This paper presents the Dynamic Information System Modeller and Executor (DISME), a low-code/no-code platform designed to help bridge the gap between enterprise modeling and their implementation into information systems. Grounded in the Design and Engineering Methodology for Organizations (DEMO), DISME allows domain experts to specify and execute organizational models through a visual, interface without writing any traditional code. The platform supports the modeling of processes, information structures, coordination acts, and business rules, which are immediately implemented into the runtime environment using its interpretation engine. DISME architecture includes a modular System Modeller and a live System Executor. In this paper we cover the key components such as action rule design, REST API integration, form building and designing and UI adaptivity that enable the real-time system configuration and interaction. Two real-world use cases are presented, highlighting some significant reductions in development time and system complexity, as well as improved usability outcomes.

Clear and cognitively compelling diagrams representing organizational reality are crucial for structured communication, proper information systems implementation, and ultimately, organizational success. Design and Engineering Methodology for Organizations (DEMO), a standard from the field of Enterprise Engineering, provides representations for Process and Fact Models. However, the complexity of its notations can impede stakeholder understanding. New representations for these models have been proposed, but lacked formal evaluation across diverse user groups. This paper addresses this gap by assessing user perception of both standard and newly proposed DEMO representations. We conducted a family of three evaluation studies using mixed research methods across distinct user groups (N = 32). Results show a unanimous preference for the new representations in terms of perceived quality and functional suitability, supporting most of our hypotheses. Our study does not support the claim that familiarity with the modeling language improves perception of empirical quality. This research expands the knowledge base on the underexplored area of user experience within DEMO models and representations.

The Design and Engineering Methodology for Organizations (DEMO) offers a comprehensive framework for modelling an organization's structure and operations in a coherent and platform-independent manner. However, criticisms have arisen regarding the complexity of DEMO models, hindering their accessibility to non-experts. Our research team has been working on refining the DEMO Modelling language for Enterprise Ontology. Drawing from previous studies, which identified challenges in using standard DEMO notations, this research introduces new representations tailored for improved communication and validation of models. Through a case study in the healthcare domain, involving domain professionals, the efficacy of these new representations is evaluated. The findings reveal significant disparities in perceived quality and functionality between traditional DEMO representations and the newly proposed ones, with a clear preference for the latter. Furthermore, the paper presents advancements in the development of a metamodel for DEMO's Action Model, leveraging an Extended Backus-Naur Form (EBNF) syntax. These developments were informed by the implementation of a system supporting the aforementioned case study on a nocode/low-code platform. In essence, this research strives to streamline DEMO Modelling, making it more accessible, comprehensible, and practical for a wider range of users and applications, while also advancing its technical foundations for enhanced implementation support. Moreover, this study underscores the importance of user-centric approaches in refining modelling languages, especially in complex domains such as healthcare. The contributions include concrete models and patterns derived from this implementation, offering reusable solutions for similar scenarios, facilitating their adoption by other low-code platforms following a similar approach.

In enterprise data management, the development of APIs for integrating diverse information systems often entails repetitive and labor-intensive tasks, such as translating variables and methods between systems. The advent of low-code platforms has significantly altered this landscape, facilitating the automatic and swift generation of APIs for both incoming and outgoing data and service actions. This paper explores a new approach using the Design and Engineering Methodology for Organizations (DEMO) data models within a low-code platform. Our methodology simplifies the API creation process by using DEMO’s Fact and Action models. Using a low-code platform, we enable users to efficiently generate endpoints for various functionalities, ranging from basic data item lists to complex query results, all achieved through intuitive drag-and-drop operations within a user-friendly graphical interface. This approach not only streamlines the development of APIs for internal tasks but also eases integration with external systems. Moreover, our approach includes the automated scanning of data from external APIs. Utilizing a user-friendly GUI, our system can automatically retrieve data from external sources and align it with internal data, ensuring consistent integration. This paper details this approach, emphasizing its effectiveness in integrating external information into local systems.

This paper’s main contributions are the comparative analysis of open source business intelli- gence platforms, having as background aim, the selection of the most appropriate one for its integration in an open source low-code platform we are developing. We researched the state-of- the art and selected nine platforms for a first and more general analysis. Out of these nine, four were then selected for a more thorough and detailed analysis and testing. The best two of this set were then selected for the implementation of concrete integration tests with our low-code platform. During the process, one of them revealed to have critical problems and the other was integrated successfully, with functional results achieving the best expectations. Thus, another main contribution of this paper is the identification of the current best candidate open source business intelligence platform for integration with a low-code platform.

This article presents a practical research project aimed at developing a method for automatically generating smart contracts from business models. The project has as a context the logistics in- dustry and uses Hyperledger Fabric as the blockchain (BC) platform. The main contributions are a mapping from DEMO (Design and Engineering Methodology for Organizations) language to Hyperledger Chaincode using GO language, as well as an evolution of DEMO’s Action Model Grammar, that enable specification of elements necessary for automatic SC generation. The proposed approach extends the DEMO methodology so that it includes an SC concern, enabling the generation of reusable action rule specifications and other elements necessary for SC genera- tion. Our research contributes to combining the strengths of the DEMO methodology and smart contracts. The design and implementation considerations of this approach are discussed in de- tail, and the results can be applied in future business cases requiring enterprise interoperability supported by distributed ledger technology.

