DaCHS 1.1 released

Today, I have released DaCHS 1.1, with the main selling point that DaCHS should now speak TAP 1.1 (as defined in the current draft).

First off, if you’re not yet on DaCHS 1.0, please read the corresponding release article before upgrading.

As usual, the general upgrading instructions are available in the operator’s guide (in short: do a dachs val ALL before the Debian upgrade). This time, I’d recommend to use the opportunity to upgrade your underlying server to stretch if you haven’t done so already. If you do that, please have a look at hints on postgres upgrades. Stretch comes with postgres 9.6 (jessie: 9.4). Postgres upgrades are generally safe, but please take a dump before migrating anyway.

So, with this out of the way, here’s a short list of the major changes from DaCHS 1.0 to DaCHS 1.1:

    • DaCHS now officially requires python 2.7. If this really is a problem for you, please shout – if wouldn’t be hard to maintain 2.6 compatibility, but by now we feel there’s no reason to bother any more.
    • Now supporting TAP 1.1; in particular, TOP n doesn’t trump MAXREC any more, and it doesn’t affect OVERFLOW indication, which may break things that used TOP to override DaCHS’ default TAP match limit of 2000. Also, TAP_SCHEMA is updated (this happens as a side effect of dachs upgrade).
    • Now serialising spoint, scircle, and friends to DALI 1.1 xtypes (timestamp, point, polygon, circle). Fields explicitly marked with adql:POINT or adql:REGION will still be serialised to STC-S. Do this only if you have no choice (DaCHS has this for obscore and epntap s_region right now).

9

    • The output column selection is sanitised. This may make for slight changes in service responses, in particular in VOTable formats. See Output Tables in the reference documentation for details if you think this might hit you.
    • DaCHS no longer comes with an outdated version pyparsing and instead uses what’s installed on the system. The Debian package further re-uses additional system resources if available (rjsmin, jquery).
    • DaCHS now tries a bit harder to come up with sensible names for SODA result files.
    • map/@source is no longer limited to identifier-like strings; any key that’s in your source is fair game.

9

  • For incremental imports with data that’s updated now and then, there’s now ignoreSources/@fromdbUpdating.
  • Relative imports from custom code (“import foo” in a custom core, for instance, getting res/foo.py) no longer work. See Importing Modules in the reference documentation for details.
  • This release fixes a severe bug in the creation of obscore metadata from SSAP tables. If you use //obscore#publishSSAPHCD or //obscore#publishSSAPMIXC mixins, update the obscore definitions by running dachs imp -m <rdid>, followed by dachs imp //obscore (the latter is only necessary once at the end).
  • You can now define a footer.html template that’s added at the foot of the main page content – with a bit of CSS magic, this lets you overwrite almost anything on DaCHS HTML pages.

As always, please complain early if something breaks for you; our regression tests can only cover so much. In particular, our support list is there for you.

Update (2017-12-06): In particular on jessie, you may
see that all DaCHS packages are being held back. To resolve this
situation, manually say apt-get install python-gavoutils<br />
python-gavostc
.

Register your stuff with purx!

TOPCAT screenshot
If you open the TAP dialog of TOPCAT, what you see is Registry content.

The VO Registry lets people find astronomical resources (which is jargon for “dataset, service, or stuff“). Currently, most of its users don’t even notice they’re using the Registry, as when TOPCAT just magically lists what TAP services are available (image above) – but there are also interfaces that let you directly interact with the registry, for instance GAVO’s WIRR service or ESAVO’s Registry Search.

Arguably, the usefulness of the Registry scales with its completeness. With sufficient completeness, the domain-specific, structured metadata will also make it interesting for generic discovery of astronomical data; in a quip, looking for UCDs in google will never work quite well – and without that, it’s hard to find things with queries like „radio fluxes of early-type stars”.

Either way: If you have a data set or a service dealing with astronomy, it’d be great if you could register it. To do this, so far you either had to set up a publishing registry, which is nontrivial even if you have a software that natively speaks a protocol called OAI-PMH (DaCHS does, but most other publishing suites don’t) or you could use one of two web interfaces to define your resource (notes for a talk on this I gave in 2016).

Neither of these options is really attractive if you publish only a few resources (so the overhead of running a publishing registry looks excessive) that change now and then (so using a web browser to update the resource records again and again is tedious). Therefore, GAVO has developed purx, the publishing registry proxy. We’ve officially announced it during the recent Southern Spring Interop in Santiago de Chile (Program), and the lecture notes for that talk are probably a good introduction to what this is about.

