This work is covering desing of database system which stores results of measerements performed on test stations which are part of assembly line.

This diploma thesis focuses on problematics associated with design of relational database. It is divided into several parts where it deals with theoretical basis, analyses of current state and the design of own solution.

Distributed actors working on a common RDF dataset regularly encounter the issue to compare the status of one graph with another or generally to synchronize copies of a dataset. A versioning system helps to synchronize the copies of a dataset, combined with a difference calculation system it is also possible to compare versions in a log and to determine, in which version a certain statement was introduced or removed. In this demo we present Quit Diff 1, a tool to compare versions of a Git versioned quad store, while it is also applicable to simple unversioned RDF datasets. We are following an approach to abstract from differences on a syntactical level to differences on the level of the RDF data model, while we leave further semantic interpretation on the schema and instance level to specialized applications. Quit Diff can generate patches in various output formats and can be directly integrated in the distributed version control system Git which provides a foundation for a comprehensive co-evolution work flow on RDF datasets.

Molecular-biological annotation data is continuously being collected, curated and made accessible in numerous public data sources. Integration of this data is a major challenge in bioinformatics. We present the GenMapper system that physically integrates heterogeneous annotation data in a flexible way and supports large-scale analysis on the integrated data. It uses a generic data model to uniformly represent different kinds of annotations originating from different data sources. Existing associations between objects, which represent valuable biological knowledge, are explicitly utilized to drive data integration and combine annotation knowledge from different sources. To serve specific analysis needs, powerful operators are provided to derive tailored annotation views from the generic data representation. GenMapper is operational and has been successfully used for large-scale functional profiling of genes.

The Swedish Environmental Protection Agency (Naturvårdsverket) is the public agency in Sweden with responsibility to overview the conditions of the environment and the policies related to the environmental monitoring data. Nowadays, observation data are stored in several different data models in this organization, leading to difficulties in finding, understanding and consequently using data in terms of analysis and management of environmental issues. One common model that uniformly structures observation data could largely make it easier for decision makers to find the required information. The aim of this study is to build an interoperable data model for environmental monitoring observation in Naturvårdsverket based on OGC-SWE standard formats. The proposed solution relies on Sensor Web architecture, which is the set of data model definitions andweb service specifications. Also, this methodology is based on open source components; therefore it is cost-effective for the users. The Service Oriented Architecture (SOA) is used to create a uniform model by using communication protocols such as Extensible Markup Language (XML) and Simple Object Access Protocol (SOAP). The primary findings of the thesis is that when the observation is encoded into the standard format from the beginning, then it is easier to parse these documents and find the required information for the end users without knowing how these information are gathered and stored. The client scan send a request to the Sensor Observation Service (SOS) and receive the observation that is structured based on Observation and Measurements (O&M).

abstract: The main objective of mathematical modeling is to connect mathematics with other scientific fields. Developing predictable models help to understand the behavior of biological systems. By testing models, one can relate mathematics and real-world experiments. To validate predictions numerically, one has to compare them with experimental data sets. Mathematical modeling can be split into two groups: microscopic and macroscopic models. Microscopic models described the motion of so-called agents (e.g. cells, ants) that interact with their surrounding neighbors. The interactions among these agents form at a large scale some special structures such as flocking and swarming. One of the key questions is to relate the particular interactions among agents with the overall emerging structures. Macroscopic models are precisely designed to describe the evolution of such large structures. They are usually given as partial differential equations describing the time evolution of a density distribution (instead of tracking each individual agent). For instance, reaction-diffusion equations are used to model glioma cells and are being used to predict tumor growth. This dissertation aims at developing such a framework to better understand the complex behavior of foraging ants and glioma cells. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2019

With the improvements in computer technology, users in utilities expect to receive more advanced functions of their power system management applications by using the data distributed among computer applications. The conventional method of point-to-point interface is not efficient for building large-scale computer systems and is especially difficult for system integration. Integration efforts are carried on to facilitate software applications communicating with others. Defining the same description for a central database and exchangeable data format among applications is the first step for integration. Since current data models in the Common Information Model (CIM) are designed mostly for analyzing the terrestrial transmission power system, they are not sufficient for Shipboard Power Systems (SPS). In order to facilitate software integration in SPS, a fundamentally common semantic for SPS applications needs to be extended from the current CIM. Therefore, these analysis applications for SPS could communicate with each other based on a standard model. In this thesis, a pulsed load model is extended from CIM. This model is a general time dependent pulsed load and the simulation of pulsed railgun load validates the proposed data model. Also, stress upon the power grid caused by the pulsed load is analyzed and the continuous railgun operation is simulated. In addition, new CIM data models are built for passive and active filters to facilitate system simulation and further application. As an active filter is a device that incorporates complicated control strategies, much work focused on finding a general data model to accommodate most common active filters. Finally the simulation for active filter validates the proposed data model.

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Availability of organized data is required for accurate prediction of structural or functional deterioration in sewer and water pipes. Toward this end, GIS provides a means for viewing, understanding, interpreting, and visualizing complex geographically referenced information to reveal data relationships, patterns, and trends. The primary objective of this research is to develop a standard GIS data model and applications of the model. In the future, these can be used to develop protocols and methods for predicting the remaining life of water and wastewater assets. The source data for this study is the utility data and other publicly available data from resources such as USGS, SSURGO etc. Field mapping files are generated from the source files and the standard data model. These are then programmed to the common Extensible markup Language (XML) file developed as a base which is then converted to the data model where the final form of utility data is stored. The data taken from the utilities is cleansed and analyzed to match the standard data model which is then uploaded through the common XML and stored in the data warehouse as a geospatial database. The geospatial database is an aggregated water and wastewater infrastructure data consisting of the utility data in standard data model format. The data warehouse is developed for utilities to store their data at a centralized server, such as the San Diego Super Computer Center. Web applications demonstrate the publishing, querying and visualization of aggregated data in a map-based browser application. This aggregation of data of multiple utilities will help in providing timely access to asset management information and resources that will lead to more efficient programs. This tool also furnishes the public with a convenient tool to learn about municipal water and wastewater infrastructure systems. This document gives an overview of how this process can be achieved using the above mentioned tools and methodologies. / Master of Science