Orbital debris ontology, terminology, and knowledge modeling

Abstract

ABSTRACT The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does the risk of collision, as well as the volume of associated data. It is, however, an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data management and knowledge modeling aspect of developing solutions for a sustainable and safe orbital space environment. An in-progress work to develop an orbital debris reference ontology [Rovetto, 2015] is summarized in order to discuss knowledge modeling for orbital debris. The formal analysis of this effort can contribute to standards development, as well as terminological and policy challenges. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015] proposed ontology development for the orbital debris and broader space domain. This paper summarizes concepts from that paper, and subsequently developed concepts [2-9]. See also https://purl.org/space-ontology and https://purl.org/space-ontology/odo . Ontology engineering is an interdisciplinary area of research related to knowledge representation and reasoning in artificial intelligence, model-based systems engineering, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge, beliefs, or assertions are stored using formally defined terms. This knowledge base is reasoned over to yield answers to database queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, and enterprise knowledge graphs. Ontologies aim to support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO) [1], and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford automated reasoning tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) [2] is part of the overall Orbital Space Ontology concept, which is conceived as a unifying domain reference ontology. It aims to provide a knowledge representation structure of orbital space, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and a means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications include web-based platforms, web apps, visualizations, modeling and simulations. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, conceptual, terminological, and ontological analysis can make helpful contributions to such efforts as the Space Debris Mitigation Requirements by developing more precise, consistent and coherent terms and definitions. Other projects can also use ODO (and its related ontologies) as a common knowledge model, metadata set, taxonomy or vocabulary. Readers interested in supporting development are encouraged to make contact.