If you’re running VO services and have not registered them so far, you probably want to read both these notes and the service documentation. If, on the other hand, you just have a web-published directory of files or a browser-based service, you probably can skip even that. Just grab a sample record (use the one for a simple browser service in both cases) and adapt it to what’s fitting for your website. Then put the resulting file online somewhere and paste the URL of that location on purx’ enrollment service. In case you’re uncertain about some of the terms in the record, perhaps our crib sheet for metadata we ask our data providers for will be helpful.

There’s really no excuse any more for not being in the Registry!

DaCHS 1.0 released

Today, I have released DaCHS 1.0 – after long years in the 0.9 range, it was finally time to do so. The jump in the major version number was an opportunity to remove some cruft that had accumulated over the years; this, on the other hand, means that if you’re running DaCHS, you should watch the upgrade and see if anything broke later (this might be the perfect time to add regression tests to your RDs).

The changelog is below, but before that a bold-faced warning:

Install python-astropy before upgrading

This is because DaCHS now depends on astropy rather than pyfits and pywcs. The latter is no longer part of Debian stretch, and so we made the jump to astropy (that would have been due during Debian stretch’s lifetime anyway) even before 1.0.

Now, Debian holds back packages with new dependencies, and due to the way DaCHS’ modules are distributed, DaCHS will break when some of its packages are held back. The symptom is error messages like “pkg_resources.DistributionNotFound: gavodachs==0.9.8”. If you already see those, a apt-get dist-upgrade should get you in business again.

With this out of the way, here is an annotated log of the major changes:

  • DaCHS’ main entry point is now actually called dachs (i.e., call dachs imp q and such in the future). gavo will work as an alias for quite a while to come, though, and it’s still used a lot in the documentation (you’re welcome to fix this: the docs are maintained on github).
  • Hopefully more useful manpage (of course, also available with man dachs) – have a peek!
  • UWS support is now at version 1.1 (i.e., there’s creationDate in jobs, filters in the joblist, and slow polling).
  • Added “declarative” licenses. Please read the Licensing chapter in the tutorial and slap licenses on your data.
  • Now using astropy.wcs instead of pywcs, and astropy.io.fits instead of pyfits. The respective APIs have, unfortunately, changed quite a bit. If you’re using them (e.g., in processors), you’ll have to change your code; it’s unlikely services are impacted at runtime. (see also How do I update my code?).
  • Removed the //epntap#table-2_0mixin. Use
    //epntap2#table-2_0 instead (sorry).
  • Removed sdmCore (use Datalink/SODA instead); the SODA procs in //datalink are also gone, use the ones from //soda instead (sorry, SODA development has been difficult on the IVOA level).
  • Removed imp -u flag and the corresponding updateMode parse option. If you used that or the uploadCore, just mark the DDs involved with updating="True" instead.
  • Massive sanitation of input parameter processing. If you’ve been using inputTable, inputDD, or have been doing creative things with inputKeys, please check the respective services carefully after upgrading. See also DaCHS’ Service Interface in the reference documentation. The most user-visible change in this department is if you’ve been using repeated parameters to fill array-valued inputs. That’s no longer allowed; if you actually must have this kind of thing, you’ll need a custom core and must fill the arrays by hand.
  • In DaCHS’ SQL interface, tuples now are matched to records and lists to arrays (it was the other way round before). If while importing you manually created tuples to fill to array-like columns, you’ll have to make lists from these now.
  • rsc.makeData or rsc.TableForDef no longer automatically make connections when used on database tables. You must give them explicit connection arguments now (with base.getTableConn() as conn:).
  • logo_tiny.png and logo_big.png are now ignored by DaCHS, all logos spit out by it are now based on logo_medium.png, including, if not overridden, the favicon (that you will now get if you have not set it before).
  • Removed (probably largely unused) features editCore, SDM2 support, pkg_resource overrides, simpleView, computedCore.
  • Removed the argparse module shipped with DaCHS. This breaks compatibility with python 2.6 (although you can still run DaCHS with a manually installed argparse.py in 2.6).

Even though that’s quite a mouthful, I expect few people will actually experience breaking services. If you do, by all means let us know on the DaCHS-support mailing list.

As usual, the general upgrading instructions are available in the operator’s guide; if you plan on upgrading to stretch soon, also have a look at hints on postgres upgrades. Stretch comes with postgres 9.6 (jessie: 9.4), and you should migrate sooner or later anyway.

Users not using Debian’s package management can, as usual, grab tarballs from http://soft.g-vo.org/dachs.

