Data management systems can help the environment by providing the power to analyse data that is collected regarding environmental issues. While politicians and scientists are able to assess this raw data, a data management system can organize it into a format that makes analysis simpler. Sophisticated software is able to identify trends in collected samples, before presenting it in a way that allows analysts to draw their own conclusions.
This type of technology is often used in meteorology for producing accurate weather forecasts, as their computers are powerful enough to calculate the possibility of an upcoming weather event. This is carried out by comparing current weather readings to historical algorithms.
In any data analysis for the environment, the whole process begins with some form of electronic data capture. An example of this could be a collection of sensors that monitor air quality by taking readings of harmful substances in the atmosphere. An automated system would be programmed to take data at regular intervals, and a central computer can then collate the data from a number of locations.
Sophisticated data collection systems also have ‘trigger points’ that lead to extra readings. In the above example, it could be programmed to collect information on a more frequent basis when a particular chemical reaches a high level.
A real life example of the above system was involved in the decision making process regarding the Congestion Charge in London. As the decision to charge inner-city rush hour motorists was a tricky political issue, Transport For London (the city authority) installed a number of sensors to collect pollution data.
Their intention was to show that the number of motorists was reducing because of the extra fee, and this would be based on evidence showing reducing pollution levels. Every annual report that has been published since the year that the fee was introduced (2003) shows a reduction in harmful emissions, and this research was made possible with the use of data management systems.
Clinical data management software is very similar to the software that is used for environmental analysis. Verifying the accuracy of entered data is an automated process, and the software is able to spot collected information that does not fit in with regular trends. This will then be flagged for a ‘second opinion’, which involves checking by a human user. This ensures that this data is not instantly discarded.