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Glossary of VSA attributes

This Glossary alphabetically lists all attributes used in the VSAv20181120 database(s) held in the VSA. If you would like to have more information about the schema tables please use the VSAv20181120 Schema Browser (other Browser versions).
A B C D E F G H I J K L M
N O P Q R S T U V W X Y Z

V

NameSchema TableDatabaseDescriptionTypeLengthUnitDefault ValueUnified Content Descriptor
v_i hipparcos_new_reduction GAIADR1 V-I colour index float 8 mag   phot.color;em.opt.V;em.opt.I
va hipparcos_new_reduction GAIADR1 Reference to variability annex int 4     meta.note
Var eros2LMCSource, eros2SMCSource, erosLMCSource, erosSMCSource EROS Variability flag: 1 if potentially variable star int 4      
var hipparcos_new_reduction GAIADR1 Cosmic dispersion added (stochastc solution) float 8     stat.fit.residual
var iras_psc IRAS percent Likelihood of Variability smallint 2     meta.code;src.var
VAR_EXP_ID twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM If the source is detected as variable (that is, if VAR_FLAG is set to True), the exposure ID ('S' or 'U' followed by a three-digit number) of the exposure with the smallest Chi² probability is given here. varchar 4      
VAR_EXP_ID xmm3dr4 XMM If the source is detected as variable (that is, if VAR_FLAG is set to True), the exposure ID ('S' or 'U' followed by a three-digit number) of the exposure with the smallest Chi² probability is given here. varchar 50      
VAR_FLAG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The flag is set to True if this source was detected as variable (Chi² probability < 1E-5, see PN_CHI2PROB, M1_CHI2PROB, M2_CHI2PROB) in at least one exposure. varchar 5      
VAR_FLAG xmm3dr4 XMM The flag is set to 1 if this source was detected as variable (Chi² probability < 1E-5, see PN_CHI2PROB, M1_CHI2PROB, M2_CHI2PROB) in at least one exposure. bit 1      
var_flag combo17CDFSSource COMBO17 variability flag (0=not variable); flag only set for objects which are detected with high S/N and which show clear variability between different observing runs (magnitude difference greater 0.15 mag, at least one magnitude has to be measured with 10 sigma, difference has to be at least 6 sigma tinyint 1      
var_flg allwise_sc2 WISE Variability flag. The variability flag is a four-character string, one character per band, in which the value for each band is related to the probability that the source flux measured on the individual WISE exposures was not constant with time. The probability calculation uses the standard deviation of the single exposure flux measurements, w?sigp1, as well as the band-to-band flux correlation significance, q12,q23,q34. CAUTION: Estimation of flux variability is unreliable for sources that are extended (ext_flg>0), and sources whose measurements are contaminated by image artifacts in a band (cc_flags[b] != '0'). varchar 4      
The probability is computed for a band only when there are at least six single-exposure measurements available that satisfy minimum quality criteria. A value of "n" in a band indicates insufficient or inadequate data to make a determination of possible variability. Values of "0" through "9" indicate increasing probabilities of variation. Values of "0" through "5" are most likely not variables. Sources with values of "6" and "7" are likely flux variables, but are the most susceptible to false-positive variability. Var_flg values greater than "7" have the highest probability of being true flux variables in a band.
var_flg_ALLWISE ravedr5Source RAVE probability that flux varied in any band greater than amount expected from unc.s varchar 5     meta.code
VAR_INST_ID twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM If the source is detected as variable (that is, if VAR_FLAG is set to True), the instrument ID (PN, M1, M2) of the exposure given in VAR_EXP_ID is listed here. varchar 2      
VAR_INST_ID xmm3dr4 XMM If the source is detected as variable (that is, if VAR_FLAG is set to True), the instrument ID (PN, M1, M2) of the exposure given in VAR_EXP_ID is listed here. varchar 50      
variabilityTable Programme VHSDR1 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSDR2 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSDR3 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSDR4 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20120926 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20130417 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20150108 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20160114 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20160507 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20170630 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20171207 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VHSv20180419 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEODR2 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEODR3 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEODR4 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEODR5 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEOv20100513 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIDEOv20111208 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGDR2 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGDR3 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGDR4 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20110714 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20111019 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20130417 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20150421 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20151230 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20160406 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20161202 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20170715 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VIKINGv20181012 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCDR1 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCDR3 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCDR4 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20110816 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20110909 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20120126 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20121128 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20130304 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20130805 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20140428 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20140903 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20150309 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20151218 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20160311 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20160822 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20170109 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20170411 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20171101 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20180702 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VMCv20181120 Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VSAQC Table name of merged variable sources varchar 64   'NONE' ??
