Resources-Events-Agents Design Theory: A Revolutionary Approach to Enterprise System Design

Enterprise systems typically include constructs such as ledgers and journals with debit and credit entries as central pillars of the systems’ architecture due in part to accountants and auditors who demand those constructs. At best, structuring systems with such constructs as base objects results in the storing the same data at multiple levels of aggregation, which creates inefficiencies in the database. At worst, basing systems on such constructs destroys details that are unnecessary for accounting but that may facilitate decision making by other enterprise functional areas. McCarthy (1982) proposed the resources-events-agents (REA) framework as an alternative structure for a shared data environment more than thirty years ago, and scholars have further developed it such that it is now a robust design theory. Despite this legacy, the broad IS community has not widely researched REA. In this paper, we discuss REA’s genesis and primary constructs, provide a history of REA research, discuss REA’s impact on practice, and speculate as to what the future may hold for REA-based enterprise systems. We invite IS researchers to consider integrating REA constructs with other theories and various emerging technologies to help advance the future of information systems and business research

Mathematical Definitions of Scene and Scenario for Analysis of Automated Driving Systems in Mixed-Traffic Simulations

This paper introduces a unified mathematical definition for describing commonly used terms encountered in systematical analysis of automated driving systems in mixed-traffic simulations. The most significant contribution of this work is in translating the terms that are clarified previously in literature into a mathematical set and function based format. Our work can be seen as an incremental step towards further formalisation of Domain-Specific-Language (DSL) for scenario representation. We also extended the previous work in the literature to allow more complex scenarios by expanding the model-incompliant information using set-theory to represent the perception capacity of the road-user agents. With this dynamic perception definition, we also support interactive scenarios and are not limited to reactive and pre-defined agent behavior. Our main focus is to give a framework to represent realistic road-user behavior to be used in simulation or computational tool to examine interaction patterns in mixed-traffic conditions. We believe that, by formalising the verbose definitions and extending the previous work in DSL, we can support automatic scenario generation and dynamic/evolving agent behavior models for simulating mixed traffic situations and scenarios. In addition, we can obtain scenarios that are realistic but also can represent rare-conditions that are difficult to extract from field-tests and real driving data repositories

Improving IT infrastructures representation: A UML profile

IT infrastructures are most times informally modeled. The resulting models are ambiguous to stakeholders, cannot be checked for validity, and therefore are unable to play their important role in design, deployment and maintenance activities. The main reason for such a poor state-of-the-art lies mainly in the absence of a modeling language capable of representing IT infrastructures at the required level of abstraction. Indeed, existing candidate languages are too abstract, as shown in this paper by reviewing their metamodels. The present paper mitigates this problem by proposing a UML profile to describe the semantics of an IT infrastructure.info:eu-repo/semantics/publishedVersio

Improving IT infrastructures representation: A UML profile

IT infrastructures are most times informally modeled. The resulting models are ambiguous to stakeholders, cannot be checked for validity, and therefore are unable to play their important role in design, deployment and maintenance activities. The main reason for such a poor state-of-the-art lies mainly in the absence of a modeling language capable of representing IT infrastructures at the required level of abstraction. Indeed, existing candidate languages are too abstract, as shown in this paper by reviewing their metamodels. The present paper mitigates this problem by proposing a UML profile to describe the semantics of an IT infrastructure.info:eu-repo/semantics/publishedVersio

Modeling Business Models: A cross-disciplinary Analysis of Business Model Modeling Languages and Directions for Future Research

