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Jessica A Keune

Publications and source records attributed to Jessica A Keune.

Rediscovering Apollo Biomedical Data to Support Artemis: The Apollo Records Synthesis Project

With the first crewed missions of the Artemis Program on the horizon, including the return of humans to another planetary surface, the space medicine and research communities have a renewed interest in buying down risk on these missions using historic Apollo datasets. Archivists with NASA’s Life Sciences Data Archive (LSDA) and epidemiologists with the Lifetime Surveillance of Astronaut Health (LSAH) are collaborating on a project aiming at improving access to historic datasets from the Apollo Program. The Apollo Records Synthesis Project (ARSP) seeks to expand the available historic biomedical knowledge base by examining physical records located across a wide range of collections, including examples such as pre-flight and post-flight physicals, lab reports, and handwritten flight surgeon and biomedical engineer logs from Apollo missions. The ARSP team has been able to identify several previously undocumented sources of biomedical information from Apollo missions. In the future, the team will modernize record storage and accessibility of these resources using digitization and natural language processing. This poster will discuss the progress of the project, give context to the dual research-clinical care nature of the records, and highlight the challenges and opportunities in using data from historical records. This poster will also provide information on how researchers can request access to datasets from these records.

life sciences↗

The Field Guide to NASA’s Life Sciences Data Repositories

For over 30 years, NASA has invested in life sciences research both in space and on the ground. Data accessibility is an important tool for researchers, and NASA has committed to preserving this vital resource for ongoing use. The Life Sciences Data Archive’s multi-center collaboration between NASA’s Johnson Space Center, Ames Research Center, and Kennedy Space Center is geared toward preserving unique and high-value data from a wide variety of disciplines, data collection methods, and species within NASA’s Life Sciences Portal (NLSP). The data generated by the Human Research Program (HRP) require a systematic approach to data preservation that accounts for diverse data sources, formats, physical storage requirements, and security and privacy protections. This poster presentation will provide a guide to the repositories where the various types of human, non-human animal, plant, and microbial data NASA generates are archived and tips for navigating these data collections. Topics will include where different types of data, metadata, and biospecimens are archived or preserved, how the federated repositories work together as a data preservation ecosystem, and how researchers can access each repository’s collections.

Robert S Beaton↗

Increasing Data Discovery and Re-Use: The Space Life Sciences Ontology

Two of the most important goals of the adoption of the FAIR principles are increasing the ability of agents to find and re-use research data. Achieving these goals for space life sciences research is even more pressing, given the relatively expensive and scarce nature of these data. We have reported in the past on the progress made by exemplar life sciences data systems towards implementing FAIR, showing gaps particularly in the “interoperability area” of the principles; the lack of common conceptual models for space life science research is one reason for this gap. There were few available resources that define, annotate, categorize or otherwise relate various kinds of metadata describing the acquisition, nature, and intent of investigational space life sciences data. To address this gap, NASA is working with the Open Biological and Biomedical Ontology Foundry (https://obofoundry.org/) to develop the Space Life Science Ontology (SLSO) that is intended to support archival and other kinds of systems that operate using these data. The scope of the ontology includes concepts regarding those aspects of investigation design and execution specific or unique to space environments, such as types of specialized equipment, operating organizations, and documentation. The ontology is continually being developed and published to the life science community (https://github.com/nasa/LSDAO/); at the time of this publication, the SLSO newly and uniquely defines 30 types (classes), 90 properties, and 14 relations specific to space life sciences metadata. In addition, the SLSO reuses (imports) some 2,360 types (classes), 49 properties, and 393 relations from other ontologies that are relevant to these kinds of metadata. In addition to its role as a common conceptualization for space biomedical research activities, the SLSO can also be used to provide automated support for traditionally difficult and expensive activities such as data curation and cross-system data integration and analysis.

fair↗

Transformation of the NASA Life Sciences Portal to a FAIR Data Point

The FAIR principles emphasize optimizing metadata, the vast majority of which are textual in nature, and often organized into attribute name-value pairs. This uniformity has led to the development of guidelines and best practices for providing programmatic access to scientific data through their metadata, yielding the first iteration of the FAIR Data Point Specifications (FDPS). A key feature of the FDPS is its support for automated agents seeking and fetching data without first needing to learn a plethora of different application programming interfaces. These software agents can interrogate metadata catalogs that adhere to FDPS in a uniform manner because each catalog describes itself and its metadata schema consistently. This approach enhances the sustainability of data retrieval support, allowing systems to refine and update their metadata schemas as needed and without requiring data-seeking software agents to change how they interrogate FDPS catalogs. An essential aspect of the FDPS is the standardization of data catalog semantics, which formalizes concepts such as “metadata” and “metadata service” and links them to other concepts specifications including the Data Catalog Vocabulary (DCAT), a W3C standard that is also the basis of NASA-STD-2831 “Metadata Standard for Data Discoverability,” authored by NASA’s Office of the Chief Information Officer. The FDPS references DCAT (version 2) elements which focus on the distribution of datasets and support the goal of stream-lined catalog integration across repositories for improved data discovery. Additionally, the FDPS also prescribe the use of Linked Data Platform elements for data catalog-metadata record containment descriptions, allowing users to ascertain which data and metadata belong to which catalogs. NASA’s Life Sciences Portal is implementing the FDPS while formalizing its metadata schema to support the accelerated synthesis of knowledge from space life sciences investigations.

platform↗

Governing Data Findability, Accessibility, Interoperability and Reusability (FAIR) Compliance

The most recent data strategy documents at both the federal and NASA levels stipulate that systems should strive for the data they manage to be Findable, Accessible, Interoperable, and Reusable (FAIR). The NASA Life Sciences Portal (NLSP) has already begun leading efforts in this area for HRP, initiating efforts to comply with the FAIR principles. The broad interpretation of the FAIR principles has led to a plethora of tools that use a splay of metrics specifically but variably developed to judge how compliant data and systems are with the principles. A recent review [3] identified and studied 1,180 metrics across 20 publicly available tools for checking FAIR compliance of data and systems. Because of their very recent development, many organizations and data systems managers and developers have not yet had adequate time or resources to understand these FAIR compliance tools and metrics, their variations in design, accuracy or ease of application to their specific data sets and systems. Thus, it would be best for larger organizations like NASA to approach formulating a strategy for governance of FAIR compliance that can be flexibly applied and is adaptable to an evolving awareness knowledge of FAIR compliance methods and tools. In September 2024, the NASA Science Mission Directorate(SMD) organized a workshop on NASA science data repositories, including the topics of implementing FAIR and governing FAIR compliance across SMD. The initial part of these FAIR discussions focused on developing consensus around required science metadata fields. This is challenging given the diverse nature of NASA’s scientific data portfolio, the variety of metadata models and vocabularies used, and variable level of resources available to curate these data. Later discussion focused on three possible approaches to governing FAIR compliance: distributed, in which various programs, projects or systems define their own methods for assessing FAIR compliance, reporting results up appropriate management lines; centralized, in which higher-level organization(s) specify compliance tools or methods for the various data systems; and multi-level, in which a group comprised of individuals with expertise from multiple levels with organizations is formed to provide guidance and/or specifications for governing FAIR compliance. We report on the recommendations this session yielded, and how these might be shaped specifically to help implement and govern the compliance with FAIR of Human Research Program data and systems.

governance↗