variabilityTable Programme VVVDR4 Table name of merged variable sources varchar 64   'NONE' ??
variableClass videoVariability VIDEODR2 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass videoVariability VIDEODR3 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass videoVariability VIDEODR4 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass videoVariability VIDEODR5 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass videoVariability VIDEOv20100513 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass videoVariability VIDEOv20111208 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGDR2 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGDR3 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGDR4 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20110714 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20111019 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20130417 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20140402 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20150421 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20151230 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20160406 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20161202 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20170715 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vikingVariability VIKINGv20181012 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCDR1 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCDR2 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCDR3 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCDR4 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20110816 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20110909 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20120126 Classification of objects across all bands. int 4   -99999999  
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20121128 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20130304 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20130805 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20140428 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20140903 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20150309 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20151218 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20160311 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20160822 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20170109 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20170411 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20171101 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20180702 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vmcVariability VMCv20181120 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableClass vvvVariability VVVDR4 Classification of objects across all bands. int 4   -99999999 meta.code.class
This gives an overall classification. Currently the weighted intrinsicRMS/expectedRMS (wsrms) is calculated across all bands, where the weighting is directly proportional to the number of good observations in each band, where any bands with <5 observations have w=0 and the band with the most observations has a weighting of 1. If wsrms>3, then variableClass=1 (i.e. the source is variable), else variableClass=0. In the future, the classification will take into account other statistics, such as correlations between bands and will also include motion and skew, and will not be limited to 0 or 1.
variableType vmcVariablesType VMCDR3 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCDR4 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20121128 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20140428 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20140903 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20150309 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20151218 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20160311 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20160822 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20170109 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20170411 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20171101 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20180702 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
variableType vmcVariablesType VMCv20181120 Type of variable as defined by VMC team varchar 32     meta.code.class;src.var
varID vmcCepheidVariables VMCv20121128 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20140428 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20140903 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20150309 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20151218 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20160311 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20160822 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20170109 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20170411 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20171101 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20180702 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables VMCv20181120 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables, vmcEclipsingBinaryVariables, vmcRRlyraeVariables VMCDR4 UID of VMC variables bigint 8     meta.id;meta.main
varID vmcCepheidVariables, vmcVariablesType VMCDR3 UID of VMC variables bigint 8     meta.id;meta.main
VbMag combo17CDFSSource COMBO17 Absolute restframe magnitude in Bessell V (calculated from redshifted best_fit template, depending on redshift and filter extrapolation outside the COMBO-17 filter set can be necessary, only calculated for objects classified as galaxies) real 4 mag    
vc twomass_sixx2_xsc TWOMASS visual verification score for source smallint 2      
vc twomass_xsc TWOMASS visual verification score for source. smallint 2     meta.code
vegaToAB Filter VHSDR1 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSDR2 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSDR4 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20120926 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20130417 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20150108 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20160114 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20160507 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20170630 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20171207 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VHSv20180419 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEODR2 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEODR3 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEODR4 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEODR5 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEOv20100513 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIDEOv20111208 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGDR2 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGDR3 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGDR4 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20110714 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20111019 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20130417 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20150421 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20151230 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20160406 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20161202 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20170715 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VIKINGv20181012 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCDR1 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCDR3 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCDR4 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20110816 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20110909 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20120126 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20121128 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20130304 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20130805 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20140428 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20140903 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20150309 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20151218 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20160311 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20160822 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20170109 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20170411 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20171101 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20180702 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VMCv20181120 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VSAQC The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter VVVDR4 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
vegaToAB Filter, FilterSections VHSDR3 The constant to convert Vega magnitudes to AB magnitudes. real 4 mag -0.9999995e9  
versionDate sage_lmcIracSource, sage_lmcMips160Source, sage_lmcMips24Source, sage_lmcMips70Source SPITZER Date catalogue was produced in the following format, "mon dd yyyy", "Dec 5 2007" varchar 12      
versionDate sage_smcIRACv1_5Source SPITZER Date catalog was produced in the following format, "mon dd yyyy", "Dec 5 2007" varchar 12      
versionNo sage_lmcIracSource, sage_lmcMips160Source, sage_lmcMips24Source, sage_lmcMips70Source, sage_smcIRACv1_5Source SPITZER Version number assigned by MIPS/IRAC pipeline team real 4      