Modeling languages for business models are a powerful and flexible means of representing and communicating knowledge related to business models. More than fifteen years after Osterwalder et al. (2005) clarified the ontology for the business model concept in this journal, we offer a systematic and cross-disciplinary assessment of the literature on business model modeling languages (BMMLs) that facilitate the visualization of this concept. In so doing, we synthesize and organize the knowledge dispersed across different disciplines in which BMMLs have originated and highlight the potential weaknesses in this literature to offer solid insights for future research. Our analysis reveals the existence of 17 BMMLs that have originated in traditional domains such as strategy and information systems, but also emerging domains such as sustainability. We contrast and compare these BMMLs along three dimensions: semantics, syntax, and pragmatics. We also analyze research that has made use of these BMMLs, differentiating between research that is conducted with a given BMML and research that is conducted about a given BMML. We conclude by offering a research agenda in which we illustrate the main challenges associated with the lack of well-accepted semantic, syntactic, and pragmatic foundations of BMMLs and outline opportunities for future research

ACTAS: Adaptive Composition and Trading with Agents for Services

Mainly in business domains, the vision of gaining flexible, adaptive service environments is based on the standardization and practical proliferation of (Semantic) Web Services, ontologies, and agents. The standards of Web Services and their Service-oriented Architectures (SOA) became the standard paradigm for software component integration. Dynamic changes and the permanently increasing amount of available e-services of different domains are a challenge of Service Discovery and Composition. Mediation between different approaches and expert knowledge is often necessary for the composition of services of different domains. Semantic enhancements, Autonomic Service Discovery, and the research for more holistic concepts for the classification of e-services are current attempts of overcoming this challenge, in order to reach the ultimate goal of Autonomic SOC

A proposal for a global task planning architecture using the RoboEarth cloud based framework

As robotic systems become more and more capable of assisting in human domains, methods are sought to compose robot executable plans from abstract human instructions. To cope with the semantically rich and highly expressive nature of human instructions, Hierarchical Task Network planning is often being employed along with domain knowledge to solve planning problems in a pragmatic way. Commonly, the domain knowledge is specific to the planning problem at hand, impeding re-use. Therefore this paper conceptualizes a global planning architecture, based on the worldwide accessible RoboEarth cloud framework. This architecture allows environmental state inference and plan monitoring on a global level. To enable plan re-use for future requests, the RoboEarth action language has been adapted to allow semantic matching of robot capabilities with previously composed plans

Application of Model-driven engineering to multi-agent systems: a language to model behaviors of reactive agents

Many users of multi-agent systems (MAS) are very commonly disinclined to model and simulate using current MAS platforms. More specifically, modeling the dynamics of a system (in particular the agents' behaviors) is very often a challenge to MAS users. This issue is more often observed in the domain of socio-ecological systems (SES), because SES domain experts are rarely programmers. Indeed, the majority of MAS platforms were not conceived taking into consideration domain-experts who are non-programmers. Most current MAS tools are not dedicated to SES, or nor do they possess an easily understandable formalism to represent the behaviors of agents. Moreover, because it is platform-dependent, a model realized in a given MAS platform cannot be properly used on another platform due to incompatibility between MAS platforms. To overcome these limitations, we propose a domain-specific language (DSL) to describe the behaviors of reactive agents, regardless of the MAS platform used for simulation. To achieve this result, we used model-driven engineering (MDE), an approach that provides tools to develop DSLs from a meta-model (abstract syntax), textual editors with syntax highlighting (for the concrete syntax) and code generation capabilities (for source-code generation of a model). As a result, we implemented a language and a textual editor that allow SES domain experts to describe behaviors in three different ways that are close to their natural expression: as equations when they are familiar with these, as a sequence of activities close to natural language or as an activity diagram to represent decisions and a sequence of behaviors using a graphic formalism. To demonstrate interoperability, we also developed code generators targeting two different MAS platforms (Cormas and Netlogo). We tested the code generators by implementing two SES models with the developed DSL. The generated code was targeted to both MAS platforms (Cormas and Netlogo), and successfully simulated in one of them. We conclude that the MDE approach provides adequate tools to develop DSL and code generators to facilitate MAS modeling and simulation by non-programmers. Concerning the DSL developed, although the behavioral aspect of MAS simulation is part of the complexity of modeling in MAS, there are still other essential aspects of model and simulation of MAS that are yet to be explored, such as model initialization and points of view on the model simulated worl