Wir stellen ein Online-Übungssytem vor, das im Rahmen des Bildungsportals Sachsen entwickelt wurde und erfolgreich im Informatikstudium der Universität Leipzig im Einsatz ist. Der Systemzugang erfolgt für Lernende und Tutoren gleichermaßen über Web-Schnittstellen. Das System eignet sich insbesondere für den vorlesungsbegleitenden Übungsbetrieb, aber auch für das Selbststudium. Für die Ausbildung im Gebiet „Datenbanken“ wird sowohl ein SQL-Trainer als auch ein XQuery-Trainer zum Erlernen und Anwenden der jeweiligen Abfragesprache integriert. Wir stellen die Konzeption und Realisierung des Systems vor und berichten über bisherige Erfahrungen und geplante Erweiterungen.

Eine zentrale Ablage für PA-Fragebögen würde den Zugriff deutlich erleichtern. Durch umfassende Suchbedingungen kann eine weitere Verbesserung der Auswahl erfolgen. Darin liegt der Ursprung dieser Arbeit. Eine zentrale Ablage für Fragebögen zu schaffen würde die Auswahl des richtigen Fragebogens deutlich erleichtern und beschleunigen. Um die Personen, welche mit Fragebögen arbeiten zu unterstützen und die Arbeit mit Fragebögen zu erleichtern ist eine zentrale Übersicht von großem Vorteil.

In this article the author recommends a hierarchically structured data base, called MemoMaster, as a mighty tool to replace traditional card indexes in the preparatory stage of onomastic research. Referring to Karlheinz Hengst’s exemplary monograph on place names in the South-West of Saxony, he demonstrates how MemoMaster enables the scholar to store and structure information in folders, subfolders, and “memos“ to be utilized in a manuscript later on. His explanation is supported by two screenshots.

Multi-tenancy in relational databases has been a topic of interest for a couple of years. On the one hand, ever increasing capabilities and capacities of modern hardware easily allow for multiple database applications to share one system. On the other hand, cloud computing leads to outsourcing of many applications to service architectures, which in turn leads to offerings for relational databases in the cloud, as well. The ability to benchmark multi-tenancy database systems (MT-DBMSs) is imperative to evaluate and compare systems and helps to reveal otherwise unnoticed shortcomings. With several tenants sharing a MT-DBMS, a benchmark is considerably different compared to classic database benchmarks and calls for new benchmarking methods and performance metrics. Unfortunately, there is no single, well-accepted multi-tenancy benchmark for MT-DBMSs available and few efforts have been made regarding the methodology and general tooling of the process. We propose a method to benchmark MT-DBMSs and provide a framework for building such benchmarks. To support the cumbersome process of defining and generating tenants, loading and querying their data, and analyzing the results we propose and provide MULTE, an open-source framework that helps with all these steps.

In starting the Demotic Palaeographical Database Project, we intend to build up an online database which pays special attention to the actual appearance of Demotic papyri and texts down to the level of the individual sign. Our idea is to analyse a papyrus with respect to its visual nature, inasmuch as it shall be possible to compare each Demotic sign to other representations of the same sign in other texts and to study its occurrences in different words. Words shall not only be analysed in their textual context but also by their orthography and it should be possible to study even the papyrus itself by means of its material features. Therefore, the Demotic Palaeographical Database Project aims for the creation of a modern and online accessible Demotic palaeography, glossary of word spellings and corpus of manuscripts, which will not only be a convenient tool for Egyptologists and researchers interested in the Demotic writing system or artefacts inscribed with Demotic script but also will serve the conservation of cultural heritage. In our paper, we will present our conceptual ideas and the preliminary version of the database in order to demonstrate its functionalities and possibilities.

“The Ancient Egyptian Demonology Project: Second Millennium BCE” was intended and funded as a three-year project (2013-2016) to explore the world of Ancient Egyptian demons in the 2nd millennium BC. It intends to create a classification and ontology of benevolent and malevolent demons. Whereas ancient Egyptians did not use a specific term denoting “demons”, liminal beings known from various other cultures such as δαίμονες, ghosts, angels, Mischwesen, genies, etc., were nevertheless described in texts and illustrations. The project aims to collect philological, iconographical and archaeological evidence to understand the religious beliefs, practices, interactions and knowledge not only of the ancient Egyptians’ daily life but also their perception of the afterlife. Till today scholars, as well as interested laymen, have had no resource to consult for specific examples of those beings, except for rather general encyclopaedias that include all kinds of divine beings or the Iconography of Deities and Demons (IDD) project that is ongoing. Neither provides, however, a searchable platform for both texts and images. The database created by the Demonology Project: 2K is designed to remedy this gap. The idea is to provide scholars and the public with a database that allows statistical analyses and innovative data visualisation, accessible and augmentable from all over the world to stimulate the dialogue and open communication not only within Egyptology but also with neighbouring disciplines. For the time-span of the three year project a pilot database was planned as a foundation for further data-collection and analysis. The data that were chosen date to the 2nd Millennium BCE and originate from objects of daily life (headrests and ivory wands), as well as from objects related to the afterlife, (coffins and ‘Book of the Dead’ manuscripts). This material, connected by its religious purposes, nevertheless provides a cross-section through ancient Egyptian religious practice. The project is funded by the Leverhulme Trust and includes Kasia Szpakowska (director) who supervises the work of the two participating PhD students in Egyptology. The project does not include funds for computer scientists or specialists in digital humanities. Therefore, the database is designed, developed and input by the members of the team only. The focus of my presentation will be the structure of the database that faces the challenge to include both textual and iconographical evidence. I will explain the organisation of the data, search patterns and the opportunities of their visualisation and possible research outcome. Furthermore, I will discuss the potentials the database already possesses and might generate in the future for scholars and the public likewise. Since the evidence belongs to numerous collections from all over the world, I would like to address the problems of intellectual property and copyright with the solution we pursue for releasing the database for registered usage onto the internet.

