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| Paper: |
DAS: A Data Management System for Instrument Tests and Operations |
| Volume: |
485, Astronomical Data Analysis Software and Systems XXIII |
| Page: |
61 |
| Authors: |
Frailis, M.; Sartor, S.; Zacchei, A.; Lodi, M.; Cirami, R.; Pasian, F.; Trifoglio, M.; Bulgarelli, A.; Gianotti, F.; Franceschi, E.; Nicastro, L.; Conforti, V.; Zoli, A.; Smart, R.; Morbidelli, R.; Dadina, M. |
| Abstract: |
The Data Access System (DAS) is a 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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