An atlas of ultraviolet spectra of star-forming galaxies
Kinney, A. L.; Bohlin, R. C.; Calzetti, D.; Panagia, N.; Wyse, Rosemary F. G. 1993ApJS...86....5K

Data loading steps

  1. Associated literature:
    refcode 1993ApJS...86....5K
    data downloaded from CDS

  2. Read associated literature to learn about the nature of the dataset:
  3. The spectral data is contained in a single ascii file: atlas. A perl script, split_atlas.pl, is written to separate out the individual co-added ascii speactra for each object, and provide some averaged wavelength bin widths and average exposure times, in a output file called: atlas.tab. This is done by running the script in the same directory as atlas. Two sets of ascii spectra file results from this, one author version (*_AUTHOR.asc) and one NED standard (*_NED.asc).
        :~> perl split_atlas.pl
    
  4. Object names (names.txt) are extracted from table 1 (table1.txt) of the published paper, then cross-matched with the pervious data table atlas.tab using the script FINDdiff.pl:
        :~> perl ~/bin/FINDdiff.pl -keepall -m -col=1,1 -sep="\t" names.txt atlas.tab > LOG_FINDdiff_1
    
    The results are in names.txt_atlas.tab.common and any unmatched lines are reported in LOG_FINDdiff_1:
    	names.txt              atlas.tab
    	MCG6-28-44             MGC6-28-44
    	NGC4861+               NGC4861
    	TOL1924-416            TOL1924-41
    	1941-543               1942-543
    
  5. To get NED format names of galaxies, we first run nedname on the set of author given galaxy names in names.txt:
        :~> nedname names.txt names.txt.out
    
    after fixing a few typical "ESO-???" problems - e.g. ESO 296-???011 → ESO 296-IG 011, the fixed name list is exported to names-fixed.txt and we use the seekNEDnames.pl script to test the validity of these names:
        :~> perl ~/bin/seekNEDnames.pl names-fixed.txt
    
    In this case, there are 5 object names not found in NED, I used NED's near-position search to find their possible counter-part via confrimation of the current refcode being listed in as a reference to the object (this can be automated) then look through the appropiate cross-ID list to "guess" the best match in name format and grab the NEDra & NEDdec, e.g.:
            published names    closest NED name
            1050+04            CGCG 1050.4+0454
            UGC7905S           UGC 07905 NED01
            UGC8315N           UGC 08315 NED02 ?
            1350-00            CGCG 1350.2+0022
            1941-543           ESO 194103-5422.3
    
  6. Next, we rename the ascii files with the associated NED names, command list in rename.

  7. Finally, after all the metadata are collected, the content of the EXCEL file: metadata_table.xls is copied into a text file (named metadata_table.fin), used as the input to the loader script generate_spectraDB_loader.pl:
    	perl generate_spectraDB_loader.pl metadata_table.fin
    
  8. This script also generate the input file for the script which makes the previews:
    	perl generate_spectraDB_preview.pl
    
  9. Finally run script makeVOtable.pl on the NED ASCII spectra to create votable-xml files:
    	perl makeVOtable.pl *_NED.txt