Frequently Asked Questions

The Sloan Digital Sky Survey is an ongoing astronomy project that has been working since 1998 to make a detailed map of the universe, including our Milky Way galaxy. Since 2015, the survey has been in operating its fourth phase. Results from all phases (including the current fourth one) are available at www.sdss4.org.

The most recent SDSS data release, the fourteenth overall, is SDSS Data Release 17 (DR17), made public on 9 December, 2019. It includes most data from prior data releases; so to get the most recent, up-to-date data for anywhere in the sky, use Data Release 17.

Data Release 17 includes imaging data for about one-third of the night sky. The imaging data include images from the camera on the SDSS's 2.5-meter telescope as preview images (JPGs) and as FITS files. The data also include catalogs of detected objects, with parameters measured from imaging, including positions and magnitudes. DR17 also includes spectroscopic data for more than three million stars, galaxies, and quasars, Spectra are available as preview images (PNGs) and FITS files. Spectroscopic catalog data include object types and redshifts.

All DR17 data are available from this site. See DR17 Data Access to learn how to view and download DR17 data.

Prior SDSS-III data releases are also available. Its final data release, Data Release 12 was made publicly available on July 31, 2015. Previous data releases are still available as Data Release 10 (July 30, 2013), Data Release 9 (July 31, 2012), and Data Release 8 (January 11, 2011).

The final data release for SDSS-I and SDSS-II is Data Release 7.

The SDSS Education page describes what educational resources are available from the SDSS project.

The SDSS Voyages and SkyServer websites includes a variety of educational projects that use SDSS data to teach topics in astronomy and other sciences, using guided and open inquiry. With our Projects, you and your students can learn about spectra and colors of stars, galaxy types, the history of the universe, and much more.

You are welcome to use and adapt any of our projects in your classes, free of charge. For more information on what you can do with SkyServer in the classroom, see our Teacher FAQ.

The SDSS had a very sensitive camera. Stars that you can see with your unaided eyes are too bright for the SDSS's camera; they are saturated, and the light from them spills all over the detector. The SDSS still gets an image of those stars (for example, here is an image of Pollux from SkyServer), but the image processing software is unable to handle these images, and there are no entries in the SDSS catalog.

The SDSS distinguishes between stars and galaxies based on their shapes: single points of light are stars, and fuzzy patches of light are galaxies. Some stars are bright enough that their light saturates the camera, and thus the light spills over the image, so to the SDSS's camera, they look like fuzzy disks instead of single points of light. Their appearance fools the SDSS's software into classifying them as galaxies.

Apart from this page there is a Glossary of SDSS terms. There are several SDSS Tutorials available, and each SkyServer tool also has its own Help section. Finally, the SDSS helpdesk is there to help.

Please note that your helpdesk email may be shared with SDSS collaboration members and contributors who we think can help answering with your question. We will retain your email and our responses for archival purposes. These questions posed may be used to guide the development of our online documentation, but no identifying or proprietary information from your email will be published in that documentation or elsewhere. We will delete your email if you request us to do so. None of the information from your email will be sold.

The SDSS includes imaging data in long, narrow "stripes", 2.5 degrees wide. Part of the processing of SDSS images is to select some objects as targets for follow-up spectroscopy. The SDSS then collects spectra later. Most spectra were collected using the original SDSS-I/-II spectrograph. DR17 includes data collected using the BOSS spectrograph for the BOSS, eBOSS and MaNGA surveys, and data collected using the APOGEE spectrograph for the APOGEE-1 and APOGEE-2 surveys.

The Scope of DR17 page shows what areas of sky (sky coverage) are included in DR17. The Scope page also includes a Coverage Check form that allows you to see what data DR17 has for a given point on the sky.

Go to the SkyServer Navigate tool. Enter the name of your object in the "Name" box, then press Enter. The RA/dec coordinates of the object will appear in the boxes below. Then, click Get Image.

If a sky image appears in the main Navigate frame, then DR17 has an image for your object.

