Entity Identity Reconciliation based Big Data Federation A MDE approach

“Information is power” is a sentence attributed to Francis Bacon that acquired a high important in the current era of the information. However, too much information can be a negative aspect. The term of “Infoxication” refers to the difficulty a person can have understanding an issue and making decisions that can be caused by the presence of too much information. With the increasing of relevance of open data and big database, the application of mechanisms and solutions to manage information is critical. This paper introduces the problem of unique identification and data reconciliation and offers a discussion about how to solve this problem in big and open data environment. The problem of data reconciliation in multiple databases and the unique identification of entities is not a new problem, but, how effective are classical mechanisms in the new internet environment? In this paper a solution based on model-driven engineering and virtual graph is presented in order to improve the processing of information in big open repositories. The paper illustrates the idea with a real example for the right exploitation of heritage information in the south of Spain.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-

Entity Identity Reconciliation based Big Data Federation-A MDE approach

“Information is power” is a sentence attributed to Francis Bacon that acquired a high important in the current era of the information. However, too much information can be a negative aspect. The term of “Infoxication” refers to the difficulty a person can have understanding an issue and making decisions that can be caused by the presence of too much information. With the increasing of relevance of open data and big database, the application of mechanisms and solutions to manage information is critical. This paper introduces the problem of unique identification and data reconciliation and offers a discussion about how to solve this problem in big and open data environment. The problem of data reconciliation in multiple databases and the unique identification of entities is not a new problem, but, how effective are classical mechanisms in the new internet environment? In this paper a solution based on model-driven engineering and virtual graph is presented in order to improve the processing of information in big open repositories. The paper illustrates the idea with a real example for the right exploitation of heritage information in the south of Spain

Configuration management for models : generic methods for model comparison and model co-evolution

It is an undeniable fact that software plays an important role in our lives. We use the software to play our music, to check our e-mail, or even to help us drive our car. Thus, the quality of software directly influences the quality of our lives. However, the traditional Software Engineering paradigm is not able to cope with the increasing demands in quantity and quality of produced software. Thus, a new paradigm of Model Driven Software Engineering (MDSE) is quickly gaining ground. MDSE promises to solve some of the problems of traditional Software Engineering (SE) by raising the level of abstraction. Thus, MDSE proposes the use of models and model transformations, instead of textual program files used in traditional SE, as means of producing software. The models are usually graph-based, and are built by using graphical notations – i.e. the models are represented diagrammatically. The advantages of using graphical models over text files are numerous, for example it is usually easier to deduce the relations between different model elements in their diagrammatic form, thus reducing the possibility of defects during the production of the software. Furthermore, formal model transformations can be used to produce different kinds of artifacts from models in all stages of software production. For example, artifacts that can be used as input for model checkers or simulation tools can be produced. This enables the checking or simulation of software products in the early phases of development, which further reduces the probability of defects in the final software product. However, methods and techniques to support MDSE are still not mature enough. In particular methods and techniques for model configuration management (MCM) are still in development, and no generic MCM system exists. In this thesis, I describe my research which was focused on developing methods and techniques to support generic model configuration management. In particular, during my research, I focused on developing methods and techniques for supporting model evolution and model co-evolution. Described methods and techniques are generic and are suitable for a state-based approach to model configuration management. In order to support the model evolution, I developed methods for the representation, calculation, and visualization of state-based model differences. Unlike in previously published research, where these three aspects of model differences are dealt with in separation, in my research all these three aspects are integrated. Thus, the result of model differences calculation algorithm is in the format which is described by my research on model differences representation. The same representation format of model differences is used as a basis of my approach to differences visualization. It is important to notice that the developed representation format for model differences is metamodel independent, and thus is generic, i.e., it can be used to represent differences between all graph-based models. Model co-evolution is a term that describes the problem of adapting models when their metamodels evolve. My solution to this problem has three steps. In the first step a special metamodel MMfMM is introduced. Unlike in traditional approaches, where metamodels are represented as instances of a metametamodel, in my approach the metamodels are represented by models which are instances of an MMfMM. In the second step, since metamodels are represented by models, previously defined methods and techniques for model evolution are reused to represent and calculate the metamodel differences. In the final step I define an algorithm that uses the calculated metamodel differences to adapt models conforming to the evolved metamodel. In order to validate my approaches to model evolution and model co-evolution, I have developed a tool for comparing models and visualizing resulting differences, and a tool for model co-evolution. Moreover, I have developed a method to compare tools for model comparison, and using this method I have conducted a series of experiments in which I compared the tool I developed to an industrial tool called EMFCompare. The results of these experiments are also presented in the thesis. Furthermore, in order to validate my tool and approach to model co-evolution, I have also specified and conducted several experiments. The results of these experiments are also presented in the thesis

Novel processes for smart grid information exchange and knowledge representation using the IEC common information model

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The IEC Common Information Model (CIM) is of central importance in enabling smart grid interoperability. Its continual development aims to meet the needs of the smart grid for semantic understanding and knowledge representation for a widening domain of resources and processes. With smart grid evolution the importance of information and data management has become an increasingly pressing issue not only because far more data is being generated using modern sensing, control and measuring devices but also because information is now becoming recognised as the ‘integral component’ that facilitates the optimal flexibility required of the smart grid. This thesis looks at the impacts of CIM implementation upon the landscape of smart grid issues and presents research from within National Grid contributing to three key areas in support of further CIM deployment. Taking the issue of Enterprise Information Management first, an information management framework is presented for CIM deployment at National Grid. Following this the development and demonstration of a novel secure cloud computing platform to handle such information is described. Power system application (PSA) models of the grid are partial knowledge representations of a shared reality. To develop the completeness of our understanding of this reality it is necessary to combine these representations. The second research contribution reports on a novel methodology for a CIM-based model repository to align PSA representations and provide a knowledge resource for building utility business intelligence of the grid. The third contribution addresses the need for greater integration of information relating to energy storage, an essential aspect of smart energy management. It presents the strategic rationale for integrated energy modeling and a novel extension to the existing CIM standards for modeling grid-scale energy storage. Significantly, this work has already contributed to a larger body of work on modeling Distributed Energy Resources currently under development at the Electric Power Research Institute (EPRI) in the USA.Dr. Martin Bradley on behalf of National Grid Plc. and the Engineering and Physical Sciences Research Council (EPSRC

Security Risk Assessments: Modeling and Risk Level Propagation

Security risk assessment is an important task in systems engineering. It is used to derive security requirements for a secure system design and to evaluate design alternatives as well as vulnerabilities. Security risk assessment is also a complex and interdisciplinary task, where experts from the application domain and the security domain have to collaborate and understand each other. Automated and tool-supported approaches are desired to help manage the complexity. However, the models used for system engineering usually focus on functional behavior and lack security-related aspects. Therefore, we present our modeling approach that alleviates communication between the involved experts and features steps of computer-aided modeling to achieve consistency and avoid omission errors. We demonstrate our approach with an example. We also describe how to model impact rating and attack feasibility estimation in a modular fashion, along with the propagation and aggregation of these estimations through the model. As a result, experts can make local decisions or changes in the model, which in turn provides the impact of these decisions or changes on the overall risk profile. Finally, we discuss the advantages of our model-based method