An MDA Approach for the Evolution of Data Warehouses

2015 ◽  
Vol 7 (3) ◽  
pp. 65-89 ◽  
Author(s):  
Said Taktak ◽  
Saleh Alshomrani ◽  
Jamel Feki ◽  
Gilles Zurfluh
Keyword(s):  
Data Warehouse ◽  
Research Topic ◽  
Multidimensional Data ◽  
Model Driven ◽  
Transformation Rules ◽  
Challenging Research ◽  
Operational Information ◽  
Evolving Context ◽  
View Transformation ◽  
Evolution Approach

Modeling and data warehousing have been considered, for more than one decade, as a new challenging research topic for which different approaches have been proposed. Nevertheless these proposals have focused on static aspects only. In practice, the evolution of the operational information system can lead to changes in its dependent multidimensional data warehouse (i.e. that this system feeds with data), and therefore may require the evolution of the data warehouse model. In this evolving context, the authors propose a model-driven based approach in order to automate the propagation of the evolutions occurred in the source database towards the multidimensional data warehouse. This approach is based on two evolution models, along with a set of transformation rules formalized in Query/View/Transformation. This paper describes this evolution approach for which we are developing a software prototype called DWE© (Data Warehouse Evolution).

scholarly journals Toward Automatic Generation of Column-Oriented NoSQL Databases in Big Data Context

2019 ◽  
Vol 15 (09) ◽  
pp. 4
Author(s):  
Redouane Esbai ◽  
Fouad Elotmani ◽  
Fatima Zahra Belkadi
Keyword(s):  
Big Data ◽  
Relational Databases ◽  
Automatic Generation ◽  
Transformation Model ◽  
Model Driven ◽  
Transformation Rules ◽  
New Concepts ◽  
Nosql Database ◽  
Meta Object Facility ◽  
View Transformation

<span>The growth of application architectures in all areas (e.g. Astrology, Meteorology, E-commerce, social network, etc.) has resulted in an exponential increase in data volumes, now measured in Petabytes. Managing these volumes of data has become a problem that relational databases are no longer able to handle because of the acidity properties. In response to this scaling up, new concepts have emerged such as NoSQL. In this paper, we show how to design and apply transformation rules to migrate from an SQL relational database to a Big Data solution within NoSQL. For this, we use the Model Driven Architecture (MDA) and the transformation languages like as MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) and Acceleo which define the meta-models for the development of transformation model. The transformation rules defined in this work can generate, from the class diagram, a CQL code for creation column-oriented NoSQL database.</span>

Semantics-Aware Advanced OLAP Visualization of Multidimensional Data Cubes

2008 ◽  
pp. 974-1003 ◽  
Author(s):  
Alfredo Cuzzocrea ◽  
Domenico Sacca ◽  
Paolo Serafino
Keyword(s):  
Data Warehouse ◽  
Large Family ◽  
Research Topic ◽  
Biological Data ◽  
Multidimensional Data ◽  
Data Cubes ◽  
Efficient Data ◽  
Spatio Temporal ◽  
Multidimensional Data Cubes ◽  
Flattening Process

Efficiently supporting advanced OLAP visualization of multidimensional data cubes is a novel and challenging research topic, which results to be of interest for a large family of data warehouse applications relying on the management of spatio-temporal (e.g., mobile) data, scientific and statistical data, sensor network data, biological data, etc. On the other hand, the issue of visualizing multidimensional data domains has been quite neglected from the research community, since it does not belong to the well-founded conceptual-logical-physical design hierarchy inherited from relational database methodologies. Inspired from these considerations, in this article we propose an innovative advanced OLAP visualization technique that meaningfully combines (i) the so-called OLAP dimension flattening process, which allows us to extract two-dimensional OLAP views from multidimensional data cubes, and (ii) very efficient data compression techniques for such views, which allow us to generate “semantics-aware” compressed representations where data are grouped along OLAP hierarchies.