If there is an image for your object, you can also check to see whether DR17 includes a spectrum. Under the RA/Dec boxes, find the Drawing options. Click the checkbox next to Objects with spectra. If a red square appears around your object, then your object has a measured spectrum in DR17.

Whether or not your object has a spectrum in DR17, the object's magnitude data will appear in the right-hand pane. Click Quick Look to go see additional basic data about that object. Click Explore for more detailed data.

When you search for data in the SDSS, you are going through the SDSS database and looking for objects that match criteria you choose. For simple searches of photometric data, use the Imaging Query Form. For simple searches of spectroscopic data, use the Spectroscopic Query Form. For more complex searches, use Structured Query Language (SQL). See SkyServer's guide on Searching for Data to learn more about SQL. To see thumbnail results of objects that meet your criteria, use the Image List tool.

For large, complex queries that will take a long time to run, use CasJobs, the SDSS's batch query interface.

Many other search tools are available. See the DR17 Data Access pages for more options.

An important note if you are using Excel with the SkyServer educational projects: SDSS object IDs are so long that they get cut off in Excel, and show up with 000 as the last three digits. This means you won't be able to find your objects anymore! To get around this problem, see this workaround.

If you have a fairly small list of objects to match - a few hundred or so - use the SkyServer Cross-ID tool. Paste your list of objects, or upload a file containing data with the last two columns as (ra, dec) in decimal degrees. Click Submit. The next page will show only those objects that appear in the SDSS, with SDSS Object IDs that link to the Explore tool.

To see a thumbnail SDSS image of each matching object, use the Image List tool. Enter your list in the textbox on the upper left and click "Get Image". Click on one of the thumbnails to go to that position in the Navigate tool, or on one of the object names to go to that object's Explore tool entry.

For longer lists, use the Neighbors Search feature of CasJobs. See the CasJobs FAQ entry on "How can I cross-identify (find matching objects in SDSS) for my list of sources for which I have RA,decs?" for more information.

The SDSS measures magnitudes through ugriz filters, which give ugriz AB magnitudes. These magnitudes can be converted into UBVRI magnitudes using a set of transformations described on the Algorithms page of this site.

There are multiple interfaces to SDSS data, including:

SkyServer

Also known as the Catalog Archive Server (CAS), SkyServer is designed for astronomers, students and the general public.

CasJobs

For bigger queries, CasJobs provids a batch (asynchronous) system for querying the database and storing results, designed to allow astronomers to search SDSS catalog data flexibly and efficiently.

Science Archive Server

The Science Archive Server (SAS) provides direct access to the full SDSS data archive, including all directories and files listed in the Data Model.

Science Archive Webapp

The Science Archive Webapp provides a searchable interface for optical and infrared spectra, images of fields and mosaics, and includes an interactive view of optical spectra and infrared spectra, and a data download facility (supports both rsync and wget). All searches are cached on the server so that you can return later, via a permalink, or email the permalink to share your search results.

Data Release 13 includes several small schema changes to handle the new data.

The SkyServer DR17 Schema Browser documents the latest catalog data schema in its entirety. Compare this documentation to the DR8 Schema Browser and the DR7 Schema Browser.

The SpecObjAll table contains all spectroscopic objects, even duplicate spectra of the same object. Thus, we have created the SpecObj view, which contains data for only those fibers defined as sciencePrimary - essentially, the best spectrum that the SDSS has obtained for that object. That is, specObj contains no duplicate observations.

Similar to sciencePrimary, another parameter called bossPrimary flags the best spectrum that BOSS has obtained for an object. Exact definitions of sciencePrimary and bossPrimary can be found in the spectroscopic catalogs documentation.

PhotoObjAll is a table that contains all of the measured photometric quantities for all of the imaging detections for every object. Because we measure hundreds of parameters for each of 1.2 billion detections, this is a very large table, and queries can take very long to run. Also, PhotoObjAll includes duplicate and "special" detections such as parent or bright detections, which are normally not of interest to science users.

