Last few days Brisbane and Ipswich faced devastating flood in some areas up to 21 m. This means that some houses have been more than 17 meters under water! I have been isolated in a virtual island with no utilities for more than three days, and I have been extremely lucky that flood water did not reach my house. The disaster was devastating in the scale of the Queensland state (as large as England) . One-third of Ipswich city was under water. Unfortunately, the disaster claimed 12 lives so far, but in the absence of technology, this could be far more.
In the University of Queensland, we have been dealing with negotiations of a database project which if has been done, the destructive effect of the project could be far less. The problem ( basically a data quality related issue and very hard to solve ) is the old challenge of schema matching.
There are thousands of water monitoring systems in Australia all over the land. They are all managed separately and do not have much in common in terms of IT. One might have an excel sheet filled manually, another may use a linux tool to generate a bunch of txt files from measurements, many Access databases or ORACLE and SQL Server etc. All with different designs an schemas. It is an extremely sparse sensor network system. Obviously standardising all the schemas is possible, but is out of our hands and might be a very lengthy and expensive process. So what we could do here in UQ was to develop a smart system that looks at all different thousands of databases and matches their schemas and provides a holistic unified view over everything. This is a classic problem which have been worked on (in Computer Science community not industry) for three decades.
Apparently this project did not go anywhere, but having it won and finished gracefully, all the water movements could be monitored in the matter of hours and flash floods could have been predicted and lives could have been saved!
Quality of Data 