See Who’s Kinking the Sky

A new arrival in the GAVO Data Center is UCAC5, another example of a slew of new catalogs combining pre-existing astrometry with Gaia DR1, just like the HSOY catalog we’ve featured here a couple of weeks back.

That’s a nice opportunity to show how to use ADQL’s JOIN operator for something else than the well-known CONTAINS-type crossmatch. Since both UCAC5 and HSOY reference Gaia DR1, both have, for each object, a notion which element of the Gaia source catalog they correspond to. For HSOY, that’s the gaia_id column, in UCAC5, it’s just source_id. Hence, to compare results from both efforts, all you have to do is to join on source_id=gaia_id (you can save yourself the explicit table references here because the column names are unique to each table.

So, if you want to compare proper motions, all you need to do is to point your favourite TAP client’s interface to http://dc.g-vo.org/tap and run

SELECT 
    in_unit(avg(uc.pmra-hsoy.pmra), 'mas/yr') AS pmradiff, 
    in_unit(avg(uc.pmde-hsoy.pmde), 'mas/yr') AS pmdediff, 
    count(*) as n, 
    ivo_healpix_index (6, raj2000, dej2000) AS hpx 
    FROM hsoy.main AS hsoy 
    JOIN ucac5.main as uc 
    ON (uc.source_id=hsoy.gaia_id) 
    WHERE comp IS NULL    -- hsoy junk filter
    AND clone IS NULL     -- again, hsoy junk filter
    GROUP BY hpx

(see Taylor et al’s All of the Sky if you’re unsure what do make of the healpix/GROUP BY magic).

Of course, the fact that both tables are in the same service helps, but with a bit of upload magic you could do about the same analysis across TAP services.

Just so there’s a colourful image in this post, too, here’s what this query shows for the differences in proper motion in RA:

(equatorial coordinates, and the aux axis is a bit cropped here; try for yourself to see how things look for PM in declination or when plotted in galactic coordinates).

What does this image mean? Well, it means that probably both UCAC5 and HSOY would still putt kinks into the sky if you wait long enough.

In the brightest and darkest points, if you waited 250 years, the coordinate system induced by each catalog on the sky would be off by 1 arcsec with respect to the other (on a sphere, that means there’s kinks somewhere). It may seem amazing that there’s agreement to at least this level between the two catalogs – mind you, 1 arcsec is still more than 100 times smaller than you could see by eye; you’d have to go back to the Mesolithic age to have the slightest chance of spotting the disagreement without serious optical aids. But when Gaia DR2 will come around (hopefully around April 2018), our sky will be more stable even than that.

Of course, both UCAC5 and HSOY are, indirectly, standing on the shoulders of the same giant, namely Hipparcos and Tycho, so the agreement may be less surprising, and we strongly suspect that a similar image will look a whole lot less pleasant when Gaia has straightened out the sky, in particular towards weaker stars.

But still: do you want to bet if UCAC5 or HSOY will turn out to be closer to a non-kinking sky? Let us know. Qualifications („For bright stars…”) are allowed.

PPMXL+Gaia DR1=HSOY in the Heidelberg Data Center

The stunning precision of Gaia’s astrometry is already apparent in the first release of the data obtained by the satellite, available since last September. However, apart from the small TGAS subset (objects already observed by the 90ies HIPPARCOS astrometry satellite) there is no information on the objects’ proper motions in DR1.

Until Gaia-quality proper motions will become available in DR2, the HSOY catalog – described in Altmann et al’s paper Hot Stuff for One Year (HSOY) freshly up in arXiv and online at http://dc.g-vo.org/hsoy – can help if you can live with somewhat lesser-quality kinematics.

It derives proper motions for roughly half a billion stars from PPMXL and Gaia DR1, which already gives an unprecedented source for 4D astrometry around J2015. And you can start working with it right now. The catalog is available in GAVO’s Heidelberg data center (TAP access URL: http://dc.g-vo.org/tap; there’s also an SCS service). Fire up your favourite TAP or SCS client (our preference: TOPCAT) and search for HSOY.

Image: Errors in proper motion in declination in HSOY on the sky

HSOY average errors in proper motion in declination over the sky, in mas/yr. The higher errors south of -30 degrees are because the great sky surveys of the 50ies could not be extended to the southern sky, and thus the first epoch there typically is in the 1980ies.

Oh, and in case you’re new to the whole TAP/ADQL game: There’s our ADQL introduction, and if you’re at a German astronomical institution, we’d be happy to hold one of our VO Days at your institute – just drop us a mail.