Enterprise Modeling is far from its maximum potential. An important reason is that opposing stakeholder concerns lead to the existence of context-dependent models that are not mutually related, resulting in an inconsistent enterprise model landscape. This causes problems regarding unsustainable model utilization, since models are not used across different focal areas and over a longer period of time. The aim of our research project is to increase the value of Enterprise Modeling by creating a design method to support users in designing practically applicable models and a model integration method to integrate locally created models into an overarching enterprise model landscape that maintains model consistency.
In this presentation, we introduce the software platform, Dbquity [9], and some learning points about REA models. Dbquity lets you declaratively model data structure and express derived information at the domain expert’s level of abstraction without over-specifying or repeating knowledge using a dedicated declarative1 language, which centers on the notions of entity and association and single inheritance with powerful member-specialization capabilities, and lets you work on multiple levels of abstraction factoring out domain-specific, reusable libraries. The language abstracts away all implementation details, and the model declared is executed directly by the Dbquity runtime without any need for further artefacts. Design goals for Dbquity include, that based on a single inheritance combined with expressive, intuitive constraints, the language must support both basic and more advanced REA patterns such as policy and valuation whilst aiming to be if not writable, then at least readable for non-programmers using a no/low-code approach. Further, the system must be able to generate the required set of reports from the model itself in as simple a way as possible. We aim to open source the specification of the language itself and keep the core tooling and runtime implementations closed source. The first2 incarnation of the runtime targets a simple, ubiquitous twotier topology using cloud-based storage and mobile phones aiming to make it as effortless as possible for modelers to distribute Dbquity models and for consumers to use the models. Our work includes several examples to make it clear how to implement REA patterns using Dbquity, and we hope to get feedback on the presented models, the language, the tooling, and the current scope.
Information entities include technical specifications, data records, and software code, but also e.g., musical scores and novels. The ontological status of information entities has been addressed in several fields, including philosophy and linguistics. In our earlier work, we have developed a general artifact ontology and proposed a textual artifact ontology as a special case. In this paper, the textual artifact ontology is compared with some other (recent) applied ontology approaches, specifically IAO and the ontology of representation proposed by Mizoguchi and Borgo. The goal is to explore the added value of the artifact ontology in the information entity debate and to identify any limitations.
The low-code & no-code platforms contain configuration languages close to the concepts that citizen developers intuitively understand, for example, flowcharts in the case of Wem.io, and pipelines in the case of Quickbase. For several years, the authors of this paper experimented with an application language based on the REA (resources, events agents) ontology [1, 2, 3, 7], which contains concepts intuitively understood by economists. In all these cases the application ontology is static, and can only be changed by a new release of the platform. At VMBO 2022 workshop at CAiSE’22 we will demonstrate a novel approach, where a citizen developer can adapt the platform’s programming model by selecting different ontologies that cover the problem domain. The platform is available at https://nocodeplatform.azurewebsites.net/ .
The FAIRification of data facilitates a fast-paced, global, FAIR metadata availability across domains for the sustainable growth of public/private organizations. Likewise, in healthcare, the clinical labs aim to achieve FAIR (biosample) metadata by keeping patient-specific infectious disease records. However, the responsible evaluation of the FAIRification process of Dutch clinical lab metadata is lacking at the local and global levels. From a responsible data science perspective, we normatively (in-principle) and empirically (in-practice) evaluate the Dutch clinical lab metadata share against FACT principles. The normative evaluation involved content analysis of FAIR concerning peer-reviewed publications and official websites. The empirical evaluation comprised a documentation review of standardized (public/confidential) documents regarding the metadata share of Dutch clinical labs. The evaluations assisted us in formulating two REA models based on REA ontology. The first REA model depicts the clinical lab metadata production run at a local/national level. The second REA model specifies the work (flow) breakdown structure of global FAIRification for FHIR Netherland using linkage relationship against FACT principles. In-field (IT and REA ontology) experts further evaluated the REA models for functional and structural veracity. Furthermore, our evaluations verified the presence of an underlying privacy-utility tradeoff in FAIRification of clinical lab metadata where data utility is prioritized over data protection.
