Radio Astronomy Data Model for Single-Dish Multiple-Feed Telescopes, and Robledo Archive Architecture

Radio Astronomy Data Model for

Single-Dish Multiple-Feed Telescopes,

and Robledo Archive Architecture

Juan de Dios Santander (IAA-CSIC) Emilio García (IAA-CSIC)

José Francisco Gómez (IAA-CSIC) Lourdes Verdes-Montenegro (IAA-CSIC)

Stephane Leon (IRAM) Olga Suárez (LAEFF-INTA) Oscar Morata (LAEFF-INTA) Enrique Solano (LAEFF-INTA)

NOTA DE PRENSA

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DEPARTAMENTO DE COMUNICACIÓN

BARCELONA MADRID VALENCIA

934 426 576 915 855 243 963 622 757

[email protected] [email protected] [email protected] Las conclusiones se publican mañana, jueves, en ‘Nature’

El CSIC colabora en el hallazgo del nacimiento del agujero negro más antiguo conocido

! Está situado a una distancia de 13.000 millones de años luz de la Tierra y fue localizado en septiembre del año pasado

! El hallazgo aportará nuevos datos sobre la muerte de las primeras estrellas, según los expertos

Madrid, 8 de marzo, 2006 Un equipo internacional, con participación de nueve investigadores del Instituto de Astrofísica de Andalucía, perteneciente al Consejo Superior de Investigaciones Científicas (CSIC), ha descubierto el nacimiento del agujero negro más antiguo conocido, GRB 050904, ubicado en los confines del Universo, a una distancia de 13.000 millones de años luz de la Tierra. Las conclusiones del hallazgo, coordinado por científicos de la Universidad de Carolina del Norte (EE.UU.) se publican mañana, jueves en la revista Nature.

El responsable del equipo español, el investigador del CSIC Alberto Castro-Tirado, asegura que el hallazgo aportará nuevos datos sobre la muerte de las primeras estrellas del universo primitivo, estrellas muy masivas, conocidas como Población III. Este astrofísico del CSIC aporta una de las claves del descubrimiento: “Durante el nacimiento del agujero negro se produjo una explosión que liberó en pocos minutos más de un quintillón de veces la energía que se puede liberar en una explosión nuclear controlada”.

Entre las aportaciones futuras del hallazgo, Castro-Tirado destaca que “la posibilidad de captar el alumbramiento de agujeros negros en los confines del Universo abre la posibilidad de estudiar regiones remotas y primitivas del

NOTA DE PRENSA

La atmósfera de Marte, a debate en Granada Del 27 de febrero al 3 de marzo tendrá lugar, en el Palacio de Congresos y Exposiciones de Granada, el Second Workshop on Modelling and Observations of the Martian

Atmosphere (Segundo Taller sobre los Modelos y Observaciones de la Atmósfera de

Marte)

Tras el éxito del primero, hace tres años, la semana próxima se celebra el Second Workshop

on Modelling and Observations of the Martian Atmosphere, organizado por el Instituto de

Astrofisica de Andalucia (IAA-CSIC), el Laboratoire de Meteorologie Dinamique (CNRS) y la Universidad de Oxford, financiado por la Agencia Espacial Europea (ESA) y el Centro de Estudios Espaciales francés (CNES).

A lo largo de una semana se reunirán, en Palacio de Congresos de Granada, más de un centenar de científicos de todo el mundo especialistas en la atmósfera de Marte para discutir los últimos avances conseguidos en el conocimiento de la atmósfera del Planeta Rojo, bien a través de las observaciones de las sondas que actualmente se hallan en órbita alrededor del planeta, o bien a través de modelos teóricos. Recibirán especial atención las últimas observaciones realizadas por la sonda europea Mars Express, que han permitido profundizar en aspectos tales como los vientos marcianos o el comportamiento del polvo o el hielo, esenciales para comprender las similitudes y diferencias de esta atmósfera con la de la Tierra. También se presentarán resultados relacionados con la posibilidad de un pasado remoto de Marte en el que el agua líquida fuera abundante –lo que pudo dar lugar a glaciares y otros fenómenos hidrológicos–, o incluso con sus potenciales consecuencias sobre la habitabilidad pasada del planeta.

El fin último de esta reunión consiste en poner en común los distintos avances que en los últimos años se han producido en este campo de la Astronomía y contribuir a mejorar nuestro conocimiento sobre el comportamiento de todo el Sistema Solar.

