In a commercial world, the financial costs associated with establishing a data provision system have to be balanced against the value derived from the data supplied by the system. However, establishing the value of data in financial terms is not straightforward and so such comparisons are difficult.
The trading of environmental data is a rapidly growing industry. For some products the market is quite mature. Weather forecasts and topographic maps are two examples of information products that are regularly sold to a consuming public. In these cases, data providers, data processors, information packagers and information users have been able to reach agreement on the value (in cost and pricing terms) of the data that has gone into producing the final product.
For many other data products, however, achieving acceptable valuation at one such level, let alone at all levels, has proved particularly difficult. The result of such uncertainty is that data and information users are finding it increasingly difficult to identify reliable least-cost solutions to the purchase of those data necessary for compliance with legal and regulatory obligations, for under-pinning decision-making systems, and for risk management.
At the other end of the chain, data originators are unsure as to what costs can, or should, be recovered through data sales, and what overhead costs should be allocated to particular data products or to particular types of data user. This is sometimes the case with public funded agencies who recognise that their data, collected to meet statutory requirements, has high value to both scientific and commercial companies.
Despite these difficulties, general and specialist environmental data and information products are regularly traded. It is on the basis of this experience that ENVALDAT seeks to build. Valuation methodologies, whether they be formal or informal, are already being employed. It is the objective of ENVALDAT to consolidate and evaluate this experience, and from this consolidate present practice on valuing data for wider circulation and use.