Publish your data in the Virtual Observatory
The VO is all about making data accessible to both scientists and the general public. Astronomical data and results published in journals do not always appear in the data centres and data produced by telescopes are not always made available to the community. Your astronomical data is too valuable to let it become forgotten -- publish it in the VO! The Virtual Observatory aims to provide astronomers with seamless access to all data and to ensure the quality and completeness of those resources.
While there are several ways to publish your data into the VO, it is probably more convenient to let us do the grunt work. This has the additional advantage that you don't need to worry about protocols, formats or updating software.
How does it work?
We are fairly flexible in terms of what we accept. You could just send a table or whatever format it is in. In addition, a preprint of your article would be very useful.
What's important in order to make it easy for others to find your data is good metadata. We're probably able to extract most of what we need from your paper, but you may still wish to have a look at http://docs.g-vo.org/DaCHS/data_checklist.html already.
What will happen then: We'll make a prototype service (password-protected until your paper is published), which probably will lead to a few additional questions from our side. You can then see how it looks like, and after one or two iterations we should be done.
Thanks for sharing your data.
For further questions send a mail to the operators of the GAVO data center at gavo @ ari . uni - heidelberg . de. Or call Markus Demleitner at ++49 6221 54 1837.
Questions & Answers about data publication within the VO
See the IVOA pages for information about what type of data to be published and available toolkits to publish data into the VO.
You can not publish your data? Lame excuses and some answers
You already know that publishing data is the right thing to do, don't you? It's just that exactly your data is an exception, right?
Here's a collection of reasons not to publish from Charly Strasser's web page we've heard many times. And some replies:
- "People will contact me and ask about stuff."
Well, science is about exchange. Think how much you learned by asking other people. Plus, you'll notice that quite a few of those questions are actually quite clever, so answering them is a good use of your time. As to the stupid questions - well, they are annoying, but at least for us even those were eye-openers now and then.
- "People will misinterpret my data."
Good documentation and standards mitigate this. As for what remains - well, if you're publishing prose (i.e., in a journal), how many of your readers do you think actually get what you're writing?
- "My data is boring or at least not very interesting."
Leave that decision to others. You'd be surprised how much "boring data" people point-and-click out of printed graphs or tables in the sweat of their mice. Every day.
- "I might yet want to use it in the great seminal research paper I've always wanted to write."
If you've not done so so far, will you at all? When? Too much data obtained for uncounted kilodollars (or megadollars, for that matter) is gathering dust, waiting for the "real soon now". Be fair to the world and to the people funding you and your research and publish the data. If you're really worried, put a one-year embargo on the material. Procraste's Law: If over a year you don't get to do it, chances are overwhelming you'll never do it.
- "I'm not sure I own the data."
That's amazingly common. So: Are you sure you cannot find out who does? If you made a reasonable effort to figure that out but failed, the likelihood is high you've orphaned data on your hands, obtained by people who've long left science for greener pastures. To avoid similar uncertainties with your data later on, please consider assigning explicit licenses to it - ideally CC-0. Do not worry that people will not give credit just because of a Free license. We're in science, and so this is a matter of scientific conduct rather than the law.
- "My data is embarrassingly bad."
Everyone's is. Good data is just bad data that more eyes have seen and more hands have improved.
- "My data is too complicated."
If it's too complicated to explain: are you sure you've understood it yourself? Be that as it may: Try explaining anyway, the improved understanding you'll get will reward you plenty.
- "I'm busy and it's not a priority."
A-ha! Here we're talking. True, the current system of rewards in science doesn't actually encourage data publishing. But publishing is the right thing to do, anyway, even before the system gets back on a path of recovery. And: more and more funding agencies at least sound requirements for data publishing and preservation.
- "It's too much work."
No, it's not. For example, the GAVO data center is there to help you. Unless your data is particularly funky, you'll not have to spend more than half a day from the half-documented, messy goo that's on your disk to a shiny, blinking, proper, VO-registred, be-proud-of data service. And we'll take care of it henceforth.