Q. How does the problem of data access become more challenging in Big Data scenarios?

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Q. What is the goal of the Optique project regarding data access for Big Data?

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Q. What does OBDA stand for in the context of data access?

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Q. How does OBDA address the bottleneck in query translation for end-users?

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Q. What challenges do end-users typically face when dealing with Big Data?

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Q. How does the involvement of IT experts affect the turnaround time for information requests?

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Q. What dimensions of data make data access challenging in Big Data scenarios?

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Q. What is the main idea behind ontology-based data access (OBDA)?

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Q. Who typically formulates queries using the terms defined by the ontology in OBDA?

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Q. What does OBDA stand for in the context of data access?

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Q. What is one advantage of using OBDA for end-user data access?

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Q. What does the ontology in OBDA help achieve?

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Q. How does OBDA make the relationship between ontology concepts and relational data explicit?

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Q. How does an ontology help in query answering in OBDA?

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Q. What does the term "GAV" stand for in the context of OBDA mappings?

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Q. How are mappings used to connect ontology vocabulary with the database schema?

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Q. What is a prerequisite for OBDA technology?

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Q. Why is end-user acceptance important in the context of OBDA?

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Q. What feature is proposed to improve usability for non-technical users in OBDA systems?

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Q. What does the proposed architecture aim to achieve?

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