Open Source Science for ESO Mission Processing Study: Open NEX Perspective
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Ian Brosnan↗
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Improving “Domain-Relevant Metadata Requirements” for Supporting Open-Source Science Initiative
Implementation of the NASA Open-Source Science Initiative (OSSI) requires sharing of all relevant information to ensure “open reproducible science” [1]. However, there are several challenges in applying the OSSI to airborne field campaigns focused on atmospheric composition, which often involve a wide variety of in-situ measurements for trace gases, aerosol and cloud properties, meteorological parameters, and radiation fields. To ensure open reproducibility from airborne field campaigns, it is essential to obtain detailed measurement descriptions, which include the detection principle, sample procedure and treatment, and data processing and correction method. The challenge is that some information, e.g., sampling procedure and treatment, may be instrument-specific and campaign or platform-dependent. The data processing may also involve empirical corrections which may evolve over time. In addition, these details (especially operation- or campaign-specific ones) are often not given in journal publications. Given these issues, there is a need to leverage and improve the current “domain-relevant metadata requirements” to represent the measurement description in standardized metadata. These requirements can then facilitate systematic collection of measurement specific metadata and serve as a foundation to develop tools for making the information accessible and data more interoperable and usable or reusable. Here we show a review of existing metadata collections, use cases, and needs for new standards.
Sean Leavor↗
Transforming NASA Earth Science Data Systems: A Journey from Big Earth Data Initiative (BEDI) to Open-Source Science Initiative (OSSI)
NASA's Earth Science Data and Information Systems (ESDIS) have undergone a significant evolution, particularly with the introduction of the Big Earth Data Initiative (BEDI) and the Open-Source Science Initiative (OSSI). In this talk, I will provide an overview of NASA's Earth Science Data and Information systems, highlighting key components such as EOSDIS, ESDIS, and ESDS. Moving forward, I will delve into the BEDI initiative, discussing its objectives, key players, and lessons learned. The second part of the talk will cover the OSSI initiative, exploring its objectives, strategy, and innovative solutions. Throughout the presentation, I will provide insights into the requests, strategies, and solutions behind both BEDI and OSSI. By the end, you will gain a comprehensive understanding of how NASA's Earth Science Data Systems have evolved over the years and witness the organization's commitment to advancing an open-source and collaborative approach to data science. Join me for an enlightening exploration into the future of Earth science data and the pivotal role played by NASA in shaping this transformative landscape.
Jennifer Wei↗
Enabling Space Biology Knowledge Discovery Through Biospecimen Sharing: The NASA Biological Institutional Scientific Collection and Space Microbial Culture Collection
NASA and international partners have conducted experiments in space to understand the biological impacts and address hazards to health. The resulting basic and applied science is imperative to enabling humanity to venture back to the Moon and then to Mars and beyond. Sending organisms into space is a costly endeavor. All biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (NBISC) to maximize the scientific return. The NASA Biological and Physical Sciences (BPS) Division ‘Open Science’ endeavor includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, the Ames Life Sciences Data Archive, and NBISC to integrate extensive data and biospecimen resources from spaceflight and/or ground-based analog experiments. NBISC biospecimens are collected and preserved according to well-established standard operating procedures to maintain scientific quality and are available on-request by the international scientific community. NBISC currently stores over 32,000 biospecimens from Shuttle, International Space Station, and ground-based space analog investigations. Tissue sharing has resulted in at least 33 publications since 2011 and 48 requests since 2016. Many requests for NBISC biospecimen come from first-time investigators who subsequently submit grants as the port-of-entry into the field of space biology. Some NBISC biospecimens have been awarded to NASA Genelab, who then generate various ‘Open Science’ -omics data sets on their platform for bioinformatics. Other NBISC biospecimen awards have led to multiple studies such as fecal microbiome analysis, DNA damage analysis using single-cell DNA sequencing, enzymatic-pathway identification involved in spaceflight muscle atrophy, and characterization of ocular morphological changes. Of note, NBISC has expanded to include a new Space Microbial Culture Collection (SMCC) for the collection, identification, documentation, long-term preservation, and distribution of space-related microbial isolates.
biospecimens↗
Public-Private Partnerships to Enable Discovery, Access, and Use of NASA’s Open Earth Science Datasets
Knowledge transfer between public research institutes and private entities is an essential component of the open science movement. While both public and private institutions are making research advances in technologies, organizational boundaries can hinder knowledge transfer. Productive public-private collaboration frameworks are needed to advance research further.
