† We would like to recognize the extraordinary effort which this decadal has taken and the members of our community who were unable to participate in this work. We would also like to acknowledge conversations with white paper teams on data management, automation, and other machine learning relevant contributions and we encourage you to review these additional data science relevant papers.

For the past fifty years of space exploration, mass spectrometry has provided unique chemical and physical insights on the characteristics of other planetary bodies in the Solar System. A variety of mass spectrometer types, including magnetic sector, quadrupole, time-of-flight, and ion trap, have and will continue to deepen our understanding of the formation and evolution of exploration targets like the surfaces and atmospheres of planets and their moons. An important impetus for the continuing exploration of Mars, Europa, Enceladus, Titan, and Venus involves assessing the habitability of solar system bodies and, ultimately, the search for life—a monumental effort that can be advanced by mass spectrometry. Modern flight-capable mass spectrometers, in combination with various sample processing, separation, and ionization techniques enable sensitive detection of chemical biosignatures. While our canonical knowledge of biosignatures is rooted in Terran-based examples, agnostic approaches in astrobiology can cast a wider net, to search for signs of life that may not be based on Terran-like biochemistry. Here, we delve into the search for extraterrestrial chemical and morphological biosignatures and examine several possible approaches to agnostic life detection using mass spectrometry. We discuss how future missions can help ensure that our search strategies are inclusive of unfamiliar life forms.

Much of the mission autonomy development before and since these reports has focused on robotic autonomy, the onboard processing of raw or low-level data products that enables a spacecraft and/or flight instrument(s) to proceed safely and efficiently with mission objectives using minimal human interaction [1]. We use the term non-robotic science autonomy to refer to the ability of a science instrument to analyze its own data in order to calibrate itself, optimize operational parameters based on real-time findings, and ultimately make mission-level decisions based on scientific observations and determine which data products to prioritize and send back first. Science autonomy also includes data processing software that could be used for rapid data interpretation by scientists. Four of the Planetary Mission Concept Studies (PMCS) in preparation for this Decadal Survey, as well as the Europa Lander concept, target planetary environments from which communications are limited in data link rates and/or in time, including outer solar system targets, subsurface oceans, and hot and/or highly irradiated surfaces. Indeed, 4 of these mission concepts, including the PMCS Mercury lander, Intrepid moon rover, and Venus Flagship, as well as the Europa Lander concept describe needs for autonomy. Beyond the coming decade, future submarine missions beneath ice shells of ocean worlds would only be enabled by the ability to operate and make decisions autonomously.There are two broad categories of non-robotic science autonomy: flight instrument autonomy and data interpretation autonomy. Flight instrument autonomy deals with an instrument's ability to autonomously collect and selectively transmit data to Earth. Instruments capable of autonomous data collection, both robotically and in terms of decision-making (what samples to analyze, when, for how long, and fidelity of transmitted data) would, for example, greatly enhance the science return for missions in extreme environments, and are being planned for e.g., the proposed Europa Lander mission [2]. Autonomy in terms of data transmission would address the Key Points 1) Future planetary missions, especially those to the outer solar system, face significant challenges to increase sampling, reduce uncertainties, and manage and transmit increasing data volumes with limited data link rates. 2) Autonomous platforms enable instruments to perform inter-calibrations, sample validation, and discriminate data transmission, which reduces measurement uncertainties for optimal science return. 3) Science autonomy is necessary to achieve science goals for planetary missions under extreme conditions, short mission timeframes, and long delays in communication, and is specifically discussed in 3 of the Planetary Mission Concept Studies informing this Decadal Survey and the proposed Europa Lander. 4) Science autonomy will enable missions that are otherwise not possible, such as a sub-ice shell ocean submersible or a Venus lander. 5) Science autonomy has already enhanced science return for the Mars Science L...

† We would like to recognize the extraordinary effort which this decadal has taken and the members of our community who were unable to participate in this work. We would also like to acknowledge conversations with additional white paper teams on data management, automation, and other machine learning relevant contributions and we encourage you to review these data science relevant papers submitted to the survey.