DAS: a data management system for instrument tests and operations
The Data Access System (DAS) is a metadata and data management software system, providing a reusable solution for the storage of data acquired both from telescopes and auxiliary data sources during the instrument development phases and operations. It is part of the Customizable Instrument WorkStatio...
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Zusammenfassung: | The Data Access System (DAS) is a metadata and data management software
system, providing a reusable solution for the storage of data acquired both
from telescopes and auxiliary data sources during the instrument development
phases and operations. It is part of the Customizable Instrument WorkStation
system (CIWS-FW), a framework for the storage, processing and quick-look at the
data acquired from scientific instruments. The DAS provides a data access layer
mainly targeted to software applications: quick-look displays, pre-processing
pipelines and scientific workflows. It is logically organized in three main
components: an intuitive and compact Data Definition Language (DAS DDL) in XML
format, aimed for user-defined data types; an Application Programming Interface
(DAS API), automatically adding classes and methods supporting the DDL data
types, and providing an object-oriented query language; a data management
component, which maps the metadata of the DDL data types in a relational Data
Base Management System (DBMS), and stores the data in a shared (network) file
system. With the DAS DDL, developers define the data model for a particular
project, specifying for each data type the metadata attributes, the data format
and layout (if applicable), and named references to related or aggregated data
types. Together with the DDL user-defined data types, the DAS API acts as the
only interface to store, query and retrieve the metadata and data in the DAS
system, providing both an abstract interface and a data model specific one in
C, C++ and Python. The mapping of metadata in the back-end database is
automatic and supports several relational DBMSs, including MySQL, Oracle and
PostgreSQL. |
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DOI: | 10.48550/arxiv.1405.7584 |