About

Below is a summary about: services & products, the provider / author, and the related project you can support.
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Services & Products

  • Products for sale include papers and presentations, and bespoke ontology models.
  • Services for hire include basic knowledge modeling and terminology activities (including invited talks & tutoring), e.g., metadata & ontology development & curation, conceptual analysis & modeling, vocabulary refinement & harmonization, ethical topics, methodology, classification, etc. To directly hire, visit this link.

The Project (call for support)

The Orbital Space Domain Reference Ontology by Robert J. Rovetto (email) is a living work to create knowledge representation models, consisting of a suite of human and computer readable metadata sets, vocabularies, ontologies, and knowledge graphs for astronautics, astronomy and other space topics. Systematically developed for various use-cases such as: data search, retrieval, integration; automated reasoning; knowledge discovery; MBSE; semantic annotation, AI applications, etc., they will offer metadata, terminology, classifications, and semantic/conceptual models. They are potential standards via their consistent, accurate and reusable terms and definitions.

Author’s Invitation: The project will benefit from an environment to continue development in a sustainable and secure manner. As a personal project, sponsors or other types of formal support are invited to make contact. Since conception in 2011, the project has been my hopeful vision as my PhD thesis; I regularly apply to programs while searching for other opportunities (potential collaborators or employers). If you find value in this project, consider supporting by inviting me to enroll as your PhD student to realize its vision, being financial patron, donating, sponsoring, mentoring, or hiring me. Schedule a meeting at this link or send a message.

Project Vision & Goals
  • To support safe spaceflight and space situational awareness (SSA).
  • To support astronomy and other space topics.
  • To support artificial intelligence (AI) applications for spaceflight operations.
  • To contribute to and improve aerospace terminology and standards.
  • To make spaceflight safer by facilitating data sharing & fusion for more comprehensible collaborative global SSA.
  • To determine the utility of knowledge-based techniques and technology.
  • To complete a suite of reusable modular ontologies: accurate domain models that capture astronautical knowledge, and describe the data, systems and the space domain.
  • To provide comprehensible, widely-applicable and neutral vocabularies, metadata sets, classifications and ontologies that can annotate data and serve as standards for the global astronautical community.
  • To be used by a broad spectrum of users: industry, government, military, and academia.
  • Ontology-annotated interactive dynamic 3D Visualizations of the orbital environment.
  • To build space ontologies for you: individuals, companies, agencies, & universities.
Development Needs
(Contact if you can support)
  • Experts (a team) in: Computer scientists, AI experts, Semantic web experts, etc.
  • Services: query-writing, web programming, troubleshooting tools & plugins, …
  • Data sources, Datasets & Use-cases.
  • A secure hosting location and platform.
  • Business dev., and legal support.
  • A graphical user interface, and visualization system, that dynamically & interactively presents the model(s) (e.g., in graph form) and applications of it on datasets.
  • An online community development platform and user interface with dynamic list, search, visualization, graph, and other features.
Potential Benefits & Users
  • Exploring the potential utility of knowledge organization systems.
  • The SSAO has been used by a solar system visualization project by NASA personnel
  • Sufficiently developed, the ontologies can be used by academia, government, industry, specific projects, or other systems metadata schemas, ontologies, etc.
  • Neutrality & Objectivity… through systematic analysis, and principled development.
  • Diverse perspectives: conceptual, semantic, lexical, ontological analysis
  • Reduces complexity in programmingby providing a reference model outside of the code (ontologies can be edited separately).
  • Makes data self-describing… as a semantic layer on databases.
  • Semantic interoperability among disparate databases with similar content.
  • Alignment among distinct vocabularies, and among disparate databases.
  • Semantic search, data retrieval, and automated machine reasoning.
  • Reduce ambiguity. Terminological normalization.
  • Potentially resolve terminological & definitional questions in space policy & law
  • Potential for innovation: applied to visualizations, simulations, model-based systems engineering (MBSE), AI, and conceptual modeling.

About the Author

Mr. Robert J. Rovetto – Formal ontologist | Conceptual modeler | Consultant | Aspiring student.
Author of articles on spaceflight semantics, space policy, symbolic logic, and philosophy. Grant-writing, and (inter)national standards development experience.

  • Actively open to PhD study opportunities, worldwide.
  • Research interests: spaceflight, small-boat operations & maritime search & rescue, philosophy, knowledge representation, ethics
  • For Hire: Visit the SERVICES page or directly hire at this link
    • Full/Part-time, Temp, Contractor, Consulting, Visting researcher/scholar
    • Resume available on request. Willing to relocate, globally.
Community service includes:
  • In (inter)national associations & groups
    • Topics: metadata, ontology, semantic technology
    • Activities & Output: Educational initiatives, Program committees, Governance review/dev., ethics, Terminology, Event organization, etc.
  • In (inter)national aerospace associations
    • Topics: space debris, space traffic management, situational awareness, policy, etc.
    • Activities & Output: Committee work. Drafted reports & articles. Co-authored publications. Co-led lexicon tasks/group. Contributing co-author to national standard documents
  • Experience in international standards development in two distinct disciplines
    • Topics: space systems, metadata/semantics/ontology
    • Activities & Output: contributor to standards dev., draft review & edits, voting, etc.
  • In water & boating safety
    • Activities & Output: research, recommendations as SME, helping develop national-level water safety plans, volunteer training in emergency first-response, on-call response availability, training development study guides
  • Research Affiliate of Center for Orbital Debris Education and Research (2014-2022)
  • A member of the NASA Datanauts (2017-2020) open data initiative (Class of 2017)

EDUCATION

  • M.A. & B.A. – Philosophy (ontology focus. interdisciplinary coursework).
  • Graduate coursework – Space Studies, M.S. (paused due to circumstances)
  • Cert. & Training – Commercial merchant mariner, Water rescue & boat response (resume aor).

