Libraries & Space Exploration: What Role Will We Play?

Mar 3

Note: Space exploration is rapidly becoming the next frontier of privatization and commercialization, raising important ethical and geopolitical concerns. Yet beyond these forces, space remains a powerful canvas for ideation—a place to rethink knowledge systems, open science, and interdisciplinary collaboration at scale. It also serves as a real-world testbed for big data and global research infrastructure, making it an invaluable case study. With that in mind, this post explores the role of libraries as architects of planetary knowledge systems—not for commercial gain, but for the advancement of open, integrated, and enduring scientific discovery.

Last week, I had the chance to visit CMU’s Mission Control Room—a place designed to simulate real-world space missions. Each workstation in the control center served a distinct role, from navigation officer to telemetry officer, mirroring the structure of NASA’s own mission teams. Right next door, in a high bay testing area, was a model planetary landscape where rovers navigated simulated terrain, monitored in real time from the control room above. It was a fascinating space—part laboratory, part simulation, part problem-solving center.

Standing there, I felt a surge of excitement—for a moment, I wanted to be an engineer. Or perhaps a Science Officer? But my thoughts quickly shifted from rockets and rovers to knowledge logistics. The complexity of planetary exploration isn’t just about engineering breakthroughs— it’s about coordinating expertise across disciplines, managing vast amounts of mission data in real time, and ensuring that insights aren’t lost between missions. These are not just engineering problems—they are knowledge management challenges too.

A few days later, I came across two reports from the National Academies: The Next Decade of Discovery in Solar and Space Physics and Proposed Science Themes for NASA’s Fifth New Frontiers Mission. These publications laid out the major obstacles facing planetary research—fragmented data, AI models that lack transparency, the challenges of interdisciplinary collaboration, and the struggle to keep scientific knowledge accessible over time. The more I read, the more I saw a direct link between space exploration and the fundamental challenges libraries have been tackling for years.

Over the weekend, I kept coming back to a question: What is the role of libraries, librarians, and archivists in space exploration? Not in some distant, speculative future, but in the next two decades.

Full disclosure—I’ve also been slowly making my way through the Foundation series, just a few pages every night before bed, so maybe Asimov is influencing my thinking on some subconscious level?

As I dug into the reports, it became clear that planetary science, space weather research, and large-scale scientific collaborations are becoming increasingly dependent on knowledge integration, open science, interdisciplinary coordination, and long-term knowledge stewardship—all areas where libraries have both expertise and opportunity.

And while, right now, it appears that the federal government is defunding itself from within, I wanted to cast an optimistic vision—a near-future in which librarians serve as architects of planetary knowledge infrastructure.

Here are several ways we might engage with space exploration—not just supporting research but actively shaping the information ecosystems of the future.

Making Planetary Science More Open, Interoperable, and Reusable

Planetary science is generating staggering amounts of data—from spacecraft observations and lab simulations to atmospheric models and geological surveys. But data alone doesn’t lead to discovery. The reports from the National Academies make clear that one of the biggest challenges in planetary research isn’t a lack of information—it’s a lack of integration. Mission data is scattered across agencies and institutions, often stored in discipline-specific silos with inconsistent metadata, limited interoperability, and few pathways for cross-disciplinary use. The result? Scientists waste time searching for, reformatting, and revalidating data that should already be accessible and reusable. Algorithmic driven analysis, cross-mission comparisons, and long-term knowledge building are being bottlenecked not by technology, but by poor knowledge infrastructure.

If libraries are serious about open science at scale, this is the moment to step forward. What if we worked directly with space agencies and research teams to build interoperable repositories that bridge planetary science disciplines? Could we help develop metadata standards tailored for AI-ready datasets, ensuring that future missions don’t repeat the data accessibility mistakes of the past? Could we design federated knowledge platforms where planetary datasets aren’t just stored, but continuously updated, enriched, and connected across fields? Instead of waiting for someone else to define the knowledge infrastructure of planetary science, why not bring our expertise in data curation, interoperability, and long-term preservation to the table—before the gaps become permanent barriers to discovery?

