NGC 1333

Dr. Luisa Rebull, a Datanaut from the new spring 2018 class, contributed this blog post. She writes from Caltech in California:

The archive I work for is IRSA (the Infrared Science Archive). IRSA is the home for NASA's long-wavelength data so that means infrared and longer wavelength light.

IRSA is the permanent home for an awful lot of data from NASA's long-wavelength missions and surveys. We have petabytes (1000 GB = TB, a terabyte; 1000 TB= PB, a petabyte) in images and about 200 billion catalog rows in databases (as I type this).

We are developing new tools to work with data all the time. These tools are aimed at professional astronomers. However, the definition of "professional astronomers" necessarily encompasses everyone from an emeritus professor who can barely read his email to a summer student getting started on her first research project ever. Since these tools need to reach everyone between (and including) these extremes, these tools should be accessible to everyone. You do need to understand some basics first, though.

If you don't know about some of the broad categories of astronomical objects (open cluster, star forming region, etc.), the best place to learn quickly (as opposed to an astro 101 textbook) is maybe Wikipedia. Charles Messier was a French man who lived in the 1700s, and he made a list of "not comets" so that he would not be distracted by them when he was searching for comets. There are a lot of different kinds of objects in his catalog, so if you go to this list on Wikipedia, from which you can click on the object type to learn more about each object.

In order to start playing with data at IRSA, you need to understand some things about astronomical images. I give public talks to many different audiences, but my most frequent audience is amateur astronomers. This movie is about an hour long, and is aimed at just such an audience. This talk covers issues of bit depth, FITS images, filters, etc. Did you know, for example, that there is no such thing as color images? All images you see as color are combinations of 3 (or 4) color planes. Your computer or tv has a grid of three kinds of pixels -- red, green, and blue -- interleaved such that your eye blends them together into a color image. Understanding that color images are created by combinations of single-band images is critical to being able to play around sensibly with the data at IRSA. If you want to save files you create to your local disk, you need to know about FITS files and that you can't save an image as a JPG or GIF. This page collects all the links I mention during that talk; there are links to learn more about FITS files, color images, artifacts, etc.

That video also shows some screen shots of the IRSA tool Finder Chart, which is a good place to start -- it gives you the same patch of sky in many different wavelengths all at the same time. When you load the tool, you can put in an object name -- such as Messier 101, abbreviated "M101" -- or a position (right ascension and declination, RA and Dec). You can pick the size of the patch of sky you want, and the size of the images as displayed in the browser (useful if you have a big screen or a small screen). You can also choose to search on catalogs at the same time, but I'd recommend turning off those catalog searches until you are ready for them .. especially if you are working with a big patch of sky, there can be REALLY A LOT of sources, and it can be overwhelming. You can't break anything .. you are working with real data, the real deal, but nothing you can do from this tool will break or damage anything. Try clicking on buttons to experiment and see what they do. There is online help available throughout the tool to help you.

IRSA has a YouTube feed with brief tutorial videos demonstrating IRSA's tools. Again, these are aimed at professional astronomers, but should be accessible to you too. They're sorted into playlists so that you can access, say, all the Finder Chart videos all in one place, but each video is its own entity, and you don't really need to watch all of them, much less all of them in order. Individual videos from this feed are promoted weekly on "Tutorial Tuesday" on the IRSA's Facebook page if you'd like a weekly tip or reminder. :)

In order to be ready for catalogs, you need to know about filters, magnitudes, fluxes and flux densities, color-color and color-magnitude diagrams, and even spectral energy distributions. I run a program called NITARP, which partners small groups of educators with a research astronomer for a year-long research project. In that context, I have a bunch of videos on some of these basic concepts; they were developed for NITARP participants, but might work for you too. Here is another about hour-long video on filters, colors, magnitudes, SEDs, CCDs, and CMDs (oh my!).

Finder Chart enables you to access catalogs from a wide variety of places, not just the surveys whose images you request from the main search page. You can request catalogs on that main page, or you can use the "Catalogs" tab to load catalogs from any of a number of places (IRSA, your own disk, the web, and the VO) after you do an initial search. You can also make plots from the catalog, such as color-color and color-magnitude plots. The plots, catalogs, and images in Finder Chart are all interlinked, so if you click on a bright source in the image, it will pull up that source in the catalog and show you where it is on the plot; you can click in the plot and have the source highlighted in the catalog and image.

Many of IRSA's other tools have the same "look and feel" as Finder Chart. This isn't a mistake -- once you master Finder Chart, you should be able to tackle any of IRSA's other tools that look like this. For example, IRSA Viewer is the most generic of the IRSA tools. The WISE image service is literally just WISE data. There are lots more data sets on the IRSA website, and tutorials (if you need them!) on the IRSA YouTube feed. Have fun! :)


About Veronica

Ronnie has been enthusiastically showcasing NASA data as a member of NASA's Open Data team since 2013. She supports NASA's open source efforts by helping to curate and administrate datasets on NASA's Open Data Portal and Open Source Code Catalog, managing citizen and internal requests for NASA data, contributing to the Space Data Daily Open NASA blog, teaching Datanauts courses, and coordinating logistics and data support for the International Space Apps Challenge hackathons.