This repository gives you an example on how you can structure your research project, from the data analysis all the way to the final version of the manuscript or a presentation.
Find out more on how to get started here.
The overarching aim is:
- to make our research more reproducible so other researchers can re-use our code, data;
- to speed up review process (e.g., avoiding that we use different tools which are not 100% compatible, Google Form, Word, etc)
- to minimise errors (e.g., copying and pasting values in Word tables and PowerPoint)
For this purpose I have tried to leverage the best tools that there are currently out there (at least in my opinion) and I have put together this repository which could be used as template/starting point to ensure that we follow a more structured approach in research. It leverages the power of Python, R and Latex, to streamline the data analysis and publication process.
This project is still in Beta version, hence it is far from being complete and the file structure may soon change. Please feel free to contribute.
The directory is divided in sub-folders. Each of which contains the relative source code. Just clone this repository on your computer or Fork it on GitHub
The objective of this folder is not to replace the database, but instead to share only some of the database data with other researchers. Data should only contain the .csv files that you want to share publicly.
It SHOULD NOT containc identifiable data.
Please save your source code in the code folder. Currently you can find an example of a Python, R and Jupiter notebook in this folder.
Figures and Tables to be used in the manuscript should be saved in the respective folder
manuscript/src/figuresormanuscript/src/tables
Once you have finalized your research, your data should then be saved in Dryad: Dryad is an open-source, research data curation and publication platform. Datasets published in Dryad receive a citation and can be versioned at any time. You can upload your data on Dryad by copy and pasting in their system the GitHub URL.
If your code needs to connect to a database or a server please make sure the username and password are not saved in plain text in your code. I keep my password saved in a file called secret.py and added this file to .gitignore so this file is not synced to the GitHub repos. And then import this file at the beginning of my main.py file.
Make sure you save the data you imported from the database in the Data folder so other researchers can import the raw data if they want to reproduce your results. Alteratively write a script which pulls the data from Dryad.
The manuscript contains all the Latex files needed to generate your manuscript and your presentation. The main source files are located in the manuscript/src.
- main.tex is your manuscript source file. The final PDF can be found here.
- Presentation.tex contains the code to generate your presentation. The final PDF can be found here.
main.tex is the source file that your Latex compiler will use to generate the paper. However, in order to keep the code cleaner, the main sections of the paper are all located in the sections. In this way you will experience less merging issues when two or more people are working on the same manuscript.
Just edit the text in the relative Latex file (e.g., introduction, methodology, etc.) and you should be ready to go. No need to change any other file.
Just copy a section file (e.g., introduction.tex) paste it in the same directory. Rename the pasted file (e.g. discussion.tex) and add this file to main.tex.
See the boilerplate code in results.tex.
For your convenience I have already included the Elsevier Latex template at the beginning of the main.tex. Feel free to change that.
If you choose to use the Elsevier template you can change the bibliography style in the mypreamble.sty file.
Alternatively you can find great resources on the Overleaf Tutorial website or on Latex wikibooks.
Python or R for the data analysis, but you can also use other programming languages or tools such as Energy Plus. How to get you started with this tools is outside the scope of this repository, but you can find a million videos on YouTube or tutorials on the Internet.
I would highly recommend you using an IDE to write code, see more below.
Latex IDE and compiler installed locally on your machine. I recommend using a PyCharm plugin called TeXiFy IDEA as IDE and miktex as Latex compiler
Alternatively you can push your code to Overleaf using git and only use Overleaf. I would discourage you from doing this! Overleaf should only be used for the review.
If you are not sure about which database to choose and you are a researcher, in 80-90% of the cases you should be fine with an SQL database, alternatively you may want to use a Time Series database.
You may want to take advantage of the power of IDEs. Well as you all know my preferred choice are JET Brains IDEs and for Python and R I would recommend using PyCharm. Alternatives are:
Always think about the future, if you think you may start doing a bit of Web development, App development (Android, Apple) or Software. The best options are PyCharm or VS Code.
I personally think you should not use Jupiter Notebook, but feel free to use it if you like it.
You should install git on your computer. And have GitHub or GitLab account
- Federico Tartarini - Initial work
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE.md file for details