Facilitating Interdisciplinary Collaboration in Space Science

One of the most persistent challenges in planetary research isn’t a lack of expertise—it’s the disconnect between experts. The reports from the National Academies underscore how breakthroughs in planetary science increasingly require integrating insights across physics, geology, chemistry, climate science, AI, and engineering. But collaboration across disciplines is often messy. Researchers speak different technical languages, rely on incompatible models, and struggle to synthesize knowledge that wasn’t designed to be interoperable. This leads to duplication of effort, lost insights, and scientific bottlenecks that slow progress.

Libraries already position themselves as connectors of knowledge—but what if we became active facilitators of interdisciplinary synthesis? Could we develop a living knowledge map that doesn’t just organize research but illuminates conceptual bridges across fields? Imagine a system where a geologist studying Martian subsurface ice could quickly find not just other geologists' work, but also atmospheric models that explain sublimation rates, AI and data models that detect ice deposits, and climate analogs from Earth—all dynamically connected through a curated, interdisciplinary framework.

But it’s not just about tools. Libraries could also act as matchmakers in interdisciplinary science, convening or connecting planetary scientists, AI researchers, and data engineers around shared challenges. Could we host structured knowledge exchanges where teams don’t just present research but build conceptual frameworks together? Could we develop new mechanisms for cross-disciplinary peer review, ensuring that research intended for multi-field impact is structured in ways that other disciplines can engage with? If space science is moving toward team-based, transdisciplinary problem-solving, then libraries should be designing the knowledge infrastructure that makes that work possible.

Supporting AI-Driven Research in Space Science

AI is rapidly reshaping space science. The reports highlight how machine learning is being used to analyze vast planetary datasets, improve space weather forecasting, identify exoplanets, and model planetary systems at an unprecedented scale. But AI is only as powerful as the data it’s trained on—and here’s where the problem emerges. Many AI applications in space research are limited not by computational power, but by the availability of well-structured, AI-ready datasets. Data remains scattered, poorly labeled, and stored in formats that are difficult to integrate across disciplines. Scientists often spend more time preparing data for AI models than they do analyzing it.

Libraries care deeply about structuring knowledge for discovery—but are we thinking big enough when it comes to AI? Could (or should?) we be playing a role in curating high-quality, AI-training datasets for space science, ensuring that machine learning models are trained on well-documented, FAIR (Findable, Accessible, Interoperable, Reusable) data. Could we work with research teams to build repositories that support ML and related applications across planetary and heliophysics research? Could we lead efforts to establish best practices for the validation and citation of AI-generated insights, ensuring that these outputs remain transparent, reproducible, and scientifically sound?

And then there’s the question of access. Right now, AI-driven research discovery is largely controlled by proprietary platforms and commercial AI tools, limiting its integration into open science ecosystems. Could we help with designing open AI-powered discovery systems for planetary science—tools that don’t just return search results, but dynamically map connections between studies, data, and computational models? If we don’t push for open, transparent AI infrastructures, then space science will evolve within walled-off, inaccessible systems that hinder collaboration. AI isn’t just another tool in planetary research—it’s becoming an entire methodological paradigm shift. And libraries should be shaping (or at least helping to shape) the knowledge systems that emerge.

Managing the Knowledge Lifecycle of Space Missions

Planetary missions are extraordinary feats of engineering and scientific collaboration—but their knowledge infrastructures are often shockingly fragile. Both reports highlight a critical issue: once a mission ends, its knowledge often becomes fragmented, inconsistently archived, or, in some cases, lost altogether. Key insights from planetary landers, atmospheric probes, and deep-space observatories don’t always make it into well-structured, reusable repositories. The consequence? Future missions must re-learn lessons, re-run experiments, and rebuild knowledge that should have been preserved from past efforts.

This isn’t a new problem—it’s an ongoing failure of scientific knowledge management. Space agencies operate on tight funding cycles, prioritizing data collection and analysis over long-term preservation and accessibility. But what if libraries helped design the knowledge infrastructures that ensure mission data isn’t just stored, but structured for continuous use? Could we work with space agencies to develop better ontologies, versioning systems, and cross-mission interoperability standards, so that research findings, datasets, and computational models remain accessible across generations of missions?

