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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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Scalable End User Access to Big Data MCQs | Page 7 of 14

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Q61.
In the context of complex queries, what is the importance of providing a textual query interface for technically versed users?

a.

It simplifies query construction for non-technical users.

b.

It prevents users from switching between different query views.

c.

It offers context-sensitive completion and navigation support.

d.

It restricts users to formal query syntax like W3C SPARQL.

Discuss
Answer: (c).It offers context-sensitive completion and navigation support. Explanation:The importance of providing a textual query interface with context-sensitive completion and navigation support for technically versed users dealing with complex queries.
Q62.
Why is it important to support "on the fly" extension of the ontology during query formulation?

a.

Ontologies are always complete and cover all domain vocabularies.

b.

Users cannot change the ontology once it's established.

c.

To adapt to changing vocabularies and cater to omissions in the ontology.

d.

On-the-fly extensions are only needed for non-technical users.

Discuss
Answer: (c).To adapt to changing vocabularies and cater to omissions in the ontology. Explanation:The importance of supporting on-the-fly extension of the ontology to adapt to changing vocabularies and cater to omissions.
Q63.
How can users relate new vocabulary to existing ontology terms when extending the ontology during query formulation?

a.

They cannot relate new vocabulary to existing terms.

b.

They must consult an IT expert for such relations.

c.

By using advanced tools and methodologies from ontology alignment.

d.

By avoiding any changes to the ontology's vocabulary.

Discuss
Answer: (c).By using advanced tools and methodologies from ontology alignment. Explanation:Users can relate new vocabulary to existing ontology terms by using advanced tools and methodologies from ontology alignment.
Q64.
How can users relate new vocabulary to existing ontology terms when extending the ontology during query formulation?What kind of query interface views should ideally be provided to users dealing with complex queries?

a.

They cannot relate new vocabulary to existing terms.Only a textual query interface.

b.

They must consult an IT expert for such relations.Only a diagrammatic query interface.

c.

By using advanced tools and methodologies from ontology alignment.Both a textual and a diagrammatic query interface.

d.

By avoiding any changes to the ontology's vocabulary.Users should not switch between query views.

Discuss
Answer: (c).By using advanced tools and methodologies from ontology alignment.Both a textual and a diagrammatic query interface. Explanation:Users can relate new vocabulary to existing ontology terms by using advanced tools and methodologies from ontology alignment.Both textual and diagrammatic query interface views should be provided, and users should ideally be able to switch between them.
Q65.
What is the purpose of the ontology in the OBDA architecture?

a.

To replace the need for data sources.

b.

To provide a global schema for data sources.

c.

To create a formal query language for users.

d.

To manage large sets of mappings.

Discuss
Answer: (b).To provide a global schema for data sources. Explanation:The ontology in the OBDA architecture acts as a "global schema" onto which the schemas of various data sources can be mapped.
Q66.
Why is developing ontologies from scratch considered expensive in OBDA?

a.

It requires advanced technical skills.

b.

It is a time-consuming process.

c.

It results in incoherent ontologies.

d.

It leads to the exclusion of data sources.

Discuss
Answer: (b).It is a time-consuming process. Explanation:Developing ontologies from scratch is considered expensive because it is a time-consuming process.
Q67.
How can ontologies evolve in OBDA systems?

a.

By removing vocabulary used in user queries.

b.

By eliminating axioms that are no longer needed.

c.

By remaining static and unchanging.

d.

By incorporating new vocabulary required in user queries.

Discuss
Answer: (d).By incorporating new vocabulary required in user queries. Explanation:In OBDA systems, ontologies can evolve by incorporating new vocabulary required in user queries.
Q68.
What is one of the challenges in managing large, evolving sets of mappings in OBDA?

a.

Finding suitable initial ontologies.

b.

Generating mappings from database schemata.

c.

Ensuring coherent addition of vocabulary to the ontology.

d.

Using interactive ontology editors.

Discuss
Answer: (c).Ensuring coherent addition of vocabulary to the ontology. Explanation:One of the challenges in managing large, evolving sets of mappings in OBDA is ensuring coherent addition of vocabulary to the ontology.
Q69.
What do ontology management tools like Protégé and NeOn primarily support?

a.

Schema mappings.

b.

Query formulation.

c.

Complex ontologies.

d.

Database schemata.

Discuss
Answer: (c).Complex ontologies. Explanation:Ontology management tools like Protégé and NeOn primarily support the construction and maintenance of complex ontologies.
Q70.
What is the goal of comparing schema mapping languages in research?

a.

To identify the most complex mapping language.

b.

To determine the optimal mapping language for all scenarios.

c.

To characterize mapping languages in terms of expressive power and complexity.

d.

To create a new schema mapping language.

Discuss
Answer: (c).To characterize mapping languages in terms of expressive power and complexity. Explanation:The goal of comparing schema mapping languages in research is to characterize mapping languages in terms of expressive power and complexity.
Page 7 of 14

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