch today? …
Software is a dynamic medium; paper isn’t. When you think in those terms it does seem strange that research like Strogatz’s, the study of dynamical systems, is so often being shared on paper …
I spoke to Theodore Gray, who has since left Wolfram Research to become a full-time writer. He said that his work on the notebook was in part motivated by the feeling, well formed already by the early 1990s, “that obviously all scientific communication, all technical papers that involve any sort of data or mathematics or modeling or graphs or plots or anything like that, obviously don’t belong on paper. That was just completely obvious in, let’s say, 1990,” he said. …”
“Romer believes in making research transparent. He argues that openness and clarity about methodology is important for scientific research to gain trust. As Romer explained in an April 2018 blog post, in an effort to make his own work transparent, he tried to use Mathematica to share one of his studies in a way that anyone could explore every detail of his data and methods. It didn’t work. He says that Mathematica’s owner, Wolfram Research, made it too difficult to share his work in a way that didn’t require other people to use the proprietary software, too. Readers also could not see all of the code he used for his equations.
Instead of using Mathematica, Romer discovered that he could use a Jupyter notebook for sharing his research. Jupyter notebooks are web applications that allow programmers and researchers to share documents that include code, charts, equations, and data. Jupyter notebooks allow for code written in dozens of programming languages. For his research, Romer used Python—the most popular language for data science and statistics.
Importantly, unlike notebooks made from Mathematica, Jupyter notebooks are open source, which means that anyone can look at all of the code that created them. …”