Data

MilkyWay3D.org is consolidating a wide variety of datasets relevant to understanding the physical processes that shape cloud and star formation in our Milky Way.

  
The assembled datasets offer 3D:

• maps of density, velocity, mass, and sometimes temperature of interstellar material

• characterizations of clouds, shells, and voids

• positions and motions of OB associations, stellar clusters, HII regions, and supernova remnants

• derived structures, such as spiral arms, proposed as significant by researchers.

Using spatial and kinematic information together MilkyWay3D.org holdings can constrain:

• the evolutionary state of the gas and stellar associations (e.g. forming, dissolving)

• spatial, dynamical, and temporal connections between gas, young stars

• sources of feedback across a range of scales and over a diverse set of galactic environments. 

Sharing Policies and Plans

All of the data and code being assembled as part of MilkyWay3D.org are being shared publicly. 

• Specific individual data sets are available via this public Google Drive.

• Some packages of related data files can be found in NASA’s Mikulski Archive for Space Telescopes (MAST) archive and/or the MilkyWay3D Dataverse. 

• Where appropriate, data collected for MilkyWay3D.org are being added to the Digital Universe database used inside of OpenSpace.

• Saved glue sessions that allow anyone to recreate any saved combination of data and visualizations are provided via this public Google Drive.

• Additional data and sessions are available for collaborators. (Click here to request access.)

Community Contributions

If you or your organization would lke to contribute data to MilkyWay3D.org, you are welcome to use this survey.  If the data volume is large, or you have questions about the appropriateness of your contribution, please contact us.

Re-formatted MilkyWay3D.org Data

The table below lists some of data sets included in the  Journal Articles-based Google Directory above.  The last column of the table shows checkmarks indicating which data sets are included in the prototype bundle of data to be contributed to MAST, from Zucker et al. 2023 .