The space industry is growing at a rapid pace as new technologies enable unprecedented access to space. Private companies are building more capable rockets and satellites while national space agencies push further into deep space exploration. As the sector expands, making sense of all the new information and research being produced is challenging. Cutting edge tools for analyzing vast volumes of text could help space industry stakeholders stay on top of emerging trends and innovations. One platform in particular, Semantic Scholar, shows promise for assisting with knowledge discovery in this high-impact domain.
Semantic Scholar is an AI research project developed by the Allen Institute for AI to be helpful, harmless, and honest. Its main function is to surface the most relevant academic papers on any given topic by understanding the concepts and ideas contained within texts, rather than just searching keywords. This ‘semantic search’ capabilities allow more nuanced discovery of relationships between papers. For the space economy, Semantic Scholar’s large database of scientific literature offers a valuable lens into cutting edge research occurring all over the world with applications to space.
Growth in Commercial Space
Over the past decade, private spaceflight has developed from a speculative future notion to reality. Companies such as SpaceX, Blue Origin, and Virgin Galactic are increasingly augmenting the capabilities traditionally held only by government agencies. Space tourism, satellite internet constellations, and even commercial lunar landers are no longer just sci-fi fantasies but actual business plans in development. This new commercial activity has energized activity in the overall space economy.
According to the Space Foundation’s 2022 Space Report, the global space economy reached $465 billion in 2021 and supported over 825,000 direct jobs. Commercial spaceflight was a major driver of this growth, with SpaceX alone valued at over $100 billion by some estimates. As more companies enter the field and make heavy investments in advanced technologies, this expansion is set to continue. With increased economic activity also comes a greater pool of new knowledge and research findings. Semantic Scholar offers a way to systematically organize and explore this expanding body of literature specific to commercial space.
Semantic Scholar indexes thousands of academic papers on commercial spaceflight topics like reusable rockets, smallsat constellations, satellite servicing, in-orbit manufacturing, space tourism, and more. Advanced filtering allows finding research most relevant to a particular sub-sector or technology. Commercial space companies and industry analysts could leverage this resource to stay on top of innovation happening outside their organizations. For emerging firms trying to enter new markets, Semantic Scholar provides access to insights from industry leaders and research institutions around the world.
Deep Space Exploration
While commercial space activity has expanded rapidly in low Earth orbit, national space agencies continue pushing further into deep space with ambitious flagship programs. NASA leads the international effort to return humans to the Moon under the Artemis program with a goal of establishing a sustainable lunar presence. The agency’s Mars Sample Return mission recently made progress caching rock cores for future retrieval. Space agencies in China, India, Japan, Europe and elsewhere are also conducting robotic explorations of the Moon, Mars and beyond.
As with low Earth orbit, the research and development behind these deep space initiatives generates huge amounts of publicly available data and papers. Semantic Scholar can play an invaluable role in synthesizing learnings across myriad scientific publications to advance humanity’s collective knowledge. For example, researchers studying habitat design for a Martian outpost could leverage the database to find papers on similar challenges faced building Antarctic research stations or underwater labs. Engineers designing a sample return rover might uncover insights published on mechanics of terrestrial geology rovers to improve mobility.
One useful feature Semantic Scholar offers for deep space research is its taxonomy of concept classifications. Papers are tagged based on over 600 broad categories like “planetary science”, “orbital mechanics”, “life support systems”, and more. Refining a search by these high level disciplines helps surface the most applicable information more rapidly than sifting through general results. The semantic analysis also pulls out key insights that may not be explicitly stated but still related to the query. This intelligent filtering saves researchers significant time that would otherwise be spent reading irrelevant papers. As flagship programs push frontiers, Semantic Scholar ensures previous relevant work isn’t overlooked.
Satellite Applications and Remote Sensing
Across industries and scientific disciplines, satellite technology enables monitoring Earth’s environment, communications, and more. Today over 4,000 operational satellites orbit our planet with an estimated $400 billion in annual revenues. And the wave of smallsat constellations launching promises to expand access to space-based capabilities. Companies like Planet, ICEYE, and Capella Space are fielding fleets delivering high revisit rates for applications in defense, agriculture, insurance, and more. Space situational awareness has also grown in strategic importance amid orbital congestion and an increasing quantity of space debris.
Semantic Scholar offers a centralized hub of knowledge around all aspects of satellite technology, systems, operations, and space-based applications. Its database indexes over 12,000 papers related specifically to topics like remote sensing, Earth observation, optoelectronics, radiofrequency engineering, and orbital mechanics important for satellite design and mission planning. Industry professionals and researchers can leverage this resource to stay informed of the latest capabilities satellites are demonstrating across diverse sectors. Semantic search also helps connect disparate but related work to inspire new innovative uses of space. For example, a startup developing crop monitoring tech may find inspiration by exploring papers at the intersection of agriculture, spectral analysis, and smallsat payload miniaturization.
Advancing Space Technologies
Cutting across all sectors of the space economy are the multitude of enabling technologies that continue driving down costs and opening new opportunities. Advancements in areas such as materials science, additive manufacturing, electric propulsion, autonomous systems, and integrated circuits all impact rocket design, satellite manufacturing, and mission architectures. International collaboration has also accelerated innovation, with countries trading capabilities to collectively achieve more. Understanding global trends in these converging technologies is critical for stakeholders to develop the most advanced and cost-effective solutions.
Semantic Scholar surfaces a wealth of multidisciplinary research with relevance to space technologies. For instance, a recent search on “materials for space applications” yielded papers on composite thermoplastics tested under extreme thermal cycling, self-healing metal alloys, and novel polymers for constructing lightweight antennas and optics. Other combined searches revealed work pairing microwave electrothermal thrusters to CubeSats or applying artificial intelligence to space situational awareness. Space agencies, entrepreneurs, and academic researchers can tap this diverse base of publications to spark new ideas, validate technical approaches, and navigate emerging fields at the intersection of space and other industries like biotech, autonomous vehicles, or renewable energy.
Challenges and Conclusion
While Semantic Scholar represents a powerful resource, some challenges remain for deriving full value from its space-related research. First, the database is limited to publicly disclosed academic literature, leaving out proprietary industry work or reports from classified government programs. Second, the AI models powering its semantic search are only as good as the training data – biased or incomplete data could impact relevance of results. Third, the rapid pace of innovation means information will quickly go stale if not continually updated. Fourth, users must still have domain expertise to properly evaluate findings in context of specific technical or programmatic needs.
Nonetheless, Semantic Scholar shows tremendous promise as a centralized platform for advancing knowledge across the entire space sector through intuitive discovery of related research worldwide. As commercial activity drives new investment while governments push farther out into the solar system, keeping track of the explosion of data and innovation becomes increasingly difficult without advanced search capabilities. Semantic Scholar leverages cutting edge AI to provide a strategic advantage for organizations seeking to solve grand challenges or capitalize on emerging opportunities by building upon the discoveries of others. With potential applications across sub-orbital tourism to deep space habitats, this innovative knowledge graph holds value for stakeholders across the new space economy.