In an effort to speed up catalog data queries, we have created PhotoTag, a view (virtual or logical table) of PhotoObjAll with only a subset of the photometric parameters that are most often requested. Queries on this "thin" version of PhotoObjAll run much faster usually than queries on the larger table. If you have a query that uses and returns only values stored in PhotoTag, then you should definitely use PhotoTag.

In addition, we have created PhotoObj, a view of PhotoObjAll that contains only those objects that are survey primary or survey secondary. PhotoObj excludes special objects such as parent or bright detections. Because PhotoObj contains the same parameters as PhotoObjAll but effectively contains fewer objects, any queries for survey primary or survey secondary objects will run faster on PhotoObj.

Finally, there is PhotoPrimary, a view of PhotoObjAll that only includes survey primary detections; if you are not interested in duplicate detections at all, this is the view to use.

To summarize, the PhotoTag view is a vertical partition of PhotoObjAll (fewer columns), and PhotoObj, PhotoPrimary and PhotoSecondary are horizontal partitions of PhotoObjAll (fewer rows).

Given the above, you should consider:

1. Querying from PhotoTag if it contains all the parameters you are using to search and all the parameters you want returned
2. Querying from PhotoObj otherwise, UNLESS you are interested in data for objects that are neither PRIMARY nor SECONDARY. In that case, you will need to use the full PhotoObjAll table.
3. Importantly, the "shorthand" quantities u,g,r,i,z do not exist in PhotoTag (because we want to keep the view as thin as possible). Instead, you must use the modelMag_[ugriz] columns. HOWEVER, in PhotoObjAll and its views, only the u,g,r,i,z are indexed, and NOT the ModelMags! This difference in indexed columns is to save space (since indexes on a huge table like PhotoObjAll are expensive), not to confuse you!

Because PhotoTag has many fewer parameters, larger portions of it can be cached, improving performance. We have found that for almost all queries that contain parameters fully in PhotoTag, it is faster.

The SpecPhotoAll table is a precomputed join between the PhotoObjAll and SpecObjAll tables. It includes the most requested parameters from these two tables. Because the join has already been performed, it can be faster than computing the join on the fly. The SpecPhoto view contains the same parameters as SpecPhotoAll, but only for objects that are survey primary or survey secondary.

Internally, these numbers are stored to their full precision as they come out of the spectroscopic pipeline. When you perform a query, they have some default string format applied that cuts them to what you see.

But you can use SQL's str() function to change the string format to whatever you like.

To get z to 6 decimals, for example, change your query to search for select str(z,8,6) as z instead of just z, and analogously for zErr. This applies the function str() to the values in column z and returns the result with column label z (without the "as", the result of a function has no column label). The function str(col,length,dec) takes the numerical value in col and formats it as a string of length length and with dec significant digits. In other words, str(z,8,6) is the SQL equivalent to the C function printf("%8.6f",z). The str() function rounds the result to the number of decimals you request.

For any object in DR17, the type parameter in SpecObj and other tables was set when that object was targeted for spectroscopy (i.e., it is based on its morphology in the imaging data). The class parameter is set by the spectroscopic pipeline after the spectrum is observed (i.e., it is based on features in the spectrum).

In nearly all cases, you should believe the classification in class, since it tells you what the measured spectrum actually was. The type field tells you about why it was targeted. (However, there is more information about the object's target selection history in the target bits; see the target bitmasks pages for more information.

A copy of the current publicly-available SDSS catalog archive is available from the SkyServer support site, which also contains information on how to host a Skyserver mirror site. Click on the Skyserver SDSS Mirrors link on that site.

As of May 10, 2016, CasJobs is part of the new SciServer collaborative data-driven science framework, and CasJobs users need to register on the SciServer portal with their original CasJobs credentials so that they can obtain a new account on the SciServer single-sign-on system that is linked to their existing CasJobs account.

CasJobs uses the idea of query contexts, allowing you to specify what data sources you can query. The default context is to search your MyDB personal database space. To search DR17, the context should be set to DR17. You can choose from the Context drop-down menu above the area where you run queries. Before you run a CasJobs query, check what context you are searching. See the CasJobs user guide for more information.