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Active Integrity Constraints for Multi-context Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10024))

Abstract

We introduce a formalism to couple integrity constraints over general-purpose knowledge bases with actions that can be executed to restore consistency. This formalism generalizes active integrity constraints over databases. In the more general setting of multi-context systems, adding repair suggestions to integrity constraints allows defining simple iterative algorithms to find all possible grounded repairs – repairs for the global system that follow the suggestions given by the actions in the individual rules. We apply our methodology to ontologies, and show that it can express most relevant types of integrity constraints in this domain.

This work was supported by the Danish Council for Independent Research, Natural Sciences, grant DFF-1323-00247, and by FCT/MCTES/PIDDAC under centre grant to BioISI (Centre Reference: UID/MULTI/04046/2013).

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Notes

  1. 1.

    In [16], existentially quantified variables can also occur in negative literals. This was not discussed in subsequent work, and we ignore it for simplicity of presentation.

  2. 2.

    Technically, \(P_p\) is a relational element of \(C_{i_p}\): it can include variables, which when instantiated yield elements of \(\bigcup \mathsf {BS}_{i_p}\) – see [4] for details.

  3. 3.

    For the sake of presentation, we simplified the management function, which in the original work is allowed to return several possible effects for each action.

  4. 4.

    This semantics is slightly changed from that of [14], in order to make some aspects of our example more realistic.

  5. 5.

    There is also a notion of repair tree for databases in [9], but it relies on the ability of inferring heads of AICs automatically, which does not exist in the MCS setting.

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Cruz-Filipe, L., Gaspar, G., Nunes, I., Schneider-Kamp, P. (2016). Active Integrity Constraints for Multi-context Systems. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-49004-5_7

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