A common issue faced by many organisations is that information does not always flow through the system. More specifically, technical information might not be exposed to the audience to whom it should be directed. As a result, it is not uncommon for ‘wheels to be re-invented’ and for information and knowledge to be lost. Put in the context of data collection this can be a very costly, for it leads to the possibility of data collected from different surveys being ‘incompatible’ when there is no reason for it to be. Data is costly and maximum usage should be obtained from it.

To help address some of these issues, Minnerva has worked on the development of the concept of establishing common standards that are adopted for data definition and data structures. In itself, this leads to the obvious notion that some form of compatibility might exist between data from different surveys; but in turn this can means that the ‘next’ survey is cheaper to do as the systems and structures to process them should (mostly) be in place.

But an important component in making this strategy a success is to ensure that the knowledge and information backing up these systems are openly available to all players in the process. By developing an Open Documentation System that is easily accessible then all definitions, assumptions, explanations etc can be seen by all. Often the analyst working on collected data might not be sure about the definitions used in the data collection; equally the data collector might not realise the importance of how a question is asked or indeed why a question is asked. By exposing the whole process then a mechanism is provided though which these issues can be addressed.

Such a system needs to be kept up to date, but the marginal effort of doing this is far less than the cost of starting over again each time a new survey is commissioned.

(Contact: Martin Bach)