The near-Earth space environment is seeing an increase in activity as more nations and organizations engage in astronomical and spaceflight endeavors. This translates to a growing wealth of data and knowledge we can tap for current generations and posterity. Interdisciplinary and diverse perspectives can be applied to leverage that content via: data analysis, search, modeling; informatics, knowledge management; knowledge representation and reasoning (KRR), artificial intelligence (AI); etc. Example techniques are the development of
knowledge organization systems (KOS), such as
controlled vocabularies, thesauri,
metadata schemas,
conceptual data models,
semantic models, ontologies and
knowledge graphs [Rovetto, 2017].
- Space data is understood to include: data about exo-atmospheric space (colloquially: outerspace) phenomena, e.g., space science data such as solar and space weather, solar system, planetary; data from observations of that space; data collected from satellite spacecraft; data about satellites & their activity & contents; celestial body samples; spatio-temporal concepts; misc.
Goals:This session aims to bring together persons and organizations interested in
space data, broadly construed (from astronomy to astronautics to other space sceince and broader
space-related topics
). Speakers will discuss data science, space and knowledge modeling topics. The session hopes to:
(
i) identify various types of space data; desiderata thereof, gaps or problems with dealing with the data; And...
(
ii) discuss whether and how presented content and KOSs can be useful, e.g., identifying techniques to organize and analyze space data, and terminology, with an emphasis on
knowledge representaiton/modeling,
semantic data modeling, conceptual modeling, graph structures, and
MBSE (model-based systems engineering). Sharing experiences are encouraged, e.g., challenges, desiderata with your space data, or with specific types or technology related to KOS or semantic technology. And...
(
iii)
Identify interest and formal support for the KOS/space ontology project presented [
Space knowledge modeling] that will be presented.
- Project goals include exploring the utility of ontologies to support space data, and specific Earth-impacting phenomena such as space debris [Rovetto, ESIP FundingFriday, 2020] [Rovetto, ESI, 2015], astronomical phenomena, and spaceflight observations and operations [Rovetto, & Kelso, 2016][O'Neil, Rovetto, 2020-2021].
- Attendees may be interested in supporting the projects concepts for developing international space data systems [Rovetto, 2016] for the global community, if not for specific organizations.
The session will hopefully draw interest (and be attended by) persons and organizations with formal opportunities--work collaborations and educational--for indivdiuals interested in these topics, thereby fostering cooperative, educational and career-building values.
RelevanceThis session is relevant for this years theme of 'Data for All People: From Data Generation to Data Use and Understanding' in various ways. First, trust in data is very pertinent for the domain of space. In particular, spaceflight has historically been a governmental or military domain, where security and trust are both critical and challenging. Ideas about how to facilitate and create trust in that and other space communities are in demand, and relevant to AI techniques, and social and societal aspects, etc. Second, applications & benefits of spaceflight activities has reached people across the globe [Rovetto, 2013]. These include Earth observation, e.g., weather and environmental data; technological spinoffs; biological and medical experimentation; and scientific discovery via astronomical observations, e.g., stellar physics, observations of the sun; origins of Earth and planetary evolution; etc. In recent times, some companies ambitiously develop fleets of orbiting spacecraft provide their services. This simultaneously means a promulgation of both data and space-based objects.By bringing together persons interested in space data from astronomy to astronautics, we can better identify avenues to formally cooperate, innovate, and potentially share data, information and knowledge.
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How to Prepare for this Session1)
Review generic material on knowledge organization systems
, representation
, ontology
, semantic & conceptual modeling, etc. Examples include:
2)
Review description references & related references: - [Rovetto, Space Knowledge Modeling] - https://purl.org/space-ontology
- [Rovetto, ESIP FundingFriday Award, 2020] https://wiki.esipfed.org/File:ROVETTO.pdf
- [Rovetto, 2021 "Semantic Orbital Sweep (SoS): Developing Knowledge Graphs and an Ontology Suite to Support Orbital Debris Remediation & Spaceflight for the Global Community" post-FF presentation]
- Rovetto, 2020 Esip Presentation "Astronautical knowledge modeling to improve spaceflight safety and data management - a call for project partners and opportunities". (spaceflight aspect of the project)
- [Rovetto, 2016]
- [Rovetto, 2017] Ontology-based Knowledge https://iafastro.directory/iac/paper/id/40147/summary/
- [Rovetto, ESI, 2015] "An Ontological Architecture for Orbital Debris Data"
- [O'Neil, Rovetto, 2017-2021] https://ntrs.nasa.gov/citations/20210000030
- [Rovetto, 2013] https://www.sciencedirect.com/science/article/abs/pii/S0265964613000660
Contact: https://ontospace.wordpress.com/contact
Services (ontology & vocabularies).
