5/29/2023 0 Comments Datagraph intersectionInstead, users formulate provenance graph queries directly against physical data representations (e.g., relational, XML, or RDF), leading to queries that are difficult to express and expensive to evaluate. However, while most systems record and store data and process dependencies, few provide easy-to-use and efficient approaches for accessing and querying provenance information. This information is often represented through provenance graphs, which can be used by scientists to better understand, reproduce, and verify scientific results. There exists a condensed representation of all repairs that permits computing trustable query answers.Ī key advantage of scientific workflow systems over traditional scripting approaches is their ability to automatically record data and process dependencies introduced during workflow runs. A positive result is that for conjunctive queries and full dependencies, The problem arising is that, in general,Ī database can be repaired in infinitely many ways. Is obtained by intersecting the query answers on all repaired versions of the database. Query answering in the presence of inconsistency relative to this refined repair notion. At the center of the paper is the problem of Update-based repairing is advantageous, because it allows rectifying an error within a tuple withoutĭeleting the tuple, thereby preserving other consistent values in the tuple. Unlike earlier work, we also allow tuple updatesĪs a repair primitive. Possible modifications considered are deletions and insertions of tuples. on query answering in the presence of inconsistency, the Repairing a database means bringing the database in accordance with a given set of integrity constraints by applying modifications Specifically, we study the problem of computing preferred repairs based on two different preference criteria, one based on weights and the other based on multisets, showing that in most cases it is possible to retain the same computational complexity as in the case where no preference criterion is available for exploitation. In this work, we focus on the problem of computing preferred (subset and superset) repairs for graph databases with data values, using a notion of consistency based on a set of Reg-GXPath expressions as integrity constraints. Graph databases provide an effective way to represent relationships among data, and allow processing and querying these connections efficiently. As information becomes more complex and interconnected, new types of repositories, representation languages and semantics are developed in order to be able to query and reason about it. Repairing inconsistent knowledge bases is a task that has been assessed, with great advances over several decades, from within the knowledge representation and reasoning and the database theory communities.
0 Comments
Leave a Reply. |