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By NASA
1 min read
NASA Science Activation Teams Present at National Rural STEM Summit
NASA Science Activation (SciAct) teams participated in the National Rural STEM (Science, Technology, Engineering, & Mathematics) Summit held June 4-7, 2024 in Tucson, Arizona. Hosted by Kalman Mannis of the Rural Activation and Innovation Network (Arizona Science Center) and the SciTech Institute, the summit fostered learning and sharing among organizations dedicated to creating partnerships and pathways for authentic STEM learning in rural communities.
Participants included:
Matt Cass and Randi Neff from SciAct’s Smoky Mountains STEM Collaborative, who presented “A sense of place: Crafting authentic experiences for rural STEM learners”; Tina Harte from NASA (Science Systems and Applications, Inc), who presented “Nature explorations with NASA”; Kalman Mannis from the SciAct STEM Ecosystems project and the Rural Activation and Innovation Network, who presented “Building leaders in STEM through coaching, connections, and camaraderie”; and members of the SciAct Rural Committee. SciAct STEM Ecosystems is supported by NASA under cooperative agreement award number 80NSSC210007 and is part of NASA’s Science Activation Portfolio. Learn more about how Science Activation connects NASA science experts, real content, and experiences with community leaders to do science in ways that activate minds and promote deeper understanding of our world and beyond: https://science.nasa.gov/learn
Randi Neff of the NASA SciAct-funded Smoky Mountains STEM Collaborative presents at the National Rural STEM Learning Summit. Arizona Science Center Share
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Last Updated Jul 05, 2024 Editor NASA Science Editorial Team Related Terms
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By NASA
1 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
NAS visualization & data sciences lead Chris Henze demonstrates the newly upgraded hyperwall visualization system to Ames center director Eugene Tu, deputy center director David Korsmeyer, and High-End Computing Capability manager William Thigpen.NASA/Brandon Torres Navarette In May, the NASA Advanced Supercomputing (NAS) facility, located at NASA’s Ames Research Center in California’s Silicon Valley, celebrated the newest generation of its hyperwall system, a wall of LCD screens that display supercomputer-scale visualizations of the very large datasets produced by NASA supercomputers and instruments.
The upgrade is the fourth generation of hyperwall clusters at NAS. The LCD panels provide four times the resolution of the previous system, now spanning across a 300-square foot display with over a billion pixels. The hyperwall is one of the largest and most powerful visualization systems in the world.
Systems like the NAS hyperwall can help researchers visualize their data at large scale, across different viewpoints or using different parameters for new ways of analysis. The improved resolution of the new system will help researchers “zoom in” with greater detail.
The hyperwall is just one way researchers can utilize NASA’s high-end computing technology to better understand their data. The NAS facility offers world-class supercomputing resources and services customized to meet the needs of about 1,500 users from NASA centers, academia and industry.
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Last Updated Jul 01, 2024 Related Terms
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By NASA
4 min read
Mapping the Red Planet with the Power of Open Science
This image of Perseverance’s backshell sitting upright on the surface of Jezero Crater was collected from an altitude of 26 feet (8 meters) by NASA’s Ingenuity Mars Helicopter during its 26th flight at Mars on April 19, 2022. NASA/JPL-Caltech Mars rovers can only make exciting new discoveries thanks to human scientists making careful decisions about their next stop. The Mars 2020 mission is aimed at exploring the geology of Jezero Crater and seeking signs of ancient microbial life on Mars using the Perseverance rover. Scientists at NASA’s Jet Propulsion Laboratory (JPL) in Southern California used novel mapping techniques to direct both the rover and the flights of the Ingenuity helicopter, which rode to Mars on Perseverance — and they did it all with open-source tools.
JPL mapping specialists Dr. Fred Calef III and Dr. Nathan Williams used geospatial analysis to help the scientific community and NASA science leadership select Jezero Crater as the landing site for Perseverance and Ingenuity. Before the vehicles arrived on Mars, they helped create maps of the terrain using data from orbiting satellites.
