Digitization that has enabled instant access to vast numbers of archival, historical images, demands a new paradigm for the use of visual imagery in historical research. This thesis proposes a new form of historiography in the digital medium, an image-based narrative mode for authoring and reading history. I propose a digital model for conveying history through the visual record, as an alternative to the printed book. Unlike the quantitative “big data” approach to digital humanities, this research explores visuality itself. In a practice-led approach, the research addresses both aspects of historiography: (1) a method of historical representation; and (2) original historical work on a selected topic. The testbed for historiographic and narrative experiments which led to the model was my case study on the Boxer Uprising in China, c. 1900. While many written histories of the Boxer Uprising exist, I collected a large portion of its extensive visual record for the first time. Sources from around the world, in a variety of media, were assembled into a digital data set that reveals previously unexplored historical themes. A series of visual narratives built in the case study culminated in a proposed “Visual Narrative Field” model. In this model, meaning emerges in the patterns observed between images within a complex visual field. The model vertically integrates three narrative approaches in order to support alternating cognitive modes used to read texts and perceive images. Linear concentration is blended with the non-linear exploration of interactive forms. The model provides historians with a much-needed tool for authoring narrative through relationships between images in a scalable approach. Due to digitization, visual databases are easily assembled, and images are as easily reproduced as written text. The Visual Narrative Field model takes advantage of the characteristics of the newly-digitized visual record, providing a means of authoring visual narrative that can be comprehended without the use of extensive written text. The model thus creates an unprecedented image-based method for performing and presenting historical research.

The master thesis deals with data quality in the context of open and linked data. One of the goals is to define specifics of data quality in this context. The specifics are perceived mainly with orientation to data quality dimensions (i. e. data characteristics which we study in data quality) and possibilities of their measurement. The thesis also defines the effect on data quality that is connected with data transformation to linked data; the effect if defined with consideration to possible risks and benefits that can influence data quality. The list of metrics verified on real data (open linked data published by government institution) is composed for the data quality dimensions that are considered to be relevant in context of open and linked data. The thesis points to the need of recognition of differences that are specific in this context when assessing and managing data quality. At the same time, it offers possibilities for further study of this question and it presents subsequent directions for both theoretical and practical evolution of the topic.

This thesis deals with usage of data mining on data of a library. It specializes in data of users and their behavior registered by library management system Clavius. For this purpose the data of University Library of Silesian University in Opava were used. Firstly the data mining therm is explained and it's use in libraries is thoroughly described. Secondly the ways of usage of the Clavius data are discussed then the text follows data mining usage for management of the library in particular. Finally the results of data mining concerning user's behavior is described in the rear of this thesis. Powered by TCPDF (www.tcpdf.org)

The specification of building material is required in multiple phases of engineering and construction projects towards holistic BIM implementations. Building material information plays a vital role in design decisions by enabling different simulation processes, such as energy, acoustic, lighting, etc. Utilization and sharing of building material information between stakeholders are some of the major influencing factors on the practical implementation of the BIM process. Different meta-data schemas (e.g. IFC) are usually available to represent and share material information amongst partners involved in a construction project. However, these schemas have their own constraints to enable efficient data sharing amongst stakeholders. This paper explains these constraints and proposes a methodological approach for the representation of material data using semantic web concepts aiming to support the sharing of BIM data and interoperability enhancements in collaboration workflows. As a result, the DICBM (https://w3id.org/digitalconstruction/BuildingMaterials) ontology was developed which improves the management of building material information in the BIM-based collaboration process.:Abstract 1. Introduction and Background 1.1 Building Information Modeling for collaboration 1.2 Information management in AEC using semantic web technologies 2 DICBM: Digital Construction Building Material Ontology 2.1 Building Material Data in IFC 2.2 Overview of the building material ontology 2.3 Integration of external ontology concepts and roles 2.4 Material Definition 2.5 Material, Material Type, and Material Property 2.6 Data Properties in DICBM 3 Conclusions Acknowledgments References

