Causality in Databases
by Alexandra Meliou, Wolfgang Gatterbauer, Joseph Y. Halpern, Christoph Koch, Katherine F. Moore, Dan Suciu
Abstract:
Provenance is often used to validate data, by verifying its origin and explaining its derivation. When searching for ``causes'' of tuples in the query results or in general observations, the analysis of lineage becomes an essential tool for providing such justifications. However, lineage can quickly grow very large, limiting its immediate use for providing intuitive explanations to the user. The formal notion of causality is a more refined concept that identifies causes for observations based on user-defined criteria, and that assigns to them gradual degrees of responsibility based on their respective contributions. In this paper, we initiate a discussion on causality in databases, give some simple definitions, and motivate this formalism through a number of example applications.
Citation:
Alexandra Meliou, Wolfgang Gatterbauer, Joseph Y. Halpern, Christoph Koch, Katherine F. Moore, and Dan Suciu, Causality in Databases, IEEE Data Engineering Bulletin, vol. 33, no. 3, 2010, pp. 59–67.
Bibtex:
@article{DBLP:journals/debu/MeliouGHKMS10,
    Abstract = {Provenance is often used to validate data, by verifying its
    origin and explaining its derivation. When searching for ``causes'' of
    tuples in the query results or in general observations, the analysis of
    lineage becomes an essential tool for providing such justifications.
    However, lineage can quickly grow very large, limiting its immediate use
    for providing intuitive explanations to the user. The formal notion of
    causality is a more refined concept that identifies causes for
    observations based on user-defined criteria, and that assigns to them
    gradual degrees of responsibility based on their respective contributions.
    In this paper, we initiate a discussion on causality in databases, give
    some simple definitions, and motivate this formalism through a number of
    example applications.},
    Author = {Alexandra Meliou and Wolfgang Gatterbauer and Joseph Y. Halpern and Christoph Koch and Katherine F. Moore and Dan Suciu},
    Journal = {IEEE Data Engineering Bulletin},
    Number = {3},
    Pages = {59-67},
    Title = {\href{http://sites.computer.org/debull/A10sept/suciu.pdf}{Causality in Databases}},
    Type = {article},
    Venue = {DEBul},
    Volume = {33},
    Year = {2010}
}