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Datenbank Spektrum 12(3) - November 2012

https://dl.gi.de/handle/20.500.12116/11571
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Auflistung Datenbank Spektrum 12(3) - November 2012 nach Titel

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  • Zeitschriftenartikel
    Bericht über den 24. GI-Workshop “Grundlagen von Datenbanken”
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Schmitt, Ingo; Höpfner, Hagen
  • Zeitschriftenartikel
    CityPlot: Colored ER Diagrams to Visualize Structure and Contents of Databases
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Dugas, Martin; Vossen, Gottfried
    CityPlot generates an extended version of a traditional entity-relationship diagram for a database. It is intended to provide a combined view of database structure and contents. The graphical output resembles the metaphor of a city. Data points are visualized according to data type and completeness. An open source reference implementation is available from http://cran.r-project.org/.
  • Zeitschriftenartikel
    Data Management Challenges in Next Generation Sequencing
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Wandelt, Sebastian; Rheinländer, Astrid; Bux, Marc; Thalheim, Lisa; Haldemann, Berit; Leser, Ulf
    Since the early days of the Human Genome Project, data management has been recognized as a key challenge for modern molecular biology research. By the end of the nineties, technologies had been established that adequately supported most ongoing projects, typically built upon relational database management systems. However, recent years have seen a dramatic increase in the amount of data produced by typical projects in this domain. While it took more than ten years, approximately three billion USD, and more than 200 groups worldwide to assemble the first human genome, today’s sequencing machines produce the same amount of raw data within a week, at a cost of approximately 2000 USD, and on a single device. Several national and international projects now deal with (tens of) thousands of genomes, and trends like personalized medicine call for efforts to sequence entire populations. In this paper, we highlight challenges that emerge from this flood of data, such as parallelization of algorithms, compression of genomic sequences, and cloud-based execution of complex scientific workflows. We also point to a number of further challenges that lie ahead due to the increasing demand for translational medicine, i.e., the accelerated transition of biomedical research results into medical practice.
  • Zeitschriftenartikel
    Der 175. Datenbankstammtisch an der HTW Dresden
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Wloka, Uwe; Gräfe, Gunter
  • Zeitschriftenartikel
  • Zeitschriftenartikel
    Dissertationen
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012)
  • Zeitschriftenartikel
    Editorial
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Gertz, Michael; Müller, Wolfgang
  • Zeitschriftenartikel
    Handling Big Data in Astronomy and Astrophysics: Rich Structured Queries on Replicated Cloud Data with XtreemFS
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Enke, Harry; Partl, Adrian; Reinefeld, Alexander; Schintke, Florian
    With recent observational instruments and survey campaigns in astrophysics, efficient analysis of big structured data becomes more and more relevant. While providing good query expressiveness and data analysis capabilities through SQL, off-the-shelf RDBMS are yet not well prepared to handle high volume scientific data distributed across several nodes, neither for fast data ingest nor for fast spatial queries. Our SQL query parser and job manager performs query reformulation to spread queries to data nodes, gathering outputs on a head node and providing them again to the shards for subsequent processing steps. We combine this data analysis architecture with the cloud data storage component XtreemFS for automatic data replication to improve the availability and access latency. With our solution we perform rich structured data analysis expressed using SQL on large amounts of structured astrophysical data distributed across numerous storage nodes in parallel. The cloud storage virtualization with XtreemFS provides elasticity and reproducibility of scientific analysis tasks through its snapshot capability.
  • Zeitschriftenartikel
    News
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012)
  • Zeitschriftenartikel
    Scientific Workflows and Provenance: Introduction and Research Opportunities
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Cuevas-Vicenttín, Víctor; Dey, Saumen; Köhler, Sven; Riddle, Sean; Ludäscher, Bertram
    Scientific workflows are becoming increasingly popular for compute-intensive and data-intensive scientific applications. The vision and promise of scientific workflows includes rapid, easy workflow design, reuse, scalable execution, and other advantages, e.g., to facilitate “reproducible science” through provenance (e.g., data lineage) support. However, as described in the paper, important research challenges remain. While the database community has studied (business) workflow technologies extensively in the past, most current work in scientific workflows seems to be done outside of the database community, e.g., by practitioners and researchers in the computational sciences and eScience. We provide a brief introduction to scientific workflows and provenance, and identify areas and problems that suggest new opportunities for database research.