The Properties of 1.2 Million Solar System Objects Are Now Contained In A Machine-Readable Database

Academic research on solar system objects has increased dramatically over the last twenty years. However, information on most of the estimated 1.2 million objects discovered in our solar system has been spread throughout various databases and research papers. Putting all that data into a single data store and making it easy to access would allow researchers to focus on their research rather than on where to collect data. That is the idea behind the Solar System Open Database Network (SsODNet), a project by data scientists at the Observatoire de Paris.

So why is this important? Ease of access to data can lower barriers to entry into the field of researching solar system objects (SSOs), allowing more people to participate in that research. The more people that research SSOs, the more likely we are to spot a potentially dangerous or economically interesting one. 

Additionally, even for researchers already involved in the field, collecting data relevant to their current research can be a time-consuming, manual process. Introducing machine-readable tools like SsODNet can dramatically speed up the time it takes to produce new research on SSOs, enabling those researchers to do better-quality work.

What parameters would those researchers be looking at? The database includes data on diameter, taxonomy, thermal inertia, rotational period, albedo, and more – the most exciting characteristics scientists want to know about an SSO. To collect this data, the developers, led by Jerome Berthier, combined data from several publicly available databases, such as the Jet Propulsion Laboratory Small Bodies Database and the Lowell Observatory Minor Planet Services, with manual data published in dozens of papers on solar system objects. Many of these preexisting databases also didn’t have machine-friendly systems, meaning that Dr. Berthier and his co-authors had to manually scrape data from them and the manuscripts to include it in SsODNet.

When building out SsODNet itself, machine interfaces were a central tenant of development. It is designed as a web service, with standard machine-interfacing protocols accepted for queries, such as Rest and web services. They also implemented a Python interface called “rocks,” which can be called from a command-line interface.

These simple interfaces combine features the SSO research community has asked for, such as standardizing the names of the 1.2 million objects in the database (called quaero in the program) and providing statistical analyses of a set of objects (ssoBFT). There are also several estimates for what properties might be correct if conflicting data points are found in the literature.

It is still incomplete even with as much data as they could gather on the 1.2 million objects in the database. The authors admit that most of the data points currently in the database are for asteroids since they are most interested in studying the type of object. However, while asteroids make up a large percentage of SSOs, they don’t include comets, satellites, or even planets, though this is planned for future database releases.

However, perhaps the most impressive part of this data collection effort is its ongoing commitment to support. The authors have committed to updating the database with new SSO data weekly (at least to the quaero name resolver) and releasing major monthly updates to the other applications. Doing so would include adding new data from new papers released during that time. Getting the data into a sustainable format to launch the database in the first place was a Herculean effort, and maintaining it for the foreseeable future will be another one. The SSO research community will undoubtedly thank them for it.

Learn More:
Berthier et al. – SsODNet: Solar system Open Database Network
Solar System Portal – SsODNet
UT – Solar System Guide
UT – Want to be an asteroid miner? There’s a database for that.

Lead Image:
Illustration of an interstellar object approaching our solar system.
Credit: Rubin Observatory/NOIRLab/NSF/AURA/J. daSilva