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Kymberley Scroggie edited this page Sep 29, 2021 · 2 revisions

Meet The Medicine Videos

Task 3 will begin with making a short Meet the Medicine video for one of the medicine you have research as part of the E$$ENTIAL MEDICINE$ challenges. This task is designed to give you an idea of how we can visualise the data collected by the project and share it.

Please let us know which medicine you are going to work on here. The template for creating these videos and all other resources are available here.

You can find some examples of Meet the Medicine videos on our social media channels if you need some inspiration.

For the next part of this task, you'll need to split into two groups of three. One will work on the data visualisation and the other on database constructions. Please let us know which group you would like to be in here. First in, best dressed.

Data Visualisation

Those working on data visualisation are tasked with coming up with 2 additional data visualisation resources. These can be anything so get creative! Alongside it you'll need to create some instructions on how to make the visualisation such that other participants interested in data visualisation can use your resource to make their own.

Note: you don't need to look at the visualisation of all the data if you don't want to. You can select just a small element of it and focus in on that if you choose. Often this makes it much easier to do and the data can be communicated more effectively.

Database Construction

Those working on database construction are tasked with designing the structure of the database such that meet the FAIR (findable, accessible, interoperable, reusable) data principals.[1] You'll need to work out the best way to structure the raw excel data that is exported from RedCap/Qualtrics and how to convert from the raw to the structured. The structure database must still be in excel. A resource to get you started (along with the original journal article) - https://www.ands.org.au/working-with-data/fairdata.

References

[1] - Wilkinson, M. D., et al. (2016). Comment: The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 1–9.

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