Más información: http://www.iaa.es/~valverde/Granada2006/LOC.html

Atención a los medios: Miguel Ángel López Valverde, Tel. 958 12 13 11. [email protected]

Talk Overview

Introduction

Radio Astronomy DAta Model for Single-dish multiple-feed telescopes: RADAMS

DSS-63 Antenna

RADAMS Entities & Relationships RADAMS Workflow

AMIGA

Analysing the insterstellar Medium of Isolated GAlaxies

Exhaustive multi-wavelength study of a complete sample of

~1000 isolated galaxies, and public galaxy catalogue at the

IAA (CSIC).

Optical, Ha, and IR luminosities, radio-continuum emission, and atomic and molecular gas contents compiled from

literature or derived from our own observations, together with POSS-I and POSS-II digitized images.

AMIGA+

AMIGA archive exploitation

Extension of the AMIGA archive to sub-mm wavelengths Development of radio-astronomical archives and Virtual Observatory integration

Collaborations already in place: DSS-63, IRAM 30m Gaining expertise for: SMA and ALMA archives

AMIGA+ & Radio-VO

So, we’re doing VO archives. Why? Because VO: Enables new science

Allow for easier Dissemination & Exploitation of data archives Can help in providing useful data for non–radio-astronomers Besides…

We’ve gathered some experience

Virtual Observatory (VO)

Definition

Set of common practices and data models that allow for easy discoverability of interoperable data-sets, with unified

description by means of a common data model. And what is a data model?

Description of the set of entities needed for information

storage in a particular field, specifying both the data being stored, and the relationships between them.

Virtual Observatory (VO)

Common data interchange format (XML), protocols (Web Services: SOAP, XML-RPC), and data models

XML-based FITS replacement: VOTABLE

Web-Services based common query techniques: SIAP, SSAP… XML metadata data-set description by standardised data models (Characterisation, STC, Provenance, Curation…)

Radio-VO Data Models

Lamb and Power’s Raw Radio-Telescope DM IVOA note ATCA’s Australian Telescope Online Archive DM

VO compliance through interfaces

No further definition of IVOA standards No standard single-dish DM

Radio Astronomy DAta Model for

Single-dish multiple-feed telescopes:

Target: DSS-63 70-m antenna

42” HPBW, 0.7 K/Jy, 49% max aperture efficiency, parabolic Cassegrain antenna LCP or RCP, cooled HEMT amplifier, K-band (22 GHz) receiver 384-sample, 2-16 MHz bandwidth spectrometer

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Sources: IVOA Work

IVOA Working Groups mainly dedicated to Data Modelling Sources for this Data Model:

Data Model for Observation

McDowell, Bonnarel et al., IVOA Data Model WG Internal Draft

Data Model for Astronomical Dataset Characterisation

McDowell, Bonnarel et al., IVOA Data Model WG Note

IVOA Spectral Data Model

McDowell, Tody et al., IVOA Data Model WG Working Draft

IVOA Data Model for Raw Radio Telescope Data

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

Data Model for Dataset

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution

RADAMS Logic Structure

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Detail

36 CHAPTER 7. DE TAILED DESCRIPTION OFRAD AMCLAS SES Table 7.1: AxisFram e.Spatial metadata. FITS Attribute Keyword UCD Descript ion axisNam e assign meta.id; meta.main Axis nam e. calibrat ionStatus assign obs.calib; meta.code Calibrati onstatus froma con-trolled vocabul ary: uncal-ibrated , calibrated , rela-tive a_{, normalized} b_. ucd assign meta.ucd; meta.main Main UCD forthe axis. unit assign meta.unit; meta.main Main uni ts forthe axis. refPos assign meta.ref; meta.id Identificat ionof t heorigi n p o-sition within the spaceR ef-Frame from a control led vocab-ulary; Se e Space-Time Co ordi -nateData Model [13]. spaceR efFram e WCSNAME or RADESYS pos.frame; meta.id Identificat ion of the reference system from a c ontroll ed vo-cabulary ; seeSpace-Ti me Co-ordinate DataMo del[13] : FK4, FK5, ELLIPTIC . . . coordE quinox assign pos; time.equinox Equinox (only if needed) . epoch assign pos; time.epoch Epoch (onl y ifneeded). independe ntAxis assign pos; obs.param; meta.code Boolean flag indicati ng whether the axis is indep en-dent of therest or not. unders amplingStat us assign pos; obs.param; meta.code Boolean flag indicati ng whether thedata aresam pled in this ax is ornot . regularSt atus assign pos; obs.param; meta.code Boolean flag used in cas e of sam pled dat a, indi cating whether sampling is regul ar or not. a_relative refers t o calibr ateddata , except foran additive or multi plicative constan t. b_normalized refers to dimens ionless quantities , such as thoseresul tingfrom thedivi sion between twocom mensurabl e dataset s. 7.5. PACKAGING 61

