33,797 research outputs found
The NASA Astrophysics Data System: Architecture
The powerful discovery capabilities available in the ADS bibliographic
services are possible thanks to the design of a flexible search and retrieval
system based on a relational database model. Bibliographic records are stored
as a corpus of structured documents containing fielded data and metadata, while
discipline-specific knowledge is segregated in a set of files independent of
the bibliographic data itself.
The creation and management of links to both internal and external resources
associated with each bibliography in the database is made possible by
representing them as a set of document properties and their attributes.
To improve global access to the ADS data holdings, a number of mirror sites
have been created by cloning the database contents and software on a variety of
hardware and software platforms.
The procedures used to create and manage the database and its mirrors have
been written as a set of scripts that can be run in either an interactive or
unsupervised fashion.
The ADS can be accessed at http://adswww.harvard.eduComment: 25 pages, 8 figures, 3 table
Database support of detector operation and data analysis in the DEAP-3600 Dark Matter experiment
The DEAP-3600 detector searches for dark matter interactions on a 3.3 tonne
liquid argon target. Over nearly a decade, from start of detector construction
through the end of the data analysis phase, well over 200 scientists will have
contributed to the project. The DEAP-3600 detector will amass in excess of 900
TB of data representing more than 10 particle interactions, a few of
which could be from dark matter. At the same time, metadata exceeding 80 GB
will be generated. This metadata is crucial for organizing and interpreting the
dark matter search data and contains both structured and unstructured
information.
The scale of the data collected, the important role of metadata in
interpreting it, the number of people involved, and the long lifetime of the
project necessitate an industrialized approach to metadata management.
We describe how the CouchDB and the PostgreSQL database systems were
integrated into the DEAP detector operation and analysis workflows. This
integration provides unified, distributed access to both structured
(PostgreSQL) and unstructured (CouchDB) metadata at runtime of the data
analysis software. It also supports operational and reporting requirements
Query processing of spatial objects: Complexity versus Redundancy
The management of complex spatial objects in applications, such as geography and cartography,
imposes stringent new requirements on spatial database systems, in particular on efficient
query processing. As shown before, the performance of spatial query processing can be improved
by decomposing complex spatial objects into simple components. Up to now, only decomposition
techniques generating a linear number of very simple components, e.g. triangles or trapezoids, have
been considered. In this paper, we will investigate the natural trade-off between the complexity of
the components and the redundancy, i.e. the number of components, with respect to its effect on
efficient query processing. In particular, we present two new decomposition methods generating
a better balance between the complexity and the number of components than previously known
techniques. We compare these new decomposition methods to the traditional undecomposed representation
as well as to the well-known decomposition into convex polygons with respect to their
performance in spatial query processing. This comparison points out that for a wide range of query
selectivity the new decomposition techniques clearly outperform both the undecomposed representation
and the convex decomposition method. More important than the absolute gain in performance
by a factor of up to an order of magnitude is the robust performance of our new decomposition
techniques over the whole range of query selectivity
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