Master of Science

Over the last decade, we have witnessed the emergence of networks in a wide spectrum of application domains, ranging from social and information networks to biological and transportation networks.Graphs provide a solid theoretical foundation for modeling complex networks and revealing valuable insights from both the network structure and the data embedded within its entities.As the business and social environments are getting increasingly complex and interconnected, graphs became a widespread abstraction at the core of the information infrastructure supporting those environments. Modern information systems consist of a large number of sophisticated and interacting business entities that naturally form graphs. In particular, integrating graphs into data warehouse systems received a lot of interest from both academia and industry. Indeed, data warehouses are the central enterprise's information repository and are critical for proper decision support and future planning. Graph warehousing is emerging as the field that extends current information systems with graph management and analytics capabilities. Many approaches were proposed to address the graph data warehousing challenge. These efforts laid the foundation for multidimensional modeling and analysis of graphs. However, most of the proposed approaches partially tackle the graph warehousing problem by being restricted to simple abstractions such as homogeneous graphs or ignoring important topics such as multidimensional integrity constraints and dimension hierarchies.In this dissertation, we conduct a systematic study of the graph data warehousing topic and address the key challenges of database and multidimensional modeling of graphs.We first propose GRAD, a new graph database model tailored for graph warehousing and OLAP analytics. GRAD aims to provide analysts with a set of simple, well-defined, and adaptable conceptual components to support rich semantics and perform complex analysis on graphs.Then, we define the multidimensional concepts for heterogeneous attributed graphs and highlight the new types of measures that could be derived. We project this multidimensional model on property graphs and explore how to extract the candidate multidimensional concepts and build graph cubes. Then, we extend the multidimensional model by integrating GRAD and show how GRAD facilitates multidimensional graph modeling, and enables supporting dimension hierarchies and building new types of OLAP cubes on graphs.Afterward, we present TopoGraph, a graph data warehousing framework that extends current graph warehousing models with new types of cubes and queries combining graph-oriented and OLAP querying. TopoGraph goes beyond traditional OLAP cubes, which process value-based grouping of tables, by considering also the topological properties of the graph elements. And it goes beyond current graph warehousing models by proposing new types of graph cubes. These cubes embed a rich repertoire of measures that could be represented with numerical values, with entire graphs, or as a combination of them.Finally, we propose an architecture of the graph data warehouse and describe its main building blocks and the remaining gaps. The various components of the graph warehousing framework can be effectively leveraged as a foundation for designing and building industry-grade graph data warehouses.We believe that our research in this thesis brings us a step closer towards a better understanding of graph warehousing. Yet, the models and framework we proposed are the tip of the iceberg. The marriage of graph and warehousing technologies will bring many exciting research opportunities, which we briefly discuss at the end of the thesis. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Aim of this thesis is the description of the Microsoft .NET Framework, its different versions, architecture, and its assembly, used for its simplistic architecture, and ease of use with the assembly it is the ideal environment for creating modular applications. The work describes the C# programming language and its versions. It includes a description of the different stages and evolution of the web application framework ASP.NET. It includes a short description of the ADO.NET and LINQ technologies, used to access data from databases. It describes different databases, they structure and classification. At the end there is a layout for a database structure, blogging system, aim and structure of the files, the different system parts and functions.

Dissertation (LLM)--University of Pretoria, 2014. / gm2015 / Centre for Human Rights / LLM / Unrestricted

see document / Master of Science

In the early phases of drug design and development, scientists must overcome many challenges involved in identifying potential drug-like or lead-like compounds. This has led to the need of creating large sets of chemical data which will aid in improving the identification of pharmacophores and active compounds. Various scientific fields especially pharmacology, medicinal chemistry and biochemistry have begun to employ the use of computer sciences to aid in the screening for potential leads with more specificity with regards to drug-like compounds' or substances' bioactivity. The emphasis of this project was to create a database containing a collection of pyrazine compounds synthesized overtime in the Faculty of Pharmacy (Charles University, Hradec Kralove) with the aim of having anti-mycobacterium (and possible antibacterial and antifungal) activity, and further utilize this database to predict certain pharmacokinetic and bioavailability properties. This project seeks to demonstrate how certain molecular descriptors can be used as reliable chemoinformation to determine the likeliness or possibility of developing a lead-like or drug-like compound by utilizing computer software. An in-house database of 623 compounds saved in SMILES format was created and used in demonstrating quantitative...

