Demo data
To follow along this guide:
- Please download this unstructured demo dataset
- Unzip the folder
Violas-PhD-Project.zipand store it somewhere ready for the next steps
Getting Started
Welcome to the DataPLANT “Getting Started” guide to create your own ARC!
ARCs are structured data containers, so-called FAIR Digital Objects. ARCs help you organize your research data in a standardized way. They are based on existing standards, unifying machine and human readability!
Starting out with ARCs can be a bit overwhelming, but don’t worry! We are here to help you with the first steps. This guide will walk you through the process of creating your first ARC, adding data to it, and sharing it with collaborators.
Together we will follow a fictional researcher Viola on her journey to create her first ARC. Viola is a plant scientist and has heard about ARCs and wants to give them a try.
I recently attended a conference where my project partner introduced me to the Annotated Research Context (ARC). Intrigued by its potential, I was eager to set up my first ARC as soon as I got back to my lab. However, once there, I realized I only remembered the basic ARC structure and something about some ISA metadata. 😕
Viola’s PhD Project
Section titled Viola’s PhD Project
For my PhD I investigate the effect of cold stress on sugar metabolism in A. thaliana. I grew the plants under ambient (25 °C) and cold stress (6 °C) conditions, harvested leaves from a two-day time series experiment, extracted proteins and soluble sugars. I submitted the protein samples to a nearby core facility for proteomics. After a few weeks of iterative consultation with the facility head as well as technicians and computational biologists, I received back a wealth of raw and processed data. The extracted sugars I measured myself via a plate reader assay. From the data I produced figures using a mix of code and statistical software. Now I want to wrap everything up to publish the results in the Journal of Wonderful Plant Sciences.