“Maps and images are a common language between different people — scientists, engineers, and management,” Williams said. “They help make sure everyone’s on the same page moving forward, in a united front to achieve the best science that we can.”
Maps and images are a common language between different people.
Nathan Williams
NASA JPL Geologist and Systems Engineer
After the mission touched down on Mars in February 2021, the Ingenuity helicopter opportunistically scouted ahead to take photos. The team then generated more detailed maps from both rover and helicopter image data to help plan the Perseverance rover’s path and science investigations.
To enable this full-scale mapping of Mars, Calef created the Multi-Mission Geographic Information System (MMGIS), an open-source web-based mapping interface. Online demos of the software, pre-loaded with Mars imagery taken from orbit, allow visitors to explore the paths of Perseverance, Ingenuity, and the Curiosity rover, a sister Mars mission that landed in 2012.
This image of NASA’s Perseverance Mars rover at the rim of Belva Crater was taken by the agency’s Ingenuity Mars Helicopter during the rotorcraft’s 51st flight on April 22, 2023. The rover is in the upper left of the image, parked at a light-toned rocky outcrop. NASA/JPL-Caltech The open nature of the software was key to the mission’s success. “We have people literally all over the world who are working on the mission, and we need to be able to give them fast and quick access to software and data,” Calef said.
MMGIS aimed to help people understand the full scope of Martian geography. By combining images from orbit and augmenting with images from Perseverance and Ingenuity, the JPL team allows researchers to zoom in to see individual boulders and zoom out to see all of Mars. This variety of viewpoints gives the team a sense of scale and context to properly understand the landscape around the Perseverance rover, and how to optimally achieve their science goals within the available terrain.
This image of an area the Mars Perseverance rover team calls “Faillefeu” was captured by NASA’s Ingenuity Mars Helicopter during its 13th flight at Mars on Sept. 4, 2021. Images of the geologic feature were taken at the request of the Mars Perseverance rover science team, which was considering visiting the geologic feature during the first science campaign. NASA/JPL-Caltech The impact of the tools developed by the JPL team went beyond the Mars 2020 mission. The team wanted their software to help other researchers easily visualize their data without needing to be data visualization experts themselves. Thanks to this open-source approach, other teams have now used MMGIS to map Earth and other planetary bodies.
In keeping with this open philosophy, the images taken by Perseverance and Ingenuity over the course of the Mars 2020 mission are freely available to the public. By sharing these data with the rest of the world, the results from the mission can be used to educate, inspire, and enable further research.
It’s being able to share data between people … getting a higher order of science.
Fred Calef
NASA JPL Geologist and Data Scientist
As Mars scientists look to the future, with the Perseverance rover team deploying even more advanced tools powered by AI, open science will pave the way for further exploration. JPL is now working on designs for potential future Mars helicopters that are far more capable and complex than Ingenuity. Payload mass, flight range, and affordability are at the forefront of their minds.
Existing open-source tools will help address those concerns. Not only are open-source applications free to use, but the large amount of collaboration in creating and testing them means that they’re often highly reliable.
Ultimately, the JPL team views its work as part of the cycle of open science, using open tools to make its job easier while also developing new features in the tools for others to use in the future. “Every mission is contributing back to the other missions and future missions in terms of new tools and techniques to develop,” Calef said. “It’s not just you working on something. It’s being able to share data between people … getting a higher order of science.”
By Lauren Leese
Web Content Strategist for the Office of the Chief Science Data Officer
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Last Updated Jun 27, 2024 Related Terms
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By NASA
Jake Cupani, a data science specialist, focuses on the intersection between data visualization and user experience — UX — design.
Name: Jake Cupani
Title: Financial analytics support specialist
Organization: Financial Analytics and Systems Office, Office of the Chief Financial Officer (Code 156)
Jake Cupani is a financial analytics support specialist at Goddard Space Flight Center in Greenbelt, Md. Photo courtesy of Jake Cupani What do you do and what is most interesting about your role here at Goddard?
