Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The preparation of existing real-world datasets for publication as  high-quality semantic b data is a complex task that requires the  concerted execution of a variety of processing steps using a range of  different tools. Faced with both changing input data and evolving  requirements on the produced output,  face a significant  engineering task  for schema and data transformation.  argue that to achieve a robust and flexible transformation process, a high-level  declarative description  is needed, that can be used to drive the entire tool chain.  have implemented this idea for the deployment of  ontology-based data access  (OBDA) solutions, where semantically annotated views that integrate  multiple data sources on different formats are created, based on an  ontology and a collection of mappings. Furthermore,  exemplify our  approach and show how a single declarative description helps to  orchestrate a complete tool chain, beginning with the download of  datasets, and through to the installation of the datasets for a variety  of tool applications, including data and query transformation processes  and reasoning services. Our case study is based on several publicly  available tabular and relational datasets concerning the operations of  the petroleum industry in Norway.  include a discussion of the  relative performance of the used tools on our case study, and an  overview of lessons learnt for practical deployment of OBDA on  real-world datasets.
['Martin G. Skjæveland', 'Martin Giese', 'Dag Hovland', 'Espen H. Lian', 'Arild Waaler']
I am writing a research paper on a idea Engineering ontology-based access to real-world data sources
[{"from": "human", "value": "I am writing a research paper on a idea Engineering ontology-based access to real-world data sources"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The preparation of existing real-world datasets for publication as  high-quality semantic b data is a complex task that requires the  concerted execution of a variety of processing steps using a range of  different tools. Faced with both changing input data and evolving  requirements on the produced output,  face a significant  engineering task  for schema and data transformation.  argue that to achieve a robust and flexible transformation process, a high-level  declarative description  is needed, that can be used to drive the entire tool chain.  have implemented this idea for the deployment of  ontology-based data access  (OBDA) solutions, where semantically annotated views that integrate  multiple data sources on different formats are created, based on an  ontology and a collection of mappings. Furthermore,  exemplify our  approach and show how a single declarative description helps to  orchestrate a complete tool chain, beginning with the download of  datasets, and through to the installation of the datasets for a variety  of tool applications, including data and query transformation processes  and reasoning services. Our case study is based on several publicly  available tabular and relational datasets concerning the operations of  the petroleum industry in Norway.  include a discussion of the  relative performance of the used tools on our case study, and an  overview of lessons learnt for practical deployment of OBDA on  real-world datasets."}]