Preparing for Science Data

Dave Brain, MAVEN Science Team Co-Investigator 

Teamwork.

The success of MAVEN hinges almost entirely on teamwork. As a scientist that uses data returned by spacecraft, it is sometimes easy for me to forget the number of people involved in making it possible for those squiggly lines of data to dance across my computer screen. After all, I simply need to load the data into my analysis software, make a plot, and learn something new about the planet I am studying (Ha! I laughed out loud as I wrote this because it is never this simple). I love doing this—a few times a year, as I look at my screen, I realize that I am the only person on the face of the Earth that has some new tidbit of information. The ‘A-ha!’ moment is an incredible rush, as is the period where I get to share the result with others.

Being involved in MAVEN has reminded me that science efforts are never independent. Thousands of people are working to make MAVEN successful. The instrument teams are testing and tweaking their instruments in preparation for delivery over the next few months to Lockheed Martin, where they will be incorporated onto the spacecraft. The spacecraft team has been working hard to get the many necessary components (electrical systems, communication systems, reaction wheels, etc.) onto the spacecraft, and preparing to receive the science instruments. I am in constant awe of the way in which these teams handle incredibly complex tasks and make them seem simple.

But what is the science team doing? After all don’t we need the data before we can do our work?

Dr. Dave Brain is a Co-Investigator on the MAVEN science team and serves as a science advisor for the Invisible Mars: Science on a Sphere education and outreach project. Dr. Brain is an assistant professor at the University of Colorado Boulder in the Laboratory for Atmospheric and Space Physics and the Department of Astrophysical and Planetary Sciences. (Courtesy Allison Baker)

The science team has not been sitting idle. We are getting ready to use MAVEN data in a variety of ways. But working with spacecraft measurements is not always a straightforward endeavor. An enormous amount of a scientist’s time can be wasted on dealing with unorganized or unnecessarily complicated datasets. More time is left for making new discoveries when data are made easy to acquire and work with. MAVEN faces a particular challenge because data from all its instruments must be considered together in order to answer our main science questions (even the instruments need to work as a team!). But the datasets are fundamentally different. For example, some instruments make measurements at the location of the spacecraft, while others look at the atmosphere far from the spacecraft. These different datasets must all be well organized, and fit together in a way that the science team can easily get to their ‘A-ha!’ moments.

My job right now is to lead an effort to make tools for the science team that solve these challenges. For the past year we have been devising plans for tools that facilitate ‘Intercomparison and Visualization’ of MAVEN data. Over the next few months we will begin developing a web portal to the MAVEN data that will allow MAVEN scientists to view and obtain the spacecraft viewing geometry, data availability, and actual measurements in a variety of different ways. Users will be able to interact directly in the webpage with many of the plots, making our site a ‘first of its kind’ experience. In addition, we are building a ‘toolbox’ of especially useful software routines that can be used with MAVEN data, thus saving the individual scientists precious time developing their own routines. Importantly, both the web page and the software toolbox are tailored to using data from different instruments simultaneously.

Now that we have the tools designed, I’m excited to see them become reality over the coming months as developers and science team members collaborate on specific features and functionality. I am confident that we’re going to provide tools that make the scientist’s analysis tasks easier.

But it’s going to take teamwork.