versionNum Multiframe VHSDR1 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSDR2 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSDR3 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSDR4 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20120926 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20130417 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20140409 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20150108 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20160114 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20160507 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20170630 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20171207 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VHSv20180419 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEODR2 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEODR3 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEODR4 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEODR5 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEOv20100513 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIDEOv20111208 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGDR2 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGDR3 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGDR4 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20110714 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20111019 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20130417 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20140402 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20150421 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20151230 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20160406 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20161202 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20170715 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VIKINGv20181012 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCDR1 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCDR2 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCDR3 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCDR4 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20110816 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20110909 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20120126 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20121128 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20130304 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20130805 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20140428 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20140903 a version number for this frame (if available) real 4   -0.9999995e9 meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20150309 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20151218 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20160311 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20160822 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20170109 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20170411 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20171101 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20180702 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VMCv20181120 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum Multiframe VVVDR4 a version number for this frame (if available) varchar 8   NONE meta.id
For deep stacks and mosaics produced in Edinburgh, (frameType=deep%stack, fileName=eYYYYMMDD_%) this refers to the database release number. For all other files, the versNum refers to the CASU pipeline version number.
versionNum ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC a version number for this frame (if available) real 4   -0.9999995e9 meta.id
versionNum vikingMapRemeasAver VIKINGZYSELJv20160909 Version number of the catalogue smallint 2      
versionNum vikingMapRemeasAver VIKINGZYSELJv20170124 Version number of the catalogue smallint 2      
versionNum vikingMapRemeasurement VIKINGZYSELJv20160909 Version number of the catalogue {catalogue extension keyword:  VERSNUM} smallint 2   -9999  
versionNum vikingMapRemeasurement VIKINGZYSELJv20170124 Version number of the catalogue {catalogue extension keyword:  VERSNUM} smallint 2   -9999  
versNum AstrCalVers VHSDR1 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSDR2 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSDR3 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSDR4 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20120926 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20130417 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20150108 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20160114 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20160507 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20170630 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20171207 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VHSv20180419 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEODR2 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEODR3 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEODR4 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEODR5 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEOv20100513 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIDEOv20111208 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGDR2 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGDR3 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGDR4 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20110714 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20111019 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20130417 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20150421 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20151230 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20160406 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20161202 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20170715 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VIKINGv20181012 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCDR1 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCDR3 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCDR4 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20110816 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20110909 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20120126 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20121128 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20130304 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20130805 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20140428 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20140903 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20150309 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20151218 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20160311 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20160822 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20170109 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20170411 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20171101 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20180702 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VMCv20181120 Version number of current astrometric solution int 4     meta.software
versNum AstrCalVers VVVDR4 Version number of current astrometric solution int 4     meta.software
versNum ExternalProductCatalogue VHSDR3 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSDR4 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20150108 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20160114 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20160507 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20170630 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20171207 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VHSv20180419 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIDEODR4 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIDEODR5 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGDR4 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20150421 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20151230 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20160406 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20161202 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20170715 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VIKINGv20181012 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCDR3 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCDR4 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20140428 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20140903 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20150309 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20151218 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20160311 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20160822 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20170109 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20170411 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20171101 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20180702 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VMCv20181120 Version of file sent from survey team int 4      
versNum ExternalProductCatalogue VVVDR4 Version of file sent from survey team int 4      
