Data Fusion, from a logic perspective with a view to implementation
Résumé
The need to combine data from different sources has become increasingly important and is likely to be so in our increasingly networked world. There are many difficulties that must be overcome to ensure the efficient and, to the es=xtent possible, the automated integration of different data sources. Although different goals and constraints may apply to the problem, not infrequently data sources are combined to achieve data of better quality. The process is generall called 'data fusion', other terms may also be applied to the same problem, including 'data integration' and 'data conflation'. For example, the term fusion is used by the image community to embrace the problem of sensor fusion, or by the database community for parts of the interoperability ^roblem. The logic community uses it for knowledge fusion.
This special issue, which takes up a set of papers presented at an international workshop in April 2001 in Quebec City, addresses the problem of data fusion from such a wide perspective, that is, including a range of tributary problems and a range of disciplines. The workshop was supported by both European 5th framework projects and several Canadian GEOIDE projects.