And what if every major space mission had a "knowledge librarian or archivist"—a dedicated expert embedded within the mission team, responsible for ensuring that critical discoveries, workflows, and methodologies are captured in ways that future researchers can actually use? Libraries or archivists could play a key role in defining how planetary science knowledge is structured for long-term impact, rather than allowing mission data to remain an afterthought. If every mission represents a major investment in human knowledge, then the question isn’t whether we should preserve it—but whether we are willing to design the systems that make that knowledge truly enduring and reusable.

Expanding Space Science Through Citizen Science and Hackathons

Space exploration has traditionally been the domain of elite research institutions, national space agencies, and highly specialized scientific teams. But both reports highlight a major shift: distributed, large-scale research networks are emerging as critical drivers of discovery. Citizen science projects are already making meaningful contributions to space weather forecasting, planetary surface mapping, and exoplanet detection. Yet, despite these successes, public participation remains scattered and underutilized, often relegated to isolated, small-scale initiatives rather than a core function of space science infrastructure.

Libraries could change that. What if we became the conveners of structured, large-scale collaborations between scientists and the public? Imagine annual planetary science hackathons, hosted in research libraries or at universities, where scientists, students, data enthusiasts, and independent researchers work together on real planetary datasets, test driven discovery models, and refine planetary simulations. These events wouldn’t just be educational—they could become pipeline accelerators for open discovery, where researchers get fresh insights, students gain hands-on experience, and space-interested participants actively contributes to cutting-edge space science.

But hackathons are just the beginning. Libraries could serve as curators and facilitators of long-term, citizen-driven research programs, providing curated datasets, open computational tools, and training modules that enable non-specialists to meaningfully engage with space science beyond one-off projects. Could we help design the frameworks that integrate public contributions into institutional research pipelines, making them an expected—and valuable—part of planetary science workflows? Libraries have long been champions of democratizing knowledge. This is our opportunity to take that ethos into one of the most ambitious domains of human exploration—ensuring that space science is accelerated.

Rethinking Scientific Publishing for Space Research

Planetary science moves fast. The reports make it clear that mission conditions shift, new discoveries emerge, and models evolve at a pace that traditional publishing simply cannot keep up with. By the time a paper makes it through peer review and appears in a journal, the data it’s based on may already be outdated—or worse, rendered obsolete by newer analyses or mission findings. Yet, planetary science remains reliant on static, fragmented publication models that struggle to accommodate the fluid and iterative nature of contemporary research.

Libraries have long played a role in scholarly communication, but are we ready to challenge the very structure of scientific publishing? What if, instead of locking planetary science insights into rigid, one-time publications, we helped develop living research papers—scientific documents that continuously evolve as new data, citations, and computational models are added? Could we work with planetary researchers to design research dashboards, where findings, datasets, and methodologies are updated in real time, rather than being trapped in static PDFs?

The shift toward dynamic, open research outputs is already happening in computational fields, where preprint archives, open code repositories, and interactive datasets are advancing discovery. Could libraries push this transformation further by developing and stewarding global open publishing platforms tailored for planetary science? And -- could we advocate for AI-assisted literature synthesis tools that can auto-update research summaries based on new mission reports? If the fundamental role of publishing is to disseminate knowledge efficiently, then planetary science demands a more fluid, adaptive, and open model of scientific communication.

A New (Next) Frontier for Libraries?

Space exploration has never been just about rockets, rovers, and planetary science. At its core, it is an exercise in knowledge infrastructure—how information is collected, organized, interpreted, and passed forward across generations. The ability to understand a distant exoplanet, model a planetary atmosphere, or forecast a solar storm depends not only on scientific instruments but on the systems, we build to connect, contextualize, and sustain knowledge over time.

Libraries have always embraced the identity of knowledge stewardship, but this moment demands more than stewardship—it demands strategy, vision, creativity, and leadership. And most of all, action! The reports from the National Academies make it clear that the future of space science will be shaped as much by how knowledge is structured and shared as by any single technological breakthrough. If libraries, archivists, and other information professionals step forward, we can help design the systems that ensure planetary research is open, interoperable, integrated, interdisciplinary, AI-ready, and enduring. But if we sit back, others will shape the landscape instead. And most likely, it will not meet the needs of the scientific community or the broader public good.

The stakes are clear: either we help design resilient knowledge systems and pathways, or we risk a future where critical planetary research is locked away, lost in silos, forgotten, or dictated by commercial interests. This knowledge should belong to everyone.

Brian Mathews