I create data visualizations and dashboards to help visualize some of the key metrics including demographics, budgeting, and forecasting. I enjoy helping our office modernize and automate their processes.
What is your educational background?
In 2020, I got a B.S. in information science with a minor in astronomy from the University of Maryland. In 2022, I got a master’s in information management and data analytics also from the University of Maryland.
How did you come to Goddard?
After graduating, I did some consulting. I came to Goddard in 2023, but I had interned for Goddard throughout my academic career. My office knew about my work and recruited me.
You describe yourself as a data science specialist. What do you mean?
Data science encompasses everything from data visualization to analysis and specifics as well as data preparation. Data visualization focuses on taking any sort of data, be it spreadsheets or tables, and creating graphs and interactive charts to explain the data and gather insights on the data.
What is most important to you as a data science specialist?
What I think is important is the intersection between the visualization and the user experience. You have to make it easy for people to digest the analytics so that they can understand the ideas you are trying to get across and the overall trends.
As a person fairly new to Goddard, what are your initial impressions?
What is great about Goddard is that everyone seems really open to helping. Everyone works collaboratively. You can always ask questions. Goddard has a collegial environment.
It is very refreshing to be in an environment that is so open and welcoming. People from all different walks of life work at Goddard and this diversity enables us to accomplish all the things that we do. People are willing to listen to other people’s ideas.
Who is your mentor and what have you learned?
My mentor is my boss, John Brady. I thank him for being such a good leader and listener. He taught me about Goddard’s culture and how decisions are made.
What is your involvement with the LGBTQ+ Employee Resource Group?
Although not in a leadership role, I attend the monthly meetings where we get together and have lunch. Sometimes we have speakers, other times we just talk. These lunches help me engage with the LGBTQ+ community.
“What I think is important is the intersection between the visualization and the user experience,” said Jake. “You have to make it easy for people to digest the analytics so that they can understand the ideas you are trying to get across and the overall trends.”Photo courtesy of Jake Cupani What one thing you would tell somebody just starting their career at Goddard?
I would tell them that working at Goddard is an amazing opportunity that will allow them to meet a lot of really smart people who also very welcoming. I would tell them not to be shy and to talk to as many people as they can.
Where do you see yourself in five years?
In five years, I want to still work in data visualization and continue to learn as much as I can to grow my expertise. Beyond that, I don’t know what is in the future for me.
What do you do for fun?
I like baking cookies, brownies, and cakes. I am also a big fan of playing video games, especially Pokémon.
By Elizabeth M. Jarrell
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Conversations With Goddard is a collection of Q&A profiles highlighting the breadth and depth of NASA’s Goddard Space Flight Center’s talented and diverse workforce. The Conversations have been published twice a month on average since May 2011. Read past editions on Goddard’s “Our People” webpage.
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Last Updated Jun 25, 2024 EditorMadison OlsonContactRob Garnerrob.garner@nasa.govLocationGoddard Space Flight Center Related Terms
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By NASA
4 min read
NASA-IBM Collaboration Develops INDUS Large Language Models for Advanced Science Research
Named for the southern sky constellation, INDUS (stylized in all caps) is a comprehensive suite of large language models supporting five science domains. NASA By Derek Koehl
Collaborations with private, non-federal partners through Space Act Agreements are a key component in the work done by NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT). A collaboration with International Business Machines (IBM) has produced INDUS, a comprehensive suite of large language models (LLMs) tailored for the domains of Earth science, biological and physical sciences, heliophysics, planetary sciences, and astrophysics and trained using curated scientific corpora drawn from diverse data sources.
INDUS contains two types of models; encoders and sentence transformers. Encoders convert natural language text into numeric coding that can be processed by the LLM. The INDUS encoders were trained on a corpus of 60 billion tokens encompassing astrophysics, planetary science, Earth science, heliophysics, biological, and physical sciences data. Its custom tokenizer developed by the IMPACT-IBM collaborative team improves on generic tokenizers by recognizing scientific terms like biomarkers and phosphorylated. Over half of the 50,000-word vocabulary contained in INDUS is unique to the specific scientific domains used for its training. The INDUS encoder models were used to fine tune the sentence transformer models on approximately 268 million text pairs, including titles/abstracts and questions/answers.