Table 7.40: Calibration metadata

a_. FITS Attribute Keyword UCD Description timestamp

DATE-RED obs.param;_time.epoch

Timestamp for the

calibration step beingperformed.

parameter.name

assign obs.calib;_obs.param; meta.id

Keyworddefining the

parameter that we will characteri

se with the remaining attributes.

parameter.type

assign obs.calib;_obs.param; meta.code

Type of calibration

parameter used, from a controlled

vo-cabulary: additive , factor, polynomial, exponential, logarithmic. parameter.value

assign obs.calib;_obs.param; meta.number

Value for the main

calibra-tion parameter, where

parame-ter.type isnot polynomial

.

parameter.sigma

assign obs.calib;_obs.param; meta.number

Value of sigma, for

exponential calibrations.

parameter.calCoeff.[n]

assign obs.calib;_obs.param; meta.number

nth degree coefficient

for a polynomial calibration

parame-ter; polynomial degree

is derived from themaximum

n. a_{It is} mandatory that at least one [parameter.name, parameter.type, parameter.value]

triplet appears, with

fluxScale as param

eter.name, and one of

antennaTemperature

, mbBrightnessTemperature

, or S nu as the param

eter.value, with a

parameter.type of string . Observation • Target.Name • Target.Description • Target.Class • Target.Pos • Target.spectralClass • Target.redshift.statError • Target.redshift.Confidence Target

Figure 7.9: Target data

model.

order to find a maser, bu

t that Target will be most

likely includedwithin an Astronomicalobject, such

as a planetary nebula, ass

ociated to that Target.

7.5 Packaging

The Packaging class has to

deal with how different

pieces of data will be

presented. For instance,

if we wantedto retrieve data

belonging to the maser 60 CHAPTER 7. DETAILED DESCRIPTION OF RAD AM CLAS SES Table 7.39:

Processing Step_metadat a. FITS Attribute Keyword _UCD Descri ption timestam_p DATE-RED obs.param; time.epoch Timestam_{p for}

the pro_cessing step being performed. type assign obs.param; meta.code Type _of processing applied to source data; comes from _a controlled _vocabul ary: unproc-essed, _{noiseWeightedAverage} , nonWeightedAverage . softwareP_ackage assign meta.software; meta.id Software package

used for _data processing;

should _{come from} a contro

lled voca_bulary:

CLASS, AIPS, AIPS++ , CASA, MOPSIC , GILDAS

, MIRA, MIR_{, other} . In the case of

other, the_actual

package that was _{used shoul}

d be added as a param

eter, with _param -eter.nam

e as softwarePackage and the _param

eter.value _{as the} package_name. param eter[n].nam_e assign obs.param; meta.code Additional processing _param eter name, whose

value will_{be in} pa-rameter.val_{ue; eventual}

ly, we will have a con trolled list of possible param eter.nam e values. param eter[n].type _assign obs.param; meta.code From a control led vocabul ary: integer , float , string . . . _At least all of_{FITS data}

types shoul_d be presen_t. param eter[n].val_ue assign obs.param a

Value for_{the param}

eter indi_cated by param_eter.name.

a

The final

UCD to m_{ark param}

eter[n].val ue will be cal culated whe n writing the VOTabl_e, as it dep ends on_param eter.type;_{it will be} obs.param; meta.number

most of the_{time, but} it could beobs.param; meta.name or obs.param; meta.code , dependi ng on the context.

Archive Infrastructure

Database (metadata) Queries SkyNode ConeSearch SSAP Control System Archive

Infrastructure Raw Data Storage

Instrument Archive Backend Archive Services Interfaces

Aladin, Sesame, NED…

SOAP

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

IVOA Standards Review & Compilation

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

IVOA Standards Review & Compilation

Detailed Metadata for DSS-63 Exhaustive UCD lists

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage VOpack

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage VOpack Calibration, Processing

RADAMS Main Contribution

Observation ObsData Characterization Provenance Curation Policy Packaging Target Accuracy Sensitivity Precision Resolution Coverage VOpack Calibration, Processing User Roles, Permissions

Conclusions &

Future Work

Conclusions

Many IVOA standards are still under development (specially for radio-astronomy) but usable ➞ Development of RADAMS

Detailed telescope DM as a result of standards’ review

First definition of Policy, Provenance and Packaging elements Initial archive infrastructure & workflow design

Colophon: archival initiatives drive definition & adoption of new IVOA standards

Future Work

Submission of RADAMS to IVOA Radio IG as IVOA Note VOPack proposal to IVOA DAL WG

Implementation of RADAMS for DSS-63 Extension of RADAMS for IRAM 30m

Definition of data models for additional instruments & Integration with IRAM’s NCS

¡Gracias!