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Welcome to the Scalable End User Access to Big Data MCQs Page

Dive deep into the fascinating world of Scalable End User Access to Big Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Scalable End User Access to Big Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Scalable End User Access to Big Data, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Big Data Computing.

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Check out the MCQs below to embark on an enriching journey through Scalable End User Access to Big Data. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Scalable End User Access to Big Data. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Scalable End User Access to Big Data MCQs | Page 6 of 14

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Discuss
Answer: (c).When a "join" operation between information about several objects is required. Explanation:Faceted search faces limitations when complex operations like "join" between information about multiple objects are needed.
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Answer: (a).They restrict queries to a single concept term. Explanation:Ontology development tools like Protégé typically allow query formulation using ontology terms but are limited to single concept term queries.
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Answer: (c).To enable users to gradually refine queries by selecting concepts and adding relationships. Explanation:A "query by navigation" interface allows users to refine queries by selecting concepts and adding relationships, making it user-friendly.
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Answer: (d).It allows for more advanced query capabilities. Explanation:Extending faceted search in ontology-based systems enables advanced query capabilities like joins, aggregation, and specifying the absence of information.
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Answer: (d).It leverages the graph-based organization of information and allows iterative narrowing of the query scope. Explanation:The navigational approach in query by navigation uses the graph-based organization of information to allow users to iteratively narrow the query scope.
Q56.
What is a potential application of query by navigation in the Semantic Web domain?
Discuss
Answer: (c).Textual semantic data browsers. Explanation:Query by navigation has been applied in the Semantic Web domain as textual semantic data browsers to facilitate user-friendly exploration of data.
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Answer: (c).They struggle to provide an overview and balance information visualization. Explanation:Diagrammatic approaches and textual data browsers face challenges in providing an overview and balancing information visualization with complex ontologies.
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Answer: (b).Because the ontology accurately describes all domain details. Explanation:End-users may find it challenging to access data because complex ontologies accurately describe all domain details, which can be more intricate than users think in their daily work.
Q59.
What is a necessary feature of a query formulation tool to help users understand complex ontologies?
Discuss
Answer: (d).Supporting searching by name for properties and concepts. Explanation:To help users understand complex ontologies, a query formulation tool should allow searching by name for properties and concepts that users know must be available in the ontology.
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Answer: (b).The ontology may define resolution differently, considering multiple image sensors. Explanation:The ontology may define resolution in a complex manner, considering multiple image sensors, which can make it challenging for users to formulate the query.

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