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Catalogues

Catalogues

The Apertif DR1 VO data collection can also be discovered directly via ALADIN either via simple image access protocol (SIAP) or tabular access protocol (TAP). The examples shown here require the desktop version of ALADIN.

Access to catalogues through TAP is handled in a way comparable to images through SIA. Open ALADIN and on the left panel for SIAP: select Others > SIA2 > → CS → astron.nl > The VO @ASTRON SIAP Version 2. Alternatively for TAP select Others > TAP > astron.nl > The VO @ASTRON TAP service (Fig. 49). A pop→ <data collection name> (purple directory icons). A pop-up window will open. Click load, and enter a query using the Server selector (Fig. 50) or TAP access with astron.nl/tap (Fig. 51) to select the target of interest for SIAP and TAP respectively.

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Image Removed Fig. 50 ALADIN server selector panel for SIAP. Click for a bigger image.

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Image Removed Fig. 51 ALADIN TAP access panel. Click for a bigger image.

After loading, the data collection catalogues can be plotted on the main panel by selecting them first on the right panel (e.g. highlighted in blue in Figures 14 and 15) and then by selecting the regions of interest on the bottom panel as shown in Figures 14 and 15. From here the usual functionality of ALADIN can be used. Note that "in view" is clicked bu default, meaning that the source in view are being loaded by default. Also note that if the Field of View is too large, the loading may fail because of a overflow on the server side (ie the query resulted in too many results). After loading, each of the catalogue entries is superimposed on top of the HiPS image as, again, a small red circle (and again this coulour has been changed in the screen shot for contrast). You can then click the "select" button and select several sources (by drawing a rectangle around them) and the table of properties will appear beneath the HiPS. See Fig. 11 for a view of those steps.

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Image Removed Fig. 52 Example of data collection selection via SIAP in ALADIN. Click for a bigger image.

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Image Removed Fig. 53 Example of data collection selection via TAP in ALADIN. Click for a bigger image.

Images

Downloading images or cubes in ALADIN is also possible (see Fig. 54). The user will need to click on the url-link in the column access_url of the bottom panel. Then, once the image is loaded, click on the right panel as shown in Fig. 54. From here the usual functionality of ALADIN can be used.

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Image Removed Fig. 54 Example of image selected from the Apertif DR1 displayed in ALADIN. Click for a bigger image.

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Anchor aladin-tap aladin-tap Image Added Fig. 11 Aladin with LoTSS DR1 as background HiPS, superimposed the cross-matched source list. The bottom shows the properties of some of tje the sources that were manually selected.

ADQL

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In several places, ADQL was mentioned as a way to construct queries to the data and catalogues. ADQL is a query language resembling SQL, so the main concepts are familiar to those acquianted with SQL. The full  reference documentation (i.e. stnadard definition) contains all possible commands. Here we show some simple examples of table queries. Also note that TOPCAT has some built in examples implemented. Even though the ADQL commands are case insensitive, it is common practice to write them in upper case so that table data and variable values can easily been distinguished from commands.

Basic examples

The first example is simply selected all items from the lcbsw.main table:

SELECT * FROM lbcs.main

In general though, we'd like to SELECT items from a table that match certain requirements. For this we use the WHERE clause

SELECT * FROM lbcs.main WHERE baselinequal ='XXX-XXX-X'

We could add an extra requirement, for instance on the observation quality, using the AND construct:

SELECT * FROM lbcs.main WHERE baselinequal ='XXX-XXX-X' AND obsqual=15

Another useful command is DISTINCT which can be used to list distinct entries in a table. A good example of this is to list all the data collections, of which the identifier is stored in the obs_collection variable in the obscore table:

SELECT DISTINCT(obs_collection) FROM ivoa.obscore

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Export machine readable table

There are multiple ways to export a catalog of the various data products of the data release. On the vo.astron.nl pages, the results of a query can be exported to a csv file or fits table; running an empty query with a table limit of 5000 or more will return all entries.TOPCAT and the pyvo interface demonstrated above also provide functionality for exporting machine-readable files.

The ADQL form is another option, and below we provide an example query that also provides information about the calibrators used for each beam. This query is specific to the continuum_images data product but can be adapted to other (beam-based, processed) data products by replacing the table name, e.g., for polarization cubes/images use pol_cubes (see Table 10 for a full list of the available tables).

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