Research Workflows
If you’re a scientist or researcher, you’ll often find yourself in a variety of roles. Sometimes, you’ll be taking meeting notes, other times you’ll be writing manuscripts or grant applications. You may spend time teaching or organizing lab groups, or presenting at conferences. However, you’re probably using a number of different tools for these activities, PowerPoint, Word, Google Docs, LaTeX, Jupyter, and more.
But it’s likely that with the tools you’re using, you’ve found they don’t integrate well, and they’re decoupled from your research. Diagrams and figures are pasted into PowerPoint, severing the link between your data and your presentation. Manuscripts are published as static PDFs, months or years after the work is completed, with limited feedback opportunities. This affects not only you, but also the speed of scientific discovery — as it impacts scientific reproducibility globally.
Curvenote was created to address these challenges. Curvenote sits at the intersection of scientific collaboration, publishing, and technology. We believe how we share and communicate scientific knowledge should evolve past the status quo of print-based publishing and all the limitations of paper.
Curvenote believes in accessible, dynamic, open, reproducible, and connected science for all.
Curvenote is an interactive text editor for modern science. It supports your entire workflow — from note-taking, research, collaboration, and publishing, to everything in between. It also integrates with Jupyter, so that your Curvenote articles can also be linked to your data, code, and simulations.
How Can I Use Curvenote to Improve My Workflows?
There are multiple ways to integrate Curvenote into your existing workflows: from introducing it in your preliminary research, to recording in-progress research and meeting notes, to publishing manuscripts.
To learn more we interviewed Dr. Lindsey Heagy, an assistant professor in Earth Data Science and researcher at the University of British Columbia. Lindsey’s also a Science Advisor for Curvenote, which she’s using for multiple of her ongoing projects.
Curvenote for Individual Research Notes
Lindsey uses both Jupyter and Curvenote for her own preliminary research notes.
“Jupyter is the space where I do a lot of my personal research,” she said. “One of the questions that I’ve been looking at is within electromagnetic geophysics. I’m trying to understand how different physical properties change the data that we observe.”
Typically, researchers study variations in electrical conductivity; how easily current can pass through a given material. This is important in applications where we need to characterize the subsurface, like locating groundwater or mineral resources, or cleaning up areas with exploded ordnance. Lindsey is studying how magnetic properties also influence these data. The question she’s trying to answer is, if we have variations in both of these properties, how will that change the data we’re seeing?
“To do that, I first set up simulations and examples in Jupyter,” explained Lindsey. “Then I use Curvenote’s Jupyter extension to version my Jupyter Notebooks, and save my various states of work. What’s really powerful about that, is the peace of mind knowing that with one-click I have a back-up of all my work.”
With Curvenote’s Jupyter extension, you can also add comments to Jupyter Notebooks — which Lindsey uses to keep track of her own work.
“Often in the academic world, your time comes in spurts,” she said. “You might have two days to work on something, and then all of a sudden you have four days of meetings. You have to put down your work, but then later you’ll come back and pick it up.”
“With Curvenote, it’s useful to have that record of what you’ve done at each stage. And you can add comments to yourself to say things like ‘I should check this out later’, or ‘this plot doesn’t make any sense, I have no idea what’s going on’. It helps me capture my workflow, processes, diversions, and updates as I move along.”
Curvenote for Group Research Notes
Lindsey also participates in the SimPEG (Simulation and Parameter Estimation in Geophysics) group — where the note taking process is even more complex.
“It’s a group of geoscientists who are using SimPEG, an open source software package for geophysics, for their work,” said Lindsey. “Folks are writing code, and showcasing different use cases from their research and applications, so we can improve the code base. This ensures SimPEG continues to serve everyone’s research within this space.”
The SimPEG group has adopted Curvenote for their weekly Wednesday meetings, where everyone showcases their work and any issues they’ve run into. The benefits have been numerous. For one, the SimPEG group has a centralized team profile — so anyone who misses a meeting can browse the week’s notes to catch up on what they missed. Curvenote also supports interactivity, so if a group member links to a Jupyter figure in the notes, it’ll stay interactive. It’s an accessible, interactive, and easy way for SimPEG to continue to build a light-weight open source community.
“There have been a couple scenarios that have been really fun to see,” said Lindsey. “There was a meeting a few weeks ago where somebody was prototyping new code, and wanted to talk about the implementation. So they linked their code directly into the group meeting notes.”
“Similarly, there are folks who have interesting research results they want to share. For example, maybe they have a figure they want to show off — and they can link to that directly in our meeting notes. It allows us to have an interesting collection of interactive scientific artifacts and ideas that different people have contributed to, but are all relevant to this one community.”