THEREDA (Thermodynamic Reference Database) is a collaborative project, which has been addressed this challenge. The partners are Helmholtz-Zentrum Dresden-Rossendorf, Karlsruhe Institute of Technology (KIT-INE), Gesellschaft für Anlagen- und Reaktorsicherheit Braunschweig mbH (GRS), TU Bergakademie Freiberg (TUBAF) and AF-Consult Switzerland AG (Baden, Switzerland). The aim of the project is the establishment of a consistent and quality assured database for all safety relevant elements, temperature and pressure ranges, with its focus on saline systems. This implied the use of the Pitzer approach to compute activity coefficients suitable for such conditions. Data access is possible via commonly available internet browsers under the address http://www.thereda.de. One part of the project - the data collection and evaluation for uranium – was a task of the Helmholtz-Zentrum Dresden-Rossendorf. The aquatic chemistry and thermodynamics of U(VI) and U(IV) is of great importance for geochemical modelling in repository-relevant systems. The OECD/NEA Thermochemical Database (NEA TDB) compilation is the major source for thermodynamic data of the aqueous and solid uranium species, even though this data selection does not utilize the Pitzer model for the ionic strength effect correction. As a result of the very stringent quality demands, the NEA TDB is rather restrictive and therefore incomplete for extensive modelling calculations of real systems. Therefore, the THEREDA compilation includes additional thermodynamic data of solid secondary phases formed in the waste material, the backfill and the host rock, though falling into quality assessment (QA) categories of lower accuracy. The data review process prefers log K values from solubility experiments (if available) to those calculated from thermochemical data.

Computing hardware is changing from systems with homogeneous CPUs to systems with heterogeneous computing units like GPUs, Many Integrated Cores, or FPGAs. This trend is caused by scaling problems of homogeneous systems, where heat dissipation and energy consumption is limiting further growths in compute-performance. Heterogeneous systems provide differently optimized computing hardware, which allows different operations to be computed on the most appropriate computing unit, resulting in faster execution and less energy consumption. For database systems, this is a new opportunity to accelerate query processing, allowing faster and more interactive querying of large amounts of data. However, the current hardware trend is also a challenge as most database systems do not support heterogeneous computing resources and it is not clear how to support these systems best. In the past, mainly single operators were ported to different computing units showing great results, while missing a system wide application. To efficiently support heterogeneous systems, a systems approach for query processing and query optimization is needed. In this thesis, we tackle the optimization challenge in detail. As a starting point, we evaluate three different approaches on isolated use-cases to assess their advantages and limitations. First, we evaluate a fork-join approach of intra-operator parallelism, where the same operator is executed on multiple computing units at the same time, each execution with different data partitions. Second, we evaluate using one computing unit statically to accelerate one operator, which provides high code-optimization potential, due to this static and pre-known usage of hardware and software. Third, we evaluate dynamically placing operators onto computing units, depending on the operator, the available computing hardware, and the given data sizes. We argue that the first and second approach suffer from multiple overheads or high implementation costs. The third approach, dynamic placement, shows good performance, while being highly extensible to different computing units and different operator implementations. To automate this dynamic approach, we first propose general placement optimization for query processing. This general approach includes runtime estimation of operators on different computing units as well as two approaches for defining the actual operator placement according to the estimated runtimes. The two placement approaches are local optimization, which decides the placement locally at run-time, and global optimization, where the placement is decided at compile-time, while allowing a global view for enhanced data sharing. The main limitation of the latter is the high dependency on cardinality estimation of intermediate results, as estimation errors for the cardinalities propagate to the operator runtime estimation and placement optimization. Therefore, we propose adaptive placement optimization, allowing the placement optimization to become fully independent of cardinalities estimation, effectively eliminating the main source of inaccuracy for runtime estimation and placement optimization. Finally, we define an adaptive placement sequence, incorporating all our proposed techniques of placement optimization. We implement this sequence as a virtualization layer between the database system and the heterogeneous hardware. Our implementation approach bases on preexisting interfaces to the database system and the hardware, allowing non-intrusive integration into existing database systems. We evaluate our techniques using two different database systems and two different OLAP benchmarks, accelerating the query processing through heterogeneous execution.

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No description available.