The aim of this project is to create a web service and downloadable executable that pre-processes csv files providing a quick summary of the data and pointing out potential errors in the original data.
We are following on from a previous project which pre-processes csv files creating a html file and displays a simple summary to a web page and detect some errors in the original data file.
The proposed system will be an extended version of the prototype which will permit a larger range of data types, provide more sophisticated summaries.
A page will be generated which summarised the data collected including averages, mode median etc. The page will also notify the user of any formatting errors in the data so that either the user can correct the file or the program will output a corrected file.
The user is also able to make changes by making changes to data type classifications, create templates for future use and generate graphs and figures using the data. The user can then check whether the experiment was incorrectly carried out and if the data file is consistently formatted before commencing further modelling and processing using the data file. It will also allow users to interact with the web page as well such as giving specifics about their data and downloading an executable program to process larger files.
Team Members from Computer Science
Alastair Chin, Jordan Hedges, Leighton Lilford, Alastair Mory, Kieran Richards, Jan Villanueva
The project is supervised by A/Prof Tim French.
A/P Adrian Keating and Melinda Hodkiewicz are the motivators for the project.