IT systems design and architecture have many similarities with the design of organisations and institutions. Both pay attention to social concepts such as rules, norms, and values. Justice is one of the key concepts that can be relevant for any institutional design from a systems perspective. This paper outlines an ontology of justice based on the Unified Foundational Ontology (UFO). We envisage that it can support designers in recognising and addressing the issues of justice during systems design and analysis, including elicitation of requirements, rules analysis, systems evaluation, and policy analysis.
Orbst’s paper on ontological interoperability presents a continuum from descriptions with very week semantics to those with strong semantics. Those ontologies represented in terms of axioms in first order logic have the strongest semantics and therefore the highest level of interoperability. These representations also allow for inferences about the system described by the axioms. The mathematicians of the early 20th century were focused on the possibility of determining which inferences were possible from the axioms. The problem for otologists working in describing services and business models is reversed. We know what inferences must be possible within the model, and it is therefore incumbent on the developers of a particular ontology to show whether these inferences are possible. For example, it is critical for a set of axioms that purport to describe the REA ontology to make inferences about not only accounting artifacts, but also other auditing conclusions. This paper attempts to describe the types of inferences that are required of any ontology.
This paper presents an ontological analysis of the concepts proposed for extensions to the REA ontology to accommodate or define Debt and Equity. Earlier work aimed to use the REA concept of ‘Claim’ to provide the language in which to create a symmetrical treatment for Debt and Equity, however no such symmetry was apparent. The exploration given here uses the Design Science Research (DSR) methodology to take a step back and consider the range of possible concepts to which the word ‘claim’ may be mapped, comparing these to the canonical REA concept for Claim. We analyzed three such concepts, rejected one, found another to be coextensive to Debt and were left with a third, useful concept that does not precisely map to REA Claim. We established that the concepts needed for Debt and for Equity can be defined using existing REA concepts, by abstracting Commitment to a broader usage in agreements generally. Finally, we identify work that remains to be done to unify the models developed in this exploration, with canonical REA concepts.
One issue that continues to plague researchers in the development of a comprehensive business ontology, concerns the specification of normative business event (sometimes referred to as tasks) models for business processes. The PCAOB’s Auditing Statement 5 indicate two types of review for business event models. First, are the models designed appropriately, and second are they operating as designed. These two types of reviews are the basis for evaluating an organization’s system of internal controls. Thus, a quality internal control system will result not only in an adequate design of the business event models, but will also ensure the proper execution of the business events. The evaluation of internal controls is a separate process then their design and operation, and requires that sufficient information is available to evaluate their design and functioning of the internal control models. Despite this relatively straightforward conceptual foundation for a system of internal controls, to date there are still only descriptions of sufficient results as opposed to necessary conditions for a quality internal control system. These sufficient results are not strictly of internal controls, but instead concern the impact of internal controls on the quality of financial statements created from the corporate information system. This results in the evaluation of internal controls as a subjective review which may not be consistent from one reviewer to the next. The purpose of this paper is to integrate representations of internal controls into the REA Ontology. This includes a set of internal control axioms which are then mapped to integers using Gӧdel numbering.
. The REA accounting model of McCarthy is often taken as a reference for accounting ontologies. The focus of these ontologies is on economic exchanges. This paper argues that accounting is more: it is about accounts and reports of economic exchanges. This suggests that accounting ontologies should broaden their scope to include Accounting Information System and Financial Report artefacts. Such an accounting ontology can not only accommodate the con-ditional-normative rules that play an important role in Accounting, but also allows to formulate questions on the ontological status of concepts like Asset and Equity.
. This paper sets out to explore the potential in re-framing the concepts in the REA Ontology to cover a broader range of agreements. These are further extended by introducing the notion of a ‘conditional’ commitment, as a precursor to entering into any formal agreement. These, alongside a more detailed break-down of delivery concepts into possession, rights and availability, constitute a potential general ontology for a wide range of economic activities. Some possible future directions for this work include smart contracts for supply chains and novel arrangements for trade finance.