By providing INDUS with domain-specific vocabulary, the IMPACT-IBM team achieved superior performance over open, non-domain specific LLMs on a benchmark for biomedical tasks, a scientific question-answering benchmark, and Earth science entity recognition tests. By designing for diverse linguistic tasks and retrieval augmented generation, INDUS is able to process researcher questions, retrieve relevant documents, and generate answers to the questions. For latency sensitive applications, the team developed smaller, faster versions of both the encoder and sentence transformer models.
Validation tests demonstrate that INDUS excels in retrieving relevant passages from the science corpora in response to a NASA-curated test set of about 400 questions. IBM researcher Bishwaranjan Bhattacharjee commented on the overall approach: “We achieved superior performance by not only having a custom vocabulary but also a large specialized corpus for training the encoder model and a good training strategy. For the smaller, faster versions, we used neural architecture search to obtain a model architecture and knowledge distillation to train it with supervision of the larger model.”
NASA Chief Scientist Kate Calvin gives remarks in a NASA employee town hall on how the agency is using and developing Artificial Intelligence (AI) tools to advance missions and research, Wednesday, May 22, 2024, at the NASA Headquarters Mary W. Jackson Building in Washington. The INDUS suite of models will help facilitate the agency’s AI goals. NASA/Bill Ingalls INDUS was also evaluated using data from NASA’s Biological and Physical Sciences (BPS) Division. Dr. Sylvain Costes, the NASA BPS project manager for Open Science, discussed the benefits of incorporating INDUS: “Integrating INDUS with the Open Science Data Repository (OSDR) Application Programming Interface (API) enabled us to develop and trial a chatbot that offers more intuitive search capabilities for navigating individual datasets. We are currently exploring ways to improve OSDR’s internal curation data system by leveraging INDUS to enhance our curation team’s productivity and reduce the manual effort required daily.”
At the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC), the INDUS model was fine-tuned using labeled data from domain experts to categorize publications specifically citing GES-DISC data into applied research areas. According to NASA principal data scientist Dr. Armin Mehrabian, this fine-tuning “significantly improves the identification and retrieval of publications that reference GES-DISC datasets, which aims to improve the user journey in finding their required datasets.” Furthermore, the INDUS encoder models are integrated into the GES-DISC knowledge graph, supporting a variety of other projects, including the dataset recommendation system and GES-DISC GraphRAG.
Kaylin Bugbee, team lead of NASA’s Science Discovery Engine (SDE), spoke to the benefit INDUS offers to existing applications: “Large language models are rapidly changing the search experience. The Science Discovery Engine, a unified, insightful search interface for all of NASA’s open science data and information, has prototyped integrating INDUS into its search engine. Initial results have shown that INDUS improved the accuracy and relevancy of the returned results.”
INDUS enhances scientific research by providing researchers with improved access to vast amounts of specialized knowledge. INDUS can understand complex scientific concepts and reveal new research directions based on existing data. It also enables researchers to extract relevant information from a wide array of sources, improving efficiency. Aligned with NASA and IBM’s commitment to open and transparent artificial intelligence, the INDUS models are openly available on Hugging Face. For the benefit of the scientific community, the team has released the developed models and will release the benchmark datasets that span named entity recognition for climate change, extractive QA for Earth science, and information retrieval for multiple domains. The INDUS encoder models are adaptable for science domain applications, and the INDUS retriever models support information retrieval in RAG applications.
A paper on INDUS, “INDUS: Effective and Efficient Language Models for Scientific Applications,” is available on arxiv.org.
Learn more about the Science Discovery Engine here.
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Last Updated Jun 24, 2024 Related Terms
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