Projects:2020s2-7511 SQL Database for Experimental Metadata
Abstract here
Contents
Introduction
In earlier times, all the metadata about each experiment would be kept in laboratory notebooks. This method is reaching the end of its useful lifetime. There is too much data, and physical notebooks are not searchable by machine. If a later researcher studies the data, how are they going to know what it means? What sort of experiment was carried out? Who did the work? Where was it done? What were the objectives of the experiment? What code should be executed in order to process the data? The purpose of this project is to develop a relational database, which can be interrogated using Structures Query Language (SQL). The data will need to be harvested, re-formatted and checked using a scripting language. We are proposing the use of the Python3 programming language. Statistical post-processing of the data can be carried out in several languages, including MATLAB, Python3, or the “R” programming language. There are number of Open-Source SQL data base packages for the Linux operating system, including Bee Keeper, Libre Office BASE, and Keri. Python3 will run under Linux. The early parts of the project would involve programming in a Linux environment. In order to make the work realistic, students will measure a series of RC ladder circuits, using a Picoscope. This will generate large amounts of accurate sampled data, which will then need to be classified and processed. The experimental part of the project is safe and could be carried out off campus, in Adelaide. Remote students, outside of Adelaide, would have to concentrate on the software aspects of the project
Project team
Project students
- Ruoyun Zhou
- Zeyu Fu
- Junwen Zheng
Supervisors
- Dr Andrew Allison
Advisors
Objectives
Set of objectives
Background
Topic 1
Method
Results
Conclusion
References
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[2] ...