History & Context

Orbitology and space has fascinated me at least since my teens. In 2011, after attending a spaceflight conference, I thought of applying my recent studies in ontology to help with the orbital debris problem (see article (1)). My idea was to facilitate data integration via ontology dev., ontologically representing the domain, while also exploring philosophical and technical aspects, and continuing my education. Since then I’ve wanted this to be my PhD project, affording further education and pursuit of my love of space toward a career in the sector. I’m still actively searching/applying to programs. My motivation has been educational and to help the community on a space sustainability and safety problem. This has resulted in extensive pure volunteering for distinct communities and orgs., as well as personal efforts via my articles and conference presentations, in the hopes of finding support and a starting point for a stable career path. Thusfar, no opportunity has been afforded or forthcoming, despite communications to potential partners/employers, some of whom have subsequently started similar projects or applications in their orgs. Documentation of my ideation and efforts/communications available on request. I’m not motivated by political agendas, or promoting a technology or method. I’m motivated by learning about the topics, modeling them, and simply the work. Personal goals, then, have included:

  • A stable funded environment to complete my knowledge models, e.g., PhD study opportunities, employer support, grants, etc.
  • I want my knowledge models to be used by others
  • I want to help build models for others. I want to work on similar projects.
  • Further education on topics of interest: space, maritime, philosophy, knowledge representation
  • I want to work in a team environment, learning from specialists in astrodynamics, space policy, maritime, systems engineering, AI, ontology engineering, semantic tech, philosophy, etc.
  • I want to learn specific or needed tech skills via a studentship or on-the-job-training in order to realize my project vision, or otherwise help your project.

How you can help

What is Ontology?

Hire me to teach your team central concepts in ontology:


SAMPLE: There are difference senses of ‘ontology’, relative to the practicing discipline. The concept originates in philosophy as the study of the generic nature of existence, and often aims to identify or formulate abstract concepts and categorizations that specify (sometimes with formal logics) the interrelationships as well as the features characterizing various things that actually or potentially exist. A given thing, topic or concept can be modeled in many ways.

Computational ontologies are computable conceptual, semantic or metadata artifacts providing a defined, structured and interconnected set of computable constructs (often called concepts, categories, or terms). They help make data and documents self-describing through semantic tags (the terms) and modeling. This provides an interpretation of the meaning of the data. They are capable of providing more detail and functionality (depending on tools and resources), than other knowledge organization systems like thesauri and taxonomies. They can be developed to varying degrees of abstraction and complexity, from the highly generic to very specific, from a simple set of terms to a fully specified axiomatic theory on a structured set of terms.

They may express or encode a conceptual model of some target subject matter, or of the internal content and concepts of an enterprise. A focus for ontologies is capturing and expressing meaning or semantic content. They minimally provide human- and computer-readable terminologies/taxonomies with a formally-specified semantics. They are encoded in formalisms that allows computers to automatically draw inferences, answering user-generated queries using the constructs or vocabulary of the ontology. Ontologies thereby provide metadata and a controlled vocabulary for the given data, application or use-case. With sufficient complexity, they can also present a knowledge model for software applications and artificial agents to draw from, reason over, and take action (e.g., in the case of knowledge-based AI applications, autonomous vehicles, etc.) in the world.

Ontology development & knowledge engineering has application in AI, informatics, data science, knowledge management, etc. The applicability to societal and personal data/information, combined with the modeling and encoding of meaning, entails an ethical and moral component to ontology design, development and use (another area of my research).

Practical goals of ontologies include: support for AI applications; data search, retrieval, fusion; information exchange, chatbots, semantic interoperability; use in autonomous vehicles; linking data and other content; etc.

Concepts, distinctions and methodologies from philosophical and formal ontology may or may not be used in contemporary computation ontology. Formal ontology is a branch of analytical metaphysics (philosophy) that uses logics to explicitly specify, systematize and represent an entire ontological theory or model, or (more modestly) a set of concepts with assigned labels.

Related Keywords: metadata, artificial intelligence (AI), knowledge model, semantic model, domain model, reference model, conceptual model, knowledge graph, property graph, semantic model, linked data, big data, open data, knowledge representation and reasoning (KRR), knowledge engineering, ontology engineering, conceptual modeling, semantic technologies, semantic web, RDF, OWL, Description Logic, symbolic logic, formal ontology, first-order logic, MBSE, model-based systems engineering, digital twin.

Copyright

©2022, Robert J. Rovetto. All rights reserved.

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