Model-Driven Data Warehouse Automation

2014 ◽  
pp. 240-267
Author(s):  
Moez Essaidi ◽  
Aomar Osmani ◽  
Céline Rouveirol
Keyword(s):  
Machine Learning ◽  
Data Warehouse ◽  
Inductive Logic Programming ◽  
Inductive Logic ◽  
Machine Learning Techniques ◽  
Learning Approach ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Transformation Rules ◽  
Learning Techniques

Transformation design is a key step in model-driven engineering, and it is a very challenging task, particularly in context of the model-driven data warehouse. Currently, this process is ensured by human experts. The authors propose a new methodology using machine learning techniques to automatically derive these transformation rules. The main goal is to automatically derive the transformation rules to be applied in the model-driven data warehouse process. The proposed solution allows for a simple design of the decision support systems and the reduction of time and costs of development. The authors use the inductive logic programming framework to learn these transformation rules from examples of previous projects. Then, they find that in model-driven data warehouse application, dependencies exist between transformations. Therefore, the authors investigate a new machine learning methodology, learning dependent-concepts, that is suitable to solve this kind of problem. The experimental evaluation shows that the dependent-concept learning approach gives significantly better results.

scholarly journals A Model Driven Architecture Approach to Generate Multidimensional Schemas of Data Warehouses

2019 ◽  
Vol 15 (12) ◽  
pp. 18
Author(s):  
Amine Azzaoui ◽  
Ouzayr Rabhi ◽  
Ayyoub Mani
Keyword(s):  
Formal Method ◽  
Heterogeneous Databases ◽  
Data Warehouses ◽  
Meta Model ◽  
Model Driven ◽  
Transformation Rules ◽  
View Transformation ◽  
Model Driven Approach

Over the past decade, the concept of data warehousing has been widely accepted. The main reason for building data warehouses is to improve the quality of information in order to achieve specific business objectives such as competitive advantage or improved decision-making. However, there is no formal method for deriving a multidimensional schema from heterogeneous databases that is recognized as a standard by the OMG and the professionals of the field. Which is why, in this paper, we present a model-driven approach (MDA) for the design of data warehouses. To apply the MDA approach to the Data warehouse construction process, we describe a multidimensional meta-model and specify a set of transformations from a UML meta-model which is mapped to a multidimensional meta-model. The transformation rules are programmed by the Query View Transformation (QVT) language. A case study illustrates our approach. It demonstrates how it reinforces the components traceability and reusability and how it globally improves the modeler’s efficiency. Furthermore, the use of the UML, as a technique to build data warehouses, is an important facilitator which prepares our further work to automate this approach.

Character Reorganization and Categorization using Hybrid Algorithms by Scanned Documents

2019 ◽  
Vol 8 (6S2) ◽  
pp. 943-948
Keyword(s):  
Research Work ◽  
Hybrid Algorithms ◽  
Research Topic ◽  
Image Processing Techniques ◽  
Digital Books ◽  
Otsu Method ◽  
Challenging Research ◽  
Processing Techniques ◽  
Scanned Documents ◽  
Day By Day

Detection and reorganization of text may save a lot of time while reproducing old books text and its chapters. This is really challenging research topic as different books may have different font types and styles. The digital books and eBooks reading habit is increasing day by day and new documents are producing every day. So in order to boost the process the text reorganization using digital image processing techniques can be used. This research work is using hybrid algorithms and morphological algorithms. For sample we have taken an letter pad where the text and images are separated using algorithms. The another objective of this research is to increase the accuracy of recognized text and produce accurate results. This research worked on two different concepts, first is concept of Pixel-level thresholding processing and another one is Otsu Method thresholding.

scholarly journals Obsidian and Obsidian-like Glass Tesserae: A Multidisciplinary Approach to Study the Dedication Wall Mosaic in the Church of St. Mary of the Admiral in Palermo (12th Century)

2020 ◽  
Vol 6 (1) ◽  
pp. 403-416
Author(s):  
Valentina Cantone ◽  
Rita Deiana ◽  
Alberta Silvestri ◽  
Ivana Angelini
Keyword(s):  
Multidisciplinary Approach ◽  
Multispectral Imaging ◽  
Volcanic Glass ◽  
Research Topic ◽  
Multidisciplinary Study ◽  
12Th Century ◽  
Challenging Research ◽  
Byzantine Period ◽  
Dark Glass ◽  
The Church