NR 20140805

A Multi-tenant architecture is a cost optimization for Software as a Service, where customers, also referred to as tenants are consolidated into the same server. The main idea of this architecture is to consolidate as many tenants as possible into the same server to reduce the total cost for the service provider. However, the contention of shared resources can lead to reduced performance for the tenants. One shared resource between the tenants is the data-layer.This thesis aims to analyze and to do a performance evaluation of different data-layer designs in a Multi-tenant architecture. The thesis compares three data-layer designs implemented in a RDBMS.An experiment was performed to evaluate the transactions per secondfor tenants when both the amount of data and the number of tenants increase. The evaluations were computed for the Create, Read, Update and Delete operations, also known as the CRUD-operations.Three data-layer designs were tested in the experiment; Shared table design, where tenants share the same database system as well as the tables, Separated table design, where tenants share the same database system but store and query data to their own private tables and Oracle Multi-tenant, where each tenant gets its own database.The experiment indicates that the Oracle Multi-tenant has the highest performance while the Shared table design suffers when both the number of tenants and the amount of data increase. / Multi-tenant arkitektur är en kostnadsoptimering för mjukvara som tillhandahålls över ett nätverk. Användarna, tenants är då betjänade av samma serverdator. Uppdraget för serverdatorn är att betjäna så många tenants som möjligt för att reducera kostnader för mjukvaruägaren. Men att dela resurser mellan tenants kan leda till försämrad prestanda. En delad resurs mellan tenants är dataskiktet.Målet med denna uppsats är att göra en analys och ett prestandatest av olika uppsättningar av dataskikt i en Multi-tenant arkitektur. Uppsatsen fokuserar endast på olika uppsättningar i ett RDBMS.Ett experiment utfördes där antalet tenants och data ökade för varje uppsättning. Experimentet evaluerade prestanda av Create, Read, Update och Delete operationer, även känt som CRUD-operationer. Tre uppsättningar testades; Shared table design, där tenants delar databas och tabeller, Separated table design, där tenants delar databas, men lagrar data i sina egna tabeller och Oracle Multi-tenant, där varje tenant får en egen databas.Experiment visar att Oracle Multi-tenant har högst prestanda medan Shared table design har lägst när antalet tenants och mängd data ökar.

This study conducted an experiment that compares the multi-model NoSQL DBMS ArangoDB with other NoSQL DBMS, in terms of the average response time of queries. The DBMS compared in this experiment are the following: Redis, MongoDB, Couchbase, and OrientDB. The hypothesis that is answered in this study is the following: “There is a significant difference between ArangoDB, OrientDB, Couchbase, Redis, MongoDB in terms of the average response time of queries”. This is examined by comparing the average response time of 1 000, 100 000, and 1 000 000 queries between these database systems. The results show that ArangoDB performs worse compared to the other DBMS. Examples of future work include using additional DBMS in the same experiment and replacing ArangoDB with another multi-model DBMS to decide whether such a DBMS, in general, performs worse than single-model DBMS.

A biological pathway is a series of reactions and molecular interactions. Pathway information provides a blueprint for biomedical researchers to devise new treatment and diagnostic solutions for human diseases. Pathway data are publicly available in many databases. Most of the databases however have only partial coverage of human biological pathways, especially for signal transduction and gene regulatory pathways. Comprehensive knowledge and a combined view for all types for biological pathways may lead to insights into the molecular physiology of cells and drug discovery. In this project, we collected human signaling pathway data from different database sources. The pathway data comes from the Biocarta, Protein Lounge, Resnet and NCI-Nature Curated databases. We analyzed the structures of collected data, and developed a comprehensive data model to manage integrated information of molecules, complexes, regulation relationships of molecules, and reactions involved in signaling and regulatory pathways. The integrated database, the Human Pathway database (HPD), is a data warehouse of a comprehensive collection of biological reactions, regulators, and metabolites, serving as a potential platform for future pathway analysis studies. We developed the database to manage integrated biomolecular information related to pathways. In HPD, which uses Oracle 10g, there are a total of 1,895 pathways, 10,631 molecular entities (proteins, complexes and compounds) and 4,370 reactions that were consolidated and integrated into a single relational database platform using Oracle 10g. We also developed a prototypical GUI for the navigation and querying of biological pathways. Such a system, when completed, and used in conjunction with future pathway data visualization and analysis tools, could provide a framework for systems biology studies. We developed HPD with comprehensive annotation data. For example, the kinase - disease association information and perturbation effect of several environmental factors are unique in HPD. The potential for merging similar pathways—“pathway mergability” —was created based on gene/protein identifiers and to provide with non-redundant pathway information. To test the technology we have done two case studies. The first case study addressed the Alzheimer’s disease by coupling pathway network analysis with gene expression data. The second case study addressed the cellular responses by coupling the pathway network analysis with protein expression data. These case studies demonstrate how an integrated pathway database can be used to generate new insights into the discovery of biomarkers, and extend our understanding of cellular physiology.