Die MOSAiC-Expedition war die größte Polarexpedition, die je durchgeführt wurde. Mehr als ein Jahr driftete das Forschungsschiff Polarstern durch den Arktischen Ozean und erhob dabei unzählige Forschungsdaten. Die Umsetzung stellte große logistische und technische Herausforderungen. Gleichzeitig setzte das Projekt Meilensteine in der Digitalisierung der MOSAiC-Daten. Das vorhandene Datenrepositorim PANGEA wurde als Datenbasis für die Abspeicherung der erhobenen und gewonnenen Daten genutzt. Das Datenmanagement hatte ein frühestmögliches Teilen der Daten zum Ziel. Außerdem stand von Anfang an das Datenmanagement als ein Teil von open science und einer frühen Datenzitierbarkeit. Ab 2023 sollen alle MOSAiC-Daten im Repositorium frei verfügbar sein. MOSAiC ist der bisher größte Anwendungsfall für das Projekt Nationale Forschungsdateninfrastruktur (NFDI). / The MOSAiC expedition was the largest polar expedition ever conducted. For more than a year, the research vessel Polarstern drifted through the Arctic Ocean collecting countless research data. The implementation posed major logistical and technical challenges. At the same time, the project set milestones in the digitization of MOSAiC data. The existing data repositoryim PANGEA was used as a database for storing the collected and acquired data. Data management aimed at sharing the data as early as possible. In addition, from the beginning, data management stood as a part of open science and early data citability. Starting in 2023, all MOSAiC data should be freely available in the repository. MOSAiC is the largest use case to date for the National Research Data Infrastructure (NFDI) project.

This Thesis deals with the problems of medical image data management. It analyzes a metadata extraction problem from medical format DICOM and their efficient saving. System is designed as a client-server application. System provides an interface for DICOM data storing, interface for searching, data editing and exporting. System cooperatives with the collaborative system VCE. Implementation was carried out in C++ and PHP language with support of SQLite and MySQL database.

Data-intensive flows deploy a variety of complex data transformations to build information pipelines from data sources to different end users. As data are processed, these workflows generate large intermediate results, typically pipelined from one operator to the following ones. Materializing intermediate results, shared among multiple flows, brings benefits not only in terms of performance but also in resource usage and consistency. Similar ideas have been proposed in the context of data warehouses, which are studied under the materialized view selection problem. With the rise of Big Data systems, new challenges emerge due to new quality metrics captured by service level agreements which must be taken into account. Moreover, the way such results are stored must be reconsidered, as different data layouts can be used to reduce the I/O cost. In this paper, we propose a novel approach for automatic selection of multi-objective materialization of intermediate results in data-intensive flows, which can tackle multiple and conflicting quality objectives. In addition, our approach chooses the optimal storage data format for selected materialized intermediate results based on subsequent access patterns. The experimental results show that our approach provides 40% better average speedup with respect to the current state-of-the-art, as well as an improvement on disk access time of 18% as compared to fixed format solutions.

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The aim of this thesis is to familiarize readers with the terms and conditions relating to Intrastat and Ex Post Control of Data. The first part deals with obligations under the data collection. There are defined terms such as Intrastat, information provider, reference period, obligation to information provider and competence of government.The text is supplemented by examples that help better understand the topic. This section ends with an example that shows the overall procedure for reporting and transmission of data Intrastat. In the second part of the thesis I deal with Ex Post Control of Data which are carried out by the Customs Administration of the Czech republic. Both parts are supplemented by a number of interesting facts as information provider, number of reported data or inspections. In conclusion I am trying to identify errors and deficiencies in data collection and Ex Post Control of Data and to propose some measures that will lead to improvements in processes relating to Intrastat.

This Ph.D. thesis deals with Open Government Data and the methodology for publication of this kind of data. Public sector bodies hold a significant amount of data that can be reused in innovative way leading to development of new products and services. According to the Open Knowledge Foundation "Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike." Publication and reuse of Open Government Data can lead to benefits such as increased economic growth. State, society as well as the public sector bodies themselves can benefit from Open Government Data. However the public sector bodies currently face a number of problems and issues when publishing Open Government Data, e.g. regular updates of the published datasets are not always ensured. Different public sector bodies apply different approaches to publication of Open Government Data. The main goal of this thesis is to design the Open Government Data Publication Methodology which should address current problems related to the publication of Open Government Data.