View examples of the SimPEG group notes:
- Meeting Notes: January 20, 2021 (check out this one for code snippets)
- Meeting Notes: February 24, 2021(check out this one for interactive plots)
Curvenote for Reproducible Research
Reproducibility is something we hear about a lot in science and academia. This is what allows others to verify your claims and ultimately build on your work — which is the basis of science. It may sound simple, but there’s a lot to explore in this concept.
“There are a few ideas to unpack here: for one, there’s computational reproducibility,” said Lindsey. “Meaning that if you have the right software environment and data, you should be able to reproduce the work that I’ve done.”
“But there’s another more important term, which is replicability. This is the ability for a researcher to follow the description of what you’ve proposed, but use their own implementation and ideas to get comparable results. That way you can pick up someone’s work, run with it, and build on the ideas.”
Both of these pieces are needed to push scientific discovery forwards. Researchers and scientists will share their code and notebook repositories to satisfy the reproducibility piece, and produce manuscripts that describe their methods to support the replicability side of things.
“These areas have been systematically disjointed, though we are moving towards distributing both now,” said Lindsey. “Curvenote strengthens that link, because the figure that we produce in our Jupyter Notebooks is the same thing that’s linked in the article we’re writing.”
Related to these concepts are the ideas of collaboration and accessibility; how you can make it easy for others to view, edit, and use your data and research — whether that’s across disciplines, industries or just within your own department. However, challenges can arise depending on the tools used.
“Typically in geophysics, we’re writing scientific papers in LaTeX because so many equations are involved,” said Lindsey. “It’s basically the same thing as writing Python scripts, which not everyone is comfortable with. And then usually you’re committing your work to GitHub, so any collaborators have to get set up on that too.”
But if you turn to a lighter-weight option, like Google Docs, to make it easier on your collaborators — you lose the link to reproducible content. Figures are copied and pasted in with no easy links back to the data, there’s no interactivity, and you lose the ability to write out equations.
“The Curvenote editor is really powerful because it contains all the technical tools needed to write a paper — but it also removes the barriers for collaborators,” said Lindsey. “You can bring in equations, easily create citations, reference figures, and all that. But you can also create headings that look like headings, and when you write the equation, it renders — so you can see it and make sure it’s correct.”
And of course, there’s also the option to bring in figures and other content from your Jupyter Notebooks with Curvenote’s extension.
“Curvenote fundamentally changes who can participate in scientific discussions. Someone can look at your Jupyter Notebook in Curvenote and comment on it, without actually having to open or install Jupyter,” said Lindsey. “I can just save my Jupyter Notebook to Curvenote, and then I send them a link! So I’m really excited to see what sort of opportunities this opens up within science.”
Creating Open Educational Resources
As a professor, Lindsey aims to constantly improve and supplement her teaching practices. She’s currently focused on integrating her open source and reproducibility practices into how she presents educational materials. Specifically, she’s working with a team to create interactive educational courses, and their main project is a geophysics course aimed at engineers and geologists.
“When we started this project, it was quite early on in the maturity of the open source publishing ecosystem,” said Lindsey. “So we made use of a lot of tools for Python documentation. The workflow was putting together some documents in Markdown or reStructuredText. And then we built that into a book that’s deployed on the web.”
“All of the collaboration and editing would happen on GitHub. And so there was that barrier of knowing how to version and do push/pull requests, to participate in the project.”
And it wasn’t just the team that was facing barriers with these tools. They also anticipated readers would have a harder time consuming the content, if it was published in a computational environment they weren’t familiar with.
“For the majority of the content we’re working on, computation is a part of it — we’re using it to show examples. But we’re not actually teaching computation,” said Lindsey. “For example, for the geophysics course, we want the readers to gain an understanding of different geophysical methods. But they don’t actually need to be the ones running the code or performing the analysis. They just need to have the skillset to be able to ask the right questions of other experts, like a contract geophysicist on their project.”
As well, Lindsey found the tools they were using weren’t the best for writing the course’s narrative content. These were tools built for programming, and they lacked some of the features needed for quick writing and editing.
To bridge these gaps, the team started using Curvenote to organize and produce their content.
“We’re writing out the narrative as much as we would in a paper,” said Lindsey. “But then we’re connecting that to Jupyter Notebooks so readers can run and explore different simulations, which can help them work through the content. It’s effectively pairing narrative content with exploratory notebooks, to provide an enhanced learning experience.”
And again, Curvenote’s features make it easy for the team to involve other experts.
“It can be so valuable to be able to email somebody with deep expertise in a topic and just say, hey, can you comment on this? And they can just look at that particular section and provide feedback,” said Lindsey. “With Curvenote articles, they’re always looking at the most up-to-date version, and they don’t need to download any software to access it.
Originally published at https://curvenote.com.