Elizabeth Fancher↗
Making Dataset Quality Information FAIR: Supporting Open-Source Science and Enhancing (Re)Use and Trustworthiness of Scientific Data
- Quality information should be documented and readily shared within and across domains. - Sharing of dataset quality information supports open science and trustworthiness of scientific data. - Dataset quality is more than data quality. - Quality tends to be domain-specific and context-dependent. - Community guidelines provide practical steps towards FAIR dataset quality information.
Ge Peng↗
High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice
Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.
James Casaletto↗
Informing Wildfire Needs: The Expanded User Interface of NASA's Fire Information for Resource Management System (Firms)
As the global community continues to experience, and respond to, living in a changing environment, access to tools, technologies, and timely data utilized by an increasingly diverse set of stakeholders is increasing. This year, 2023, has thus far seen an unprecedented number of extreme events, increasingly driven by changes in the climate and a strong 2023 ENSO pattern. In Canada, a record number of wildfires, and associated weather events, evacuations, and infrastructure and habitat destruction has taken place, and is ongoing. Large swaths of Greece have experienced similar wildfire destruction. Most recently, Maui has experienced destructive wildfires, and early 2023 saw massive wildfires in Chile. NASA's Fire Information for Resource Management System, or FIRMS, has a fifteen-year history of providing timely and comprehensive data and information on wildfires to stakeholders. FIRMS was initially developed in 2007 by the University of Maryland, with funds from NASA's Applied Sciences Program and the United Nations Food and Agriculture Organization (UN FAO), to provide near real-time active fire Locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information. FIRMS has consistently evolved to address the needs of stakeholders Living in a changing environment; in 2012 it transitioned to NASA LANCE and in 2021 through a partnership between NASA and the US Forest Service, an updated version of FIRMS was released for the US and Canada. As NASA and other federal agencies continue to accelerate Open Science through integrated efforts such as the Year of Open Science, the provision of readily discoverable, findable, accessible, interoperable, reusable data represents a major focus to facilitate equitable outcomes. FIRMS supports this acceleration in Open Science by continuing to provision data and information for its traditional user base, while addressing the novel user needs of an increasingly diverse set of stakeholders seeking robust, reliable, transparently generated data and information. Increasingly, FIRMS is utilized by citizen scientists and individuals directly affected by wildfires - through evacuations, risks to structures/homes, poor air quality. etc. FIRMS has also been Leveraged to detect and assess the impacts resulting from ongoing conflicts. This further highlights the multi-faceted impacts of wildfires and other events. In the Fall of 2023, FIRMS will release an expanded User Interface (UI). This interface captures and reflects the needs of, and input from, a multitude of users. These users range from federal agency representatives to non-government organizations to the private sector to citizen science entities. To respond to this expansive and diverse user need base, the updated FIRMS UI will capture a range of features to support those beginning to explore the range of data and tools available to inform wildfire awareness and knowledge. These users are supported through a Basic Mode interface, furnishing access to a light set of functionalities that provision straight-forward, readily usable information and data, and ingestible knowledge. The Advanced Mode interface supports those stakeholder groups already proficient in navigating FIRMS. These stakeholders, representing fire managers and others, perform active fire management and tactical wildfire response activities. For these stakeholders, additional datasets have been included which require in-depth knowledge of both the utility as well as the caveats of such datasets. Additional functionalities have also been embedded to aid specific user queries. The expanded UI will introduce a new Experimental Mode. The focus of this UI will be to support the provision of emerging and innovative datasets that are in development for review and comment by the user community Examples include post-fire products generated by NASA's Earth Information System (EIS) Fire. This presentation will provide an overview of the expanded FIRMS UI. We will discuss how this UI is designed to be scalable and support the unique needs of an expanding and diverse user base. We will highlight key features, elements, and datasets, and describe how user needs have informed and guided the design of the UI. We will also share recent use cases to convey, and increase awareness, among conference participants. As the global community faces more extreme wildfires, due to climate variability and change, there is an increased need for reliable data to inform, manage, and mitigate the impacts of these events. Through this work, NASA FIRMS is striving to level the playing field, by making information accessible to all; from policy makers to the private sector to historically marginalized communities. In doing so, NASA is promoting the all-hands-on-deck response needed to minimize the impacts of wildfires and harness the strengths of open science to address the greatest environmental challenge faced.
