Tracing the lineage of view data in a warehousing environment
ACM Transactions on Database Systems (TODS)
The complexity of acyclic conjunctive queries
Journal of the ACM (JACM)
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Complexity results for structure-based causality
Artificial Intelligence
Why and Where: A Characterization of Data Provenance
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Causes and Explanations: A Structural-Model Approach: Part 1: Causes
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Causes and explanations in the structural-model approach: tractable cases
Artificial Intelligence
Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
What causes a system to satisfy a specification?
ACM Transactions on Computational Logic (TOCL)
On the complexity of deriving schema mappings from database instances
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the provenance of non-answers to queries over extracted data
Proceedings of the VLDB Endowment
Secondary-storage confidence computation for conjunctive queries with inequalities
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Provenance in Databases: Why, How, and Where
Foundations and Trends in Databases
Responsibility and blame: a structural-model approach
Journal of Artificial Intelligence Research
Artemis: a system for analyzing missing answers
Proceedings of the VLDB Endowment
How to ConQueR why-not questions
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Proceedings of the 4th International Workshop on Logic in Databases
Provenance for aggregate queries
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Maximizing conjunctive views in deletion propagation
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Tracing data errors with view-conditioned causality
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Sensitivity analysis and explanations for robust query evaluation in probabilistic databases
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Scrubbing query results from probabilistic databases
Proceedings of the 15th Symposium on International Database Engineering & Applications
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
A dichotomy in the complexity of deletion propagation with functional dependencies
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
DataPlay: interactive tweaking and example-driven correction of graphical database queries
Proceedings of the 25th annual ACM symposium on User interface software and technology
Maximizing Conjunctive Views in Deletion Propagation
ACM Transactions on Database Systems (TODS)
ACM Transactions on Database Systems (TODS)
Compact explanation of data fusion decisions
Proceedings of the 22nd international conference on World Wide Web
Data debugging with continuous testing
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
Wondering why data are missing from query results?: ask conseil why-not
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Causality and responsibility: probabilistic queries revisited in uncertain databases
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Multi-tuple deletion propagation: approximations and complexity
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
An answer to a query has a well-defined lineage expression (alternatively called how-provenance) that explains how the answer was derived. Recent work has also shown how to compute the lineage of a non-answer to a query. However, the cause of an answer or non-answer is a more subtle notion and consists, in general, of only a fragment of the lineage. In this paper, we adapt Halpern, Pearl, and Chockler's recent definitions of causality and responsibility to define the causes of answers and non-answers to queries, and their degree of responsibility. Responsibility captures the notion of degree of causality and serves to rank potentially many causes by their relative contributions to the effect. Then, we study the complexity of computing causes and responsibilities for conjunctive queries. It is known that computing causes is NP-complete in general. Our first main result shows that all causes to conjunctive queries can be computed by a relational query which may involve negation. Thus, causality can be computed in PTIME, and very efficiently so. Next, we study computing responsibility. Here, we prove that the complexity depends on the conjunctive query and demonstrate a dichotomy between PTIME and NP-complete cases. For the PTIME cases, we give a non-trivial algorithm, consisting of a reduction to the max-flow computation problem. Finally, we prove that, even when it is in PTIME, responsibility is complete for LOGSPACE, implying that, unlike causality, it cannot be computed by a relational query.