Blockchain Ontologies: OCL and REA

Unified Modeling Language (UML) of Object Management Group, along with Object Constraint Language (OCL), are considered as the best fit for blockchain ontology. OCL is a declarative language that describes the rules applicable to UML models and is part of the UML standard. Initially, OCL was just an extension of the formal specification language for UML. Now, OCL can be used with any meta-model. Enterprise ontology is combined with the business ontology of Resources, Events, Agents (REA) to be used for the content of the change. REA was originally proposed in 1982 by William E. McCarthy as generalized accounting model. DOI: 10.13140/RG.2.2.14744.1408

The Role of Ontologies for Designing Accounting Information Systems

The accounting ontologies were conceptualized as a framework for building accounting information systems in a shared data environment, within enterprises or between different enterprises. The model’s base feature was an object pattern consisting of two mirror-image that represented conceptual the input and output components of a business process. The REA acronym derives from that pattern’s structure, which consisted of economic resources, economic events, and economic agents. The REA model was proposed as a means for an organization to capture the signification of economic exchanges between two business partners. The REA ontology provides an alternative for modelling an enterprise’s economic resources, economic events, economic agents, and their relationships. Resources are considerate organization assets that are able to generate revenue for implicated parties. Events provide a source of detailed data in this approach. Agents participate in events and can affect some resources. They can be an individual or organization inside or outside the organization that is capable of controlling economic resources and interacting with other agents. The objective of this work is to offer an understandable of this framework and to explain how this model can help us via the identification of the afferent concepts.REA ontology, accounting information systems, business process, economic exchange

Foreign objects? Web content management systems, journalistic cultures and the ontology of software

Research on ‘digital’ journalism has focused largely on online news, with comparatively less interest in the longer-term implications of software and computational technologies. Drawing upon a six-year study of the Toronto Star, this paper provides an account of TOPS, an in-house web content management system (CMS) which served as the backbone of thestar.com for six years. For some, TOPS was a successful software innovation, while for others, a strategic digital ‘property’. But for most journalists, it was slow, deficient in functionality, aesthetically unappealing and cumbersome. Although several organizational factors can explain TOPS’ obstinacy, I argue for particular attention to the complex ontology of software. Based on an outline of this ontology, I suggest software be taken seriously as an object of journalism, which implies: acknowledging its partial autonomy from human use or authorization; accounting for its ability to mutate indefinitely; and analyzing its capacity to encourage forms of ‘computational thinking

Ontology-based e-assessment for accounting: Outcomes of a pilot study and future prospects

This article reports on a pilot of a novel ontology-based e-assessment system in accounting that draws on the potential of emerging semantic technologies to produce an online assessment environment capable of marking students' free-text answers to questions of a conceptual nature. It does this by matching their response with a "concept map" or "ontology" of domain knowledge expressed by subject specialists. The system used, OeLe, allows not only for marking, but also for feedback to individual students and teachers about student strengths and weaknesses, as well as to whole cohorts, thus providing both a formative and a summative assessment function. This article reports on the results of a "proof of concept" trial of OeLe, in which the system was implemented and evaluated outside its original development environment (an online course in education being used instead in an undergraduate course in financial accounting. It describes the potential affordances and demands of implementing ontology-based assessment in accounting, together with suggestions of what needs to be done if such approaches are to be more widely implemented. © 2013 Elsevier Ltd

Logical Semantics and Commonsense Knowledge: Where Did we Go Wrong, and How to Go Forward, Again

We argue that logical semantics might have faltered due to its failure in distinguishing between two fundamentally very different types of concepts: ontological concepts, that should be types in a strongly-typed ontology, and logical concepts, that are predicates corresponding to properties of and relations between objects of various ontological types. We will then show that accounting for these differences amounts to the integration of lexical and compositional semantics in one coherent framework, and to an embedding in our logical semantics of a strongly-typed ontology that reflects our commonsense view of the world and the way we talk about it in ordinary language. We will show that in such a framework a number of challenges in natural language semantics can be adequately and systematically treated

Gene ontology analysis for RNA-seq: accounting for selection bias

GOseq is a method for GO analysis of RNA-seq data that takes into account the length bias inherent in RNA-se

A Simulation Model Articulation of the REA Ontology

This paper demonstrates how the REA enterprise ontology can be used to construct simulation models for business processes, value chains and collaboration spaces in supply chains. These models support various high-level and operational management simulation applications, e.g. the analysis of enterprise sustainability and day-to-day planning. First, the basic constructs of the REA ontology and the ExSpect modelling language for simulation are introduced. Second, collaboration space, value chain and business process models and their conceptual dependencies are shown, using the ExSpect language. Third, an exhibit demonstrates the use of value chain models in predicting the financial performance of an enterprise

The transaction pattern through automating TrAM

Transaction Agent Modelling (TrAM) has demonstrated how the early requirements of complex enterprise systems can be captured and described in a lucid yet rigorous way. Using Geerts and McCarthy’s REA (Resource-Events-Agents) model as its basis, the TrAM process manages to capture the ‘qualitative’ dimensions of business transactions and business processes. A key part of the process is automated model-checking, which CG has revealed to be beneficial in this regard. It enables models to retain the high-level business concepts yet providing a formal structure at that high-level that is lacking in Use Cases. Using a conceptual catalogue informed by transactions, we illustrate the automation of a transaction pattern from which further specialisations impart a tested specification for system implementation, which we envisage as a multi-agent system in order to reflect the dynamic world of business activity. It would furthermore be able to interoperate across business domains as they would share the generalised TM as a pattern.</p