AbstractPliny the Elder testifies that roman workshops used volcanic glass (obsidian), but also produced and used a dark glass (obsidian-like glass) quite similar to the natural one. In the context of the study on medieval mosaics, the use of the obsidian and obsidian-like tesserae is a challenging research topic. In this paper, we present the results of a multidisciplinary study carried out on the Dedication wall mosaic, realized by a byzantine workshop in the 12th century in the Church of St. Mary of the Admiral in Palermo, and where numerous black-appearing tesserae, supposed to be composed of obsidian by naked-eyes observation, are present. Historical documents, multispectral imaging of the wall mosaic, and some analytical methods (SEM-EDS and XRPD) applied to a sample of black tesserae, concur in identifying here the presence of obsidian and different obsidian-like glass tesserae. This evidence, although related to the apparent tampering and restoration, could open a new scenario in the use of obsidian and obsidian-like glass tesserae during the Byzantine period in Sicily and in the reconstruction of multiple restoration phases carried out between 12th and 20th century AD on the mosaics of St. Mary of the Admiral.

Metal–organic frameworks as catalytic selectivity regulators for organic transformations

2021 ◽  
Author(s):  
Jun Guo ◽  
Yutian Qin ◽  
Yanfei Zhu ◽  
Xiaofei Zhang ◽  
Chang Long ◽  
...  
Keyword(s):  
Heterogeneous Catalysts ◽  
Metal Organic Frameworks ◽  
Research Topic ◽  
Organic Transformations ◽  
Catalytic Selectivity ◽  
Challenging Research ◽  
Metal Organic

Selective organic transformations using metal–organic frameworks (MOFs) and MOF-based heterogeneous catalysts have been an intriguing but challenging research topic in both the chemistry and materials communities.

Formal Metamodeling for Secure Model-Driven Engineering

2021 ◽  
Vol 12 (2) ◽  
pp. 46-67
Author(s):  
Liliana Maria Favre
Keyword(s):  
Cloud Computing ◽  
Formal Specifications ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Transformation Rules ◽  
Systematic Development ◽  
Definition Of ◽  
Context Specific ◽  
Theoretical Foundations

Systems and applications aligned with new paradigms such as cloud computing and internet of the things are becoming more complex and interconnected, expanding the areas in which they are susceptible to attacks. Their security can be addressed by using model-driven engineering (MDE). In this context, specific IoT or cloud computing metamodels emerged to support the systematic development of software. In general, they are specified through semiformal metamodels in MOF style. This article shows the theoretical foundations of a method for automatically constructing secure metamodels in the context of realizations of MDE such as MDA. The formal metamodeling language Nereus and systems of transformation rules to bridge the gap between formal specifications and MOF are described. The main contribution of this article is the definition of a system of transformation rules called NEREUStoMOF for transforming automatically formal metamodeling specifications in Nereus to semiformal-MOF metamodels annotated in OCL.

The study of mixed assets allocation based on Black–Litterman model

2021 ◽  
pp. 2150022
Author(s):  
Jianwu Lin ◽  
Mengwei Tang ◽  
Jiachang Wang ◽  
Ping He
Keyword(s):  
Stock Market ◽  
Asset Allocation ◽  
Private Equity ◽  
Equity Market ◽  
Research Topic ◽  
Allocation Model ◽  
Quantitative Models ◽  
Challenging Research ◽  
Qualitative Models ◽  
New Type

With Private Funds having a new type of license for asset allocation practice in China, comprehensive asset allocation cross private equity and stock market has received more attention. However, most of the studies focus more on the stock market, and asset allocation models for private equity market that are mainly made based on experience. Thus, the joint allocation of assets crosses both markets making it a challenging research topic. This paper introduces the Black–Litterman model into the private equity market, realizing the transition from qualitative models to quantitative models. It lays a solid quantitative ground for the mixed asset allocation model in both the markets.

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