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Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. 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, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, 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 or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), 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 inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, 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 thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗

Standard terminology in the laboratory and classroom

Each of the materials produced by modern technologists is associated with a family of immaterials--all the concepts of substance, process, and purpose. It is concepts that are essential to transfer knowledge. It is concepts that are the stuff of terminology. Terminology is standardized today by companies, standards organizations, governments, and other groups. Simply described, it is the pre-negotiation of the meanings of terms. Terminology has become a key issue in businesses, and terminology knowledge is essential in understanding the modern world. The following is a introductory workshop discussing the concepts of terminology and methods of its standardization.

Strehlow, Richard A.↗

Re-evaluation of cosmic ray cutoff terminology

The study of cosmic ray access to locations inside the geomagnetic field has evolved in a manner that has led to some misunderstanding and misapplication of the terminology originally developed to describe particle access. This paper presents what is believed to be a useful set of definitions for cosmic ray cutoff terminology for use in theoretical and experimental cosmic ray studies.

Cooke, D. J.↗

Comments on the Terminology of "Convectively-Coupled Kelvin Waves"

The terminology "convectively-coupled Kelvin waves" has been used frequently in the literature to refer to the 15 m/s eastward-moving planetary and large-scale waves in the tropics. This note points out that this terminology is not appropriate, since these waves contain Rossby waves and mixed Rossby-gravity waves also. The significance of pointing out this misnomer is that a better understanding of these waves may contribute to the search for their cause.

Chao, Winston C.↗

Toward an agreement on terminology of nuclear and subnuclear divisions of the motor thalamus

The nomenclature most commonly applied to the motor-related nuclei of the human thalamus differs substantially from that applied to the thalamus of other primates, from which most knowledge of input-output connections is derived. Knowledge of these connections in the human is a prerequisite for stereotactic neurosurgical approaches designed to alleviate movement disorders by the placement of lesions in specific nuclei. Transfer to humans of connectional information derived from experimental studies in nonhuman primates requires agreement about the equivalence of nuclei in the different species, and dialogue between experimentalists and neurosurgeons would be facilitated by the use of a common nomenclature. In this review, the authors compare the different nomenclatures and review the cyto- and chemoarchitecture of the nuclei in the anterolateral aspect of the ventral nuclear mass in humans and monkeys, suggest which nuclei are equivalent, and propose a common terminology. On this basis, it is possible to identify the nuclei of the human motor thalamus that transfer information from the substantia nigra, globus pallidus, cerebellum, and proprioceptive components of the medial lemniscus to prefrontal, premotor, motor, and somatosensory areas of the cerebral cortex. It also becomes possible to suggest the principal functional systems involved in stereotactically guided thalamotomies and the functional basis of the symptoms observed following ischemic lesions in different parts of the human thalamus.

Non-NASA Center↗

Toward an agreement on terminology of nuclear and subnuclear divisions of the motor thalamus

The nomenclature most commonly applied to the motor-related nuclei of the human thalamus differs substantially from that applied to the thalamus of other primates, from which most knowledge of input-output connections is derived. Knowledge of these connections in the human is a prerequisite for stereotactic neurosurgical approaches designed to alleviate movement disorders by the placement of lesions in specific nuclei. Transfer to humans of connectional information derived from experimental studies in nonhuman primates requires agreement about the equivalence of nuclei in the different species, and dialogue between experimentalists and neurosurgeons would be facilitated by the use of a common nomenclature. In this review, the authors compare the different nomenclatures and review the cyto- and chemoarchitecture of the nuclei in the anterolateral aspect of the ventral nuclear mass in humans and monkeys, suggest which nuclei are equivalent, and propose a common terminology. On this basis, it is possible to identify the nuclei of the human motor thalamus that transfer information from the substantia nigra, globus pallidus, cerebellum, and proprioceptive components of the medial lemniscus to prefrontal, premotor, motor, and somatosensory areas of the cerebral cortex. It also becomes possible to suggest the principal functional systems involved in stereotactically guided thalamotomies and the functional basis of the symptoms observed following ischemic lesions in different parts of the human thalamus.

Review, Tutorial↗

Terminology of ranging measurements and DSS calibrations

A set of basic terminology related to deep space ranging measurements is proposed. Calibration equations are derived for the dish-mounted zero delay device method for 26-m antenna systems and the translator method for 64-m antenna systems.

