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Get the free DReW: a Reasoner for Datalog-rewritable Description Logics and DL-Programs

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The document presents DReW, a reasoner designed for efficiently handling Datalog-rewritable Description Logics and DL-programs under well-founded semantics, including its development, evaluation,
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How to fill out DReW: a Reasoner for Datalog-rewritable Description Logics and DL-Programs

01
Begin by downloading the DReW software from the official website.
02
Install the software by following the provided installation instructions.
03
Launch the DReW application after installation is complete.
04
Create or load a Datalog-rewritable ontology or DL-Program in the application.
05
Enter the necessary input parameters, such as the knowledge base and queries.
06
Configure any settings related to reasoning strategies or output preferences.
07
Run the reasoning process by clicking the appropriate 'Run' button.
08
Review the output and results presented by DReW for your queries.

Who needs DReW: a Reasoner for Datalog-rewritable Description Logics and DL-Programs?

01
Researchers in the field of artificial intelligence and knowledge representation.
02
Software developers working on applications that require reasoning over ontologies.
03
Academics involved in teaching or studying description logics and their implementations.
04
Industry professionals in fields such as semantic web, natural language processing, and data integration.
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DReW is a reasoning system designed for Datalog-rewritable Description Logics and DL-Programs, which allows for efficient querying and inference in knowledge bases.
Researchers, developers, and practitioners who utilize Datalog-rewritable Description Logics and DL-Programs in their projects are required to file DReW.
Filling out DReW involves entering relevant details about the knowledge base, specifying logical constructs, and ensuring proper syntax for the Datalog queries.
The purpose of DReW is to facilitate reasoning over knowledge bases by providing tools for inferencing, query processing, and verifying logical consistency.
Users must report the structure of the knowledge base, including predicates, rules, and any assumptions made during the reasoning process.
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