Abstract: The integration of heterogeneous systems is still one of the main challenges in the area of data management. Its importance is based on the trend towards heterogeneous system environments, where the different levels of integration approaches result in a large number of different integration systems. Due to these proprietary solutions and the lack of a standard for data-intensive integration processes, the model-driven development— following the paradigm of the Model-Driven Architecture (MDA)—is advantageous. This paper contributes to the model-driven development of complex and data-intensive integration processes. In addition, we illustrate optimization possibilities offered by this model-driven approach and discuss first evaluati...
As of today, most of the data processing systems have to deal with a large amount of data originated...
The increasing need to exchange information in joint operations has resulted in interoperability sta...
Information required for decision making is generally scattered across disparate data sources. To ga...
Due to the changing scope of data management from centrally stored data towards the management of di...
As a result of the changing scope of data management towards the management of highly distributed sy...
The integration of different development activities and artifacts into a single coherent system is a...
Model Driven Data Integration is a data integration approach that proactively incorporates and utili...
Increased use of data is influencing the existing practices in the engineering domain,including that...
New methods and techniques are needed to reduce the very costly integration and test effort (in term...
AbstractNew methods and techniques are needed to reduce the very costly integration and test effort ...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
AbstractComplex systems, Pattern-based Systems Engineering, and Model-based Systems Engineering are ...
This work presents a few considerations on a project aimed at addressing the complexity of multi-lay...
Model Driven Data Integration is a data integration approach that proactively incorporates and utili...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
As of today, most of the data processing systems have to deal with a large amount of data originated...
The increasing need to exchange information in joint operations has resulted in interoperability sta...
Information required for decision making is generally scattered across disparate data sources. To ga...
Due to the changing scope of data management from centrally stored data towards the management of di...
As a result of the changing scope of data management towards the management of highly distributed sy...
The integration of different development activities and artifacts into a single coherent system is a...
Model Driven Data Integration is a data integration approach that proactively incorporates and utili...
Increased use of data is influencing the existing practices in the engineering domain,including that...
New methods and techniques are needed to reduce the very costly integration and test effort (in term...
AbstractNew methods and techniques are needed to reduce the very costly integration and test effort ...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
AbstractComplex systems, Pattern-based Systems Engineering, and Model-based Systems Engineering are ...
This work presents a few considerations on a project aimed at addressing the complexity of multi-lay...
Model Driven Data Integration is a data integration approach that proactively incorporates and utili...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
As of today, most of the data processing systems have to deal with a large amount of data originated...
The increasing need to exchange information in joint operations has resulted in interoperability sta...
Information required for decision making is generally scattered across disparate data sources. To ga...