Abstract

In many application areas like e-science and data-warehousing detailed
information about the origin of data is required. This kind of information is often referred
to as data provenance or data lineage. The provenance of a data item includes
information about the processes and source data items that lead to its creation and
current representation. The diversity of data representation models and application
domains has lead to a number of more or less formal definitions of provenance. Most
of them are limited to a special application domain, data representation model or data
processing facility. Not surprisingly, the associated implementations are also restricted
to some application domain and depend on a special data model. In this paper we give
a survey of data provenance models and prototypes, present a general categorization
scheme for provenance models and use this categorization scheme to study the properties
of the existing approaches. This categorization enables us to distinguish between
different kinds of provenance information and could lead to a better understanding of
provenance in general. Besides the categorization of provenance types, it is important
to include the storage, transformation and query requirements for the different kinds of
provenance information and application domains in our considerations. The analysis
of existing approaches will assist us in revealing open research problems in the area of
data provenance.