Blockchain Enterprise Ontologies: TOVE and DEMO

Enterprise ontology for blockchain transactions includes datalogical, infological and essential levels. OntoClean analyzes ontologies based on formal, domain-independent properties (metaproperties), being the first attempt to formalize the notion of ontological analysis for computer systems. The notions are extracted from the philosophical ontology. In the semantic web, a property is a binary relationship, with a subtle distinction between ownership and class. Thus, a metaproperty is a property of a property or a class. The design of ontology can be done when there is a basic understanding of the blockchain analysis.


Blockchain enterprise ontologies: TOVE and DEMO
Enterprise ontology for blockchain transactions includes datalogical, infological and essential levels. OntoClean (Guarino 1998) developed by Nicola Guarino and Chris Welty (Guarino and Welty 2000) analyzes ontologies based on formal, domain-independent properties (metaproperties), being the first attempt to formalize the notion of ontological analysis for computer systems. The notions are extracted from the philosophical ontology. In the semantic web, a property is a binary relationship, with a subtle distinction between ownership and class. Thus, a metaproperty is a property of a property or a class.
Identity for the ontologies of computer systems includes conceptual modeling of the database, especially those that expose the existence or at least the need to represent other entities.
In OntoClean, identity criteria are associated with, or carried by a class whose instances are identified in the same way, called sortal. Identification criteria and sortals are intuitively designed to respond to the linguistic way of associating identity with certain classes.
The design of ontology can be done when there is a basic understanding of the blockchain analysis. Blockchain comes in three forms: public, private or hybrid. (Buterin 2015) Blockchain ontology should also refer to the operations and business processes of potential adopters.
Enterprise ontology provides a collection of relevant terms and definitions of natural language.
Examples of frameworks for enterprise ontology are TOVE, EO and DEMO. (Kruijff and Weigand 2017) TOVE, the acronym of the TOronto Virtual Enterprise project, is a project for an ontological framework for enterprise integration based and tailored for enterprise modeling. (Totland 1997) The initial objectives of the project were: (Fox 1992) Creating a distributed representation or an ontology of the enterprise that every agent in the distributed enterprise can understand and use • Defining the meaning of all descriptions or semantics • Implementing semantics into a set of axioms that will allow TOVE to automatically answer to many "common sense" questions about the enterprise, and • Defining a symbol system to represent a concept in a graphical context.
The project develops a set of integrated ontologies for modeling enterprises. Ted Williams states that it is "multi-level, spanning conceptual, generic and applications layers. The generic and applications layers all also stratified and composed of micro theories spanning, for example, activities, time, resources, constraints, etc." (Williams 2000) Fox et al. presented TOVE enterprise models as a second-generation knowledge engineering approach. An approach to first generation knowledge engineering "is extracting rules from experts, while second generation is ontology engineering: They develop comprehensive ontologies for all the aspects of an organization they find necessary (necessity is decided based on competency requirements to the model, i.e., what are the questions the model will have to answer, either by ordinary look-up or by deduction). The background of TOVE is clearly knowledge engineering and to some degree Computer Integrated Manufacturing." (Fox 1992) A business modeling methodology for transactions and the analysis and representation of business processes that provide a coherent understanding of communication, information, action and organization was developed in the 1980s by Jan Dietz and is inspired by the perspective language/action introduced in the field of computer science and computer systems design by has proven to be a useful methodology to formalize systems that are ambiguous, inconsistent or incomplete, especially when it comes to reducing the complexity of modeling (Wang, Albani, and Barjis 2011) enterprise ontology. (Kruijff and Weigand 2017) The methodology provides a coherent understanding of communication, information, action and organization, and is based on the following principles: (J. Dietz 1996) • An organization consists of people with authority and responsibility to act and negotiate.
• Information systems and business processes design leads to uniformity.
• The models should be understandable for everyone interested. options from the conceptual model of the database (principle of data independence). A similar separation is very necessary for the blockchain domain. An axiom of distinction of enterprise ontology can be adopted as an ontological basis for this separation. (Kruijff and Weigand 2017)