Abstract
The article is addressed to a wide range of specialists involved in data science including ontological data modeling and knowledge extracting in the various fields related to sustainable development (SD). A hierarchically structured ontological metamodel of SD is developed consisting of a conceptual layer of interconnected common, domain and application ontologies, and a physical layer of instance databases and documents. The SD common ontology is the top level of the conceptual layer and is associated with the next level of the SD domain ontologies in the economy, society, and nature. The third level is of the SD application ontologies and is illustrated by an example application ontology of firm sustainability. All ontologies of the SD metamodel have links to the relevant external ontologies and to specific instance databases. The proposed metamodel is a useful tool for SD knowledge structuring and classification, as well as a base for building machine learning models as a part of artificial intelligence.
TopBackground
A review of the achievements in ontological SD modeling discovers several ontologies that can be considered as parts of a common SD ontology:
Key Terms in this Chapter
Semantic Reasoner (or Simply Reasoner): A software application verifying semantic structure and mutual consistency of the ontological units as well as deriving new facts from ontologies.
Coevolutionary Approach: A research approach for investigation and analyzing the reciprocal evolutionary change in group of species in the nature or the mutual causal influences between the natural (environmental) and human (social and economic) dimensions.
Web Ontology Language (OWL): A standard formal language recommended by World Wide Web Consortium (W3C) for formal ontology description.
Ontology Instance (Individual): An ontology element denoting an example of a concept (i.e., United Nations is an instance of concept organization).
Ontological Metamodel: A set of ontologies on a common topic organized in a hierarchical system or in a network.
Thesaurus: In informatics, a controlled vocabulary supplemented with hierarchical and nonhierarchical (associative) relationships between terms.
Taxonomy: A scheme (a tree structure) of a categorization and hierarchical classification of things or concepts in given area.
Text Corpus: A set of texts of specific topic used for research and analysis of the content in order to extract main components (parts of speech, concepts, relations, etc.).
Controlled vocabulary: A dictionary containing approved (preferred) terminology along with the definitions.
Text Analytics (With Synonyms Text Analysis, Text Mining, Text Annotation): Automated Natural Language Processing (NLP) technology in AI for unstructured text data treatment to extract topics, entities and keywords.