adplus-dvertising
frame-decoration

Question

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.

Posted under Big Data Computing

Answer: (b).It is a time-consuming process. Explanation:Developing ontologies from scratch is considered expensive because it is a time-consuming process.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. Why is developing ontologies from scratch considered expensive in OBDA?

Similar Questions

Discover Related MCQs

Q. How can ontologies evolve in OBDA systems?

Q. What is one of the challenges in managing large, evolving sets of mappings in OBDA?

Q. What do ontology management tools like Protégé and NeOn primarily support?

Q. What is the goal of comparing schema mapping languages in research?

Q. What is one of the main aspects considered when comparing schema mappings in research?

Q. What is one of the challenges in mapping management within the realm of OBDA?

Q. Why might mappings in OBDA systems become obsolete?

Q. What is the goal of mapping simplification in the context of OBDA?

Q. How can the problem of accommodating new vocabulary or knowledge from new data sources be addressed in OBDA?

Q. What is the goal of defining a specific language for querying schema mappings?

Q. What is the purpose of designing a query language over a mapping meta-model?

Q. How can reasoning techniques based on a mapping meta-model support the evolution of schema mappings?

Q. What is the main goal of a reasoning system that monitors changes and reactions to them in schema mappings?

Q. What is the primary motivation for using query rewriting techniques in the context of OBDA?How do succinct query expressions, such as nonrecursive Datalog programs, compare to unions of conjunctive queries (UCQs) in terms of query rewriting speed?

Q. What is the primary motivation for using query rewriting techniques in the context of OBDA?

Q. What benefits can be achieved through load-time precomputation of inferences in OBDA systems?

Q. What role does the form of the SQL query play in achieving high performance in the context of query rewriting into SQL?

Q. Which system served as a platform for the implementation of epistemic-query answering techniques in the context of Description Logic (DL) ontologies?

Q. Which prototype implemented resolution-based query rewriting techniques?

Q. Which system focused on the exploitation of efficient rewriting techniques, SQO optimization, and the generation of efficient SQL queries?