Jenny Hewson↗
NASA Earth Science Data Systems Evolution from Big Earth Data Initiative (BEDI) to Open-Source Science Initiative (OSSI)
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Jennifer Wei↗
Enabling Space Biology Knowledge Discovery Through Biospecimen Sharing: The NASA Biological Institutional Scientific Collection
NASA and international partners have conducted experiments in space to understand the biological impacts and address hazards to health. The resulting basic and applied science is imperative to enabling humanity to venture back to the Moon and then to Mars and beyond. Sending organisms into space is a costly endeavor. All biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (NBISC) to maximize the scientific return. The NASA Biological and Physical Sciences (BPS) Division has an ‘Open Science’ endeavor which includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, the Ames Life Sciences Data Archive, and NBISC. Its purpose is to integrate extensive data and biospecimen resources from spaceflight and/or ground-based analog experiments. NBISC biospecimens are collected and preserved according to well-established standard operating procedures to maintain scientific quality and are available on-request by the international scientific community. NBISC currently stores over 32,000 biospecimens from Shuttle, International Space Station, and ground-based space analog investigations. Tissue sharing has resulted in at least 33 publications since 2011 and 48 requests since 2016. Many requests for NBISC biospecimen come from first-time investigators who subsequently submit grants as the port-of-entry into the field of space biology. Some NBISC biospecimens have been awarded to NASA Genelab, who then generate various ‘Open Science’ -omics data sets on their platform for bioinformatics. Other NBISC biospecimen awards have led to multiple studies such as fecal microbiome analysis, DNA damage analysis using single-cell DNA sequencing, enzymatic-pathway identification involved in spaceflight muscle atrophy, and characterization of ocular morphological changes. Of note, NBISC has expanded to include a new Space Microbial Culture Collection (SMCC) for the collection, identification, documentation, long-term preservation, and distribution of space-related microbial isolates.
Ryan T. Scott↗
AIST Technology Perspectives for ESO Mission Processing and Open-sourced Science
NASA is formulating the Earth System Observatory (ESO), a set of Earth-focused missions to provide key information to guide efforts related to monitoring climate change, mitigating disasters, fighting forest fires, and improving real-time agricultural processes. Within that framework, this presentation will introduce the Advanced Collaborative Frameworks (ACF) concepts that have been developed as part of the Advanced Information Systems Technology (AIST) Program, demonstrating the capability for facilitating open-sourced science and with a strong transition/infusion potential.
Jacqueline Le Moigne↗
Transform Your Search Capability Using Insight Engines
Enable rapid discovery of NASA’s open science data, software and documentation. Support NASA’s open science goals and infrastructure. Promote interdisciplinary science. Prototype emerging technologies and search techniques including Large Language Models.
Kaylin Bugbee↗
Microbial Vessel for Impedance Spectroscopy and Electrochemistry (Mvise): an Extensible, Interoperable Data Acquisition Platform for Liquid Culture Studies in Space Biology Research
The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.
Stephen Lantin↗
Space Crop Production Gaps and Challenges
As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.
Gioia Donna Massa↗
Space Crop Production Gaps and Challenges
As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.
Gioia Massa↗
Cryosphere Sciences Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science
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Sandra O. Brugger↗
Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)
The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.
cloud computing↗
The Nasa SRA Process as It Relates to Open-Source Workflows Developed for GeneLab Data Processing
To release open, standards-compliant processed data sets in the Open Science Data Repository (OSDR), the GeneLab Data Processing team works with the scientific community through the OSDR Analysis Working Groups to design and build open-source data processing pipelines. Once baselined internally, these pipelines are wrapped into workflows and published on the NASA GeneLab Data Processing public GitHub repository along with detailed instructions for installation and use. Each workflow must be approved through NASA's Software Release Authorization (SRA) process prior to publishing. However, the SRA process lacks sufficient documentation and clarity regarding which forms are applicable for new open-source software that utilizes publicly available 3rd party tools, and the SRA process can take several months to complete, making sharing software outside of NASA cumbersome and in contradiction with the concept of Open Science. Furthermore, the SRA process was designed as a one-size fits all approach and thus many of the questions asked are not applicable to our open-source workflows. Here we describe the software provided on the NASA GeneLab Data Processing GitHub repository, summarize our experiences with the SRA process to release these software, and propose a more stream-lined approach for review of open-source projects.
Software Release Authorization↗