versNum PhotCalVers VHSDR2 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSDR3 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSDR4 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20120926 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20130417 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20150108 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20160114 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20160507 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20170630 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20171207 the version number of the calibration int 4     meta.software
versNum PhotCalVers VHSv20180419 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEODR2 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEODR3 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEODR4 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEODR5 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEOv20100513 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIDEOv20111208 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGDR2 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGDR3 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGDR4 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20110714 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20111019 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20130417 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20150421 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20151230 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20160406 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20161202 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20170715 the version number of the calibration int 4     meta.software
versNum PhotCalVers VIKINGv20181012 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCDR1 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCDR3 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCDR4 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20110816 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20110909 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20120126 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20121128 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20130304 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20130805 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20140428 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20140903 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20150309 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20151218 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20160311 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20160822 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20170109 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20170411 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20171101 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20180702 the version number of the calibration int 4     meta.software
versNum PhotCalVers VMCv20181120 the version number of the calibration int 4     meta.software
versNum PhotCalVers VVVDR4 the version number of the calibration int 4     meta.software
versNum PhotCalVers, PreviousMFDZP VHSDR1 the version number of the calibration int 4     meta.software
VF_D combo17CDFSSource COMBO17 flux in filter V in run D (07.10.-22.10.1999) float 8      
vFlag rosat_bsc, rosat_fsc ROSAT variability flag varchar 1     meta.code
vigF rosat_fsc ROSAT vignetting factor float 8     instr.param
vigf rosat_bsc ROSAT vignetting factor float 8     instr.param
viracID vvvParallaxCatalogue VVVDR4 unique source identifier in VIRAC catalogue. {catalogue TType keyword: sourceid} bigint 8   -99999999 meta.id;meta.main
viracID vvvProperMotionCatalogue VVVDR4 unique source identifier from VIRAC catalogue. {catalogue TType keyword: sourceid} bigint 8   -99999999 meta.id;meta.main
visibility_periods_used gaia_source GAIADR2 Number of visibility periods uased in the astrometric solution smallint 2     meta.number
vistaRunNo Multiframe VHSDR1 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSDR2 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSDR3 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSDR4 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20120926 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20130417 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20140409 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20150108 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20160114 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20160507 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20170630 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20171207 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VHSv20180419 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEODR2 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEODR3 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEODR4 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEODR5 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEOv20100513 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIDEOv20111208 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGDR2 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGDR3 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGDR4 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20110714 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20111019 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20130417 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20140402 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20150421 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20151230 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20160406 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20161202 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20170715 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VIKINGv20181012 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCDR1 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCDR2 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCDR3 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCDR4 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20110816 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20110909 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20120126 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20121128 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20130304 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20130805 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20140428 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20140903 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20150309 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20151218 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20160311 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20160822 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20170109 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20170411 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20171101 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20180702 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VMCv20181120 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo Multiframe VVVDR4 Original VISTA run number (from filename) int 4   -99999999 meta.bib
vistaRunNo ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC Original VISTA run number (from filename) int 4   meta.bib
VjMag combo17CDFSSource COMBO17 Absolute restframe magnitude in Johnson V (calculated from redshifted best_fit template, depending on redshift and filter extrapolation outside the COMBO-17 filter set can be necessary, only calculated for objects classified as galaxies) real 4 mag    
Vmag mcps_lmcSource, mcps_smcSource MCPS The V band magnitude real 4 mag    
vMag ukirtFSstars VIDEOv20100513 V band total magnitude real 4 mag -0.9999995e9 phot.mag
vMag ukirtFSstars VIKINGv20110714 V band total magnitude real 4 mag -0.9999995e9 phot.mag
Vmag_APASSDR9 ravedr5Source RAVE V magnitude from APASSDR9 real 4 mag   phot.mag;em.opt.V
VmagOGLEII spitzer_smcSource SPITZER The OGLEII V band magnitude. real 4 mag    
vMeanMag vmcCepheidVariables VMCDR3 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCDR4 Mean V band magnitude {catalogue TType keyword: Vmag} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20121128 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20140428 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20140903 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20150309 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20151218 Mean V band magnitude {catalogue TType keyword: V} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20160311 Mean V band magnitude {catalogue TType keyword: Vmag} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcCepheidVariables VMCv20160822 Mean V band magnitude {catalogue TType keyword: Vmag} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCDR4 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20160822 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20170109 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20170411 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20171101 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20180702 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vMeanMag vmcRRlyraeVariables VMCv20181120 Mean V band magnitude from OGLE-3 survey {catalogue TType keyword: VMAG} real 4 mag -0.9999995e9 phot.mag;stat.mean;em.opt.V
vr_m_opt twomass_psc TWOMASS Visual or red magnitude of the associated optical source. real 4 mag   phot.flux
vt_mag tycho2 GAIADR1 Tycho2 VT magnitude real 4 mag   phot.mag;em.opt.V
VTmag_TYCHO2 ravedr5Source RAVE magnitude from TYCHO2 real 4 mag VT   phot.mag;em.opt.V



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20/11/2018