An ontology for satellite databases

Abstract

Abstract. This paper demonstrates the development of ontology for satellite databases. First, I create a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD for short), called the UCS Satellite Ontology (or UCSSO). Second, in developing UCSSO I show that The Space Situational Awareness Ontology (SSAO)--an existing space domain reference ontology--and related ontology work by the author (Rovetto 2015, 2016) can be used either (i) with a database-specific local ontology such as UCSSO, or (ii) in its stead. In case (i), local ontologies such as UCSSO can reuse SSAO terms, perform term mappings, or extend it. In case (ii), the author_s orbital space ontology work, such as the SSAO, is usable by the UCSSD and organizations with other space object catalogs, as a reference ontology suite providing a common semantically-rich domain model. The SSAO, UCSSO, and the broader Orbital Space Environment Domain Ontology project is online at https://purl.org/space-ontology and GitHub. This ontology effort aims, in part, to provide accurate formal representations of the domain for various applications. Ontology engineering has the potential to facilitate the sharing and integration of satellite data from federated databases and sensors for safer spaceflight.

Construction of Space Object Situation Information Service Based on Knowledge Graph

“…Based on [7] and [8], Rovetto constructed a generalized ontology oriented to space objects, and provided taxonomies and definitions for them. Based on ongoing research, the Union of Concerned Scientists' (UCS) satellite ontology [10] was constructed based on the UCS satellite database, and the application of ontology to the European Space Agency (ESA) SSA project was taken as an example [11]. Rovetto researched the knowledge management of space data based on ontology, and analyzed the application of ontology in different fields of space science in detail [12].…”

“…The azimuth A is defined as the angle from the positive direction of X -axis to SW clockwise, ranging from 0 • to 360 • ; the pitch P is defined as the angle between SD and the XOY plane, ranging from −90 • to 90 • , and pointing along the Z -axis is positive and in the other direction is negative. We use (x S , y S , z S ) and (vx S , vy S , vz S ) to represent the position and velocity of S, and (x D , y D , z D ) and (vx D , vy D , vz D ) to represent the position and velocity of D; then, A and P of D relative to S can be expressed by (10) and (11), respectively.…”

From Data Silos to Intelligent Web for RSO Recognition

“…Due to barriers made by humans or caused by technical limitations, the multi-source RSO data form "data silos" (15,16) . The biggest advantage of RSO domain ontology is that the ontology represents multi-source data to find a way out of the "data silos" dilemma (15) .…”

“…Ontologies have many applications in integrating diverse data and representing multiple types of knowledge (1,2,15,16) , especially in the field of space situational awareness, with its unique advantages. For example, ontologies are used to represent soft and hard data for buildings, and cross-domain data islands are integrated to achieve optimal performance of building performance (12) .…”

“…For example, ontologies are used to represent soft and hard data for buildings, and cross-domain data islands are integrated to achieve optimal performance of building performance (12) . In space situational awareness domain, the space object ontology can integrate multi-source RSO data (15,16) , represent a variety of RSO features, and enhance RSO characterization and provide robust entity tracking (15) . OntoStar (Ontology of Space Target Automatic Recognition) integrates domain knowledge and knowledge obtained by machine learning such as tactics, regulations, and inductive rules estimating specific features, targeting at solving RSO classification problem when some features are missing (2) .…”