This module will teach you the skills and concepts for effective Data Management. Simply put, Data Management is about taking care of your data so that your work isn’t hindered by data issues. Your data is effectively organised and stored so you can access and understand it with ease. Effective data management goes hand in hand with effective data sharing, if you organise data well for your own use, collaborators and other users of the data will also benefit.
- Devise and apply a logical file naming scheme to a data set
- Store data in an open, readable, logically structured format when possible
- Understand a range of data storage options and their advantages and disadvantages
- Create metadata for scientific data that follows common standards
- Understand the prupose of meta data; how it aids in discoverability and describing data
- Understand issues around data sensitivity, and how to mitigate and manage these issues
- Write a data management plan outlining data collection processes and naming conventions
Learn the importance of data management and how to write a data management plan for your project.
- Lecture: Introduction
- Activity: Write a Data Management Plan
- Lecture: Organising Your Project
- Lecture: Security, Protection and Privacy
File Naming and Organisation
Given a raw data set, come up with an improved structure and file naming strategy. Sketch or create an example of this strategy and discuss its benefits with an assessor.
Create a comprehensive ReadMe file which gives the reader a clear understanding of the project purpose, structure, run requirements, expected output and licence.
That’s So Meta
Using the same scenario as Badge 2, create meta data using [STANDARD X]
Intellectual and Ethical Data Issues
Using same scenario as Badges 2 and 3, identify how the raw data might need to be collected (anonymization), stored for a length of time/destroyed after study as well as limitations around sharing for IP reasons.