Komarek, T. A.↗

Variant terminology

A system called Variant Terminology Switching (VTS) is set forth that is intended to provide computer-assisted spellings for terms that have American and British versions. VTS is based on the use of brackets, parentheses, and other symbols in conjunction with letters that distinguish American and British spellings. The symbols are used in the systems as indicators of actions such as deleting, adding, and replacing letters as well as replacing entire words and concepts. The system is shown to be useful for the intended purpose and also for the recognition of misspellings and for the standardization of computerized input/output. The VTS system is of interest to the development of international retrieval systems for aerospace and other technical databases that enhance the use by the global scientific community.

Buchan, Ronald L.↗

Terminology and concepts of control and Fuzzy Logic

Viewgraphs on terminology and concepts of control and fuzzy logic are presented. Topics covered include: control systems; issues in the design of a control system; state space control for inverted pendulum; proportional-integral-derivative (PID) controller; fuzzy controller; and fuzzy rule processing.

Aldridge, Jack↗

Lunar Mega Project: Processes, Work Flow and Terminology of the Terrestrial Construction Industry versus the Space Industry

Recent developments around the world show an increased interest and international activity toward developing a lunar surface human and robotic presence with a long term, sustainable vision. In Europe, the construction of a "Moon Village" has been proposed, and China has stated its intention to build a research station with a crew at the lunar South Pole. Russia stated it will land cosmonauts on the Moon in the 2030's. India has sent an orbiter, a robotic lander, and rover to the Moon. The USA intends to land the first woman and a man on the Moon by 2024 to initiate a sustained human lunar presence.A lunar research station with associated commercial activities will require infrastructure to become a permanent capability. Landing and launch pads, propellant storage and distribution farms, spacecraft access and handling structures, cranes, blast protection berms or walls, roads, graded areas, dust stabilized areas, foundations, parking lots, radiation shelters, micro-meteorite protection hangars, habitats and other human shelters, greenhouse farms, utility trenches, power plants, industrial water and oxygen extraction plants, communications antenna towers, thermal protection, mining zones, crater access and sub-surface access will be required to create a safe and sustainable lunar operations capability. This infrastructure will require significant construction activities in an extreme environment, with risky and expensive operations. On Earth, there are similar large and expensive projects (>$1 Billion) in difficult locations that attract a lot of public attention. These are known as "Mega Projects" and examples include bridges, tunnels, highways, railways, airports, seaports, power plants, dams, wastewater projects, Special Economic Zones (SEZ), oil and natural gas extraction projects, public buildings, information technology systems, aerospace projects, and weapons systems. Large consortiums consisting of public and private entities typically implement these infrastructure Mega-Projects.This paper will compare the typical design process, project management process, and work flow in the terrestrial construction industry to the space industry in order to create a better understanding between the terrestrial construction industry and the space industry, to further enable collaboration on a lunar Mega Project to build infrastructure on the Moon. In addition, a glossary of respective industry terminology with annotated linkages and definitions has been compiled. This information will enable contracts and business practices to be formulated for generating requests for proposals (RFP) by governments to consortiums consisting of construction and space industry companies that will bid on Lunar Infrastructure Projects that could lead to contracts to build the permanent capabilities.

Robert P Mueller↗

Digital Elevation Models: Terminology and Definitions

Abstract:Digital elevation models (DEMs) provide fundamental depictions of the three-dimensionalshape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record theinterface between the atmosphere and the lithosphere using a discrete two-dimensional grid, withcomplexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere.The treatment of DEM surfaces, affected by these intervening spheres, depends on their intendeduse, and the characteristics of the sensors that were used to create them. DEM is a general term,and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) recordthe treatment of the intermediate surfaces. Several global DEMs generated with optical (visible andnear-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars andproducts of satellite altimetry, share the common characteristic of a georectified, gridded storagestructure. Nevertheless, not all DEMs share the same vertical datum, not all use the same conventionfor the area on the ground represented by each pixel in the DEM, and some of them have variable dataspacings depending on the latitude. This paper highlights the importance of knowing, understandingand reflecting on the sensor and DEM characteristics and consolidates terminology and definitions ofkey concepts to facilitate a common understanding among the growing community of DEM users,who do not necessarily share the same background

Peter L Guth↗

Approximate reasoning using terminological models

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved.

Yen, John↗