Low-code platforms have gained attention in recent years as a visual and model-driven approach to application development. This approach uses drag-and-drop elements, model-driven logic, and graphical user interfaces to democratize development, making it possible for developers or business analysts of various skill levels to produce applications. In this experiment, we compare the traditional development approach with a low-code one using a platform that executes models in DEMO language, as an information and workflow system. We make this comparison with NexusBRaNT as its object, a system projected to manage information of a research project, which targets health professionals who perform cognitive rehabilitation. Our findings show that, in this particular case, the low-code approach could deliver a high-quality and functional application with an impressive reduction in needed time and implementation complexity. Namely, the standard approach took 888 hours of work, while using low-code, just 47.5 hours of work were needed, a 94.63% reduction in the needed effort. Regarding complexity, the traditional approach led to a total of 12310 lines of code implementing the system, while the low-code approach led to a total of 1723 database records, a reduction of 86%. This is highly relevant, especially for organizations that need to rapidly develop and deploy applications. The results of this experiment have important implications for the future of software development, particularly in the context of digital transformation and the increasing demand for agile and rapid application development.

: Demo’s (Design and Engineering Methodology for Organizations) Way of Modelling encompasses a collection of interconnected models and diagrams designed to depict an organization’s structure and operations in a cohesive and platform-independent manner. Nevertheless, there has been a contention that the syntax and semantics of DEMO models are overly intricate and cluttered, posing challenges for laypeople in terms of interpretation. Our research team has been working on improvements to the DEMO Modelling language for Enterprise Ontology. Previous work had shown challenges in using standard DEMO notations for model communication and validation, prompting the development of new representations. This study evaluates these representations through quality and functionality testing using a health domain case and health professionals with domain knowledge. The results of the conducted tests reveal significant differences in perceived quality and functionality between the new and traditional DEMO representations. These findings indicate a strong preference for the new representations over traditional ones. This study underscores the importance of focusing on users in enhancing the effectiveness of modelling languages like DEMO, particularly in complex domains such as healthcare. The results suggest that these new representations have the potential to improve the perceived quality and functionality of DEMO models in various practical applications, including health-related information systems.

We consider current Design and Engineering Methodology for Organizations (DEMO) Action Rules Specification to be unnecessarily complex and ambiguous. Even while using a "structured English" syntax similar to the one used in Semantics of Business Vocabulary and Business Rules (SBVR), such specifications are: incomplete while not containing enough ontological information to derive a functional implementation; and complex by containing mostly unneeded specifications. We propose a new meta-model for DEMO's Action Model in the form of an Extended Backus–Naur Form (EBNF) syntax which is being implemented in a prototype that directly executes DEMO models as an Information and Workflow System. This prototype includes an action engine that runs DEMO transactions and the enclosed actions specified in our approach. We are currently integrating Blockly in our solution to allow syntactically correct visual programming of our proposed new Action Rule language that includes constructs to evaluate logical conditions, update the state of internal or external information systems, obtain input and provide output (formatted with a 'What You See Is What You Get' (WYSIWYG) template editor) to users, among others.

An overview of the Dynamic Information System Modeller and Executor, an enterprise engineering, DEMO based, open source, low code platform with an Adaptive Object Model approach for workflow management in organizations. An alternative take, seeing an organization as a living organism, thus providing the tools for instant change in the processes to immediately reflect on their execution. We detail the multiple components of the System Modeller and how they interconnect with each other to produce the system executor that can be used by users for their day-to-day workflow in their organizations.

Context: Companies must make a paradigm shift in which both short- and long-term value aspects are employed to guide their decision-making. Such need is pressing in innovative industries, such as ICT, and is the core of Value-based Software Engineering (VBSE). Objective: This paper details three case studies where value estimation models using Bayesian Network (BN) were built and validated. These estimation models were based upon value-based decisions made by key stakeholders in the contexts of feature selection, test cases execution prioritization, and user interfaces design selection. Methods: All three case studies were carried out according to a Framework called VALUE - improVing decision-mAking reLating to software-intensive prodUcts and sErvices development. This framework includes a mixed-methods approach, comprising several steps to build and validate company-specific value estimation models. Such a building process uses as input data key stakeholders' decisions (gathered using the Value tool), plus additional input from key stakeholders. Results: Three value estimation BN models were built and validated, and the feedback received from the participating stakeholders was very positive. Conclusions: We detail the building and validation of three value estimation BN models, using a combination of data from past decision-making meetings and also input from key stakeholders.

The software industry's current decision-making relating to product/project management and development is largely done in a value neutral setting, in which cost is the primary driver for every decision taken. However, numerous studies have shown that the primary critical success factor that differentiates successful products/projects from failed ones lie in the value domain. Therefore, to remain competitive, innovative and to grow, companies must change from cost-based to value-based decisionmaking where the decisions taken are the best for that company's overall value creation. This paper details a case study where value-based decisions made by key stakeholders to select features for the next sprint of an Internet of Things (IoT) project, stored in a decisions database, were used to build and validate a value estimation model. This model's goal was to estimate the overall value contribution that each feature being discussed during a decision-making meeting would bring to the company, if selected for implementation. The estimation technique employed was Bayesian Network, and validation results were quite positive.

To sustain growth, maintain competitive advantage and to innovate, companies must make a paradigm shift in which both short- and long-term value aspects are employed to guide their decision-making. Such need is clearly pressing in innovative industries, such as ICT, and is also the core of Value-based Software Engineering (VBSE). The goal of this paper is to detail a framework called VALUE--improving decision-making relating to software-intensive products and services development--and to show its application in practice to a large ICT company in Finland. The VALUE framework includes a mixed-methods approach, as follows: to elicit key stakeholders' tacit knowledge regarding factors used during a decision-making process, either transcripts from interviews with key stakeholders are analysed and validated in focus group meetings or focus-group meeting(s) are directly applied. These value factors are later used as input to a Web-based tool (Value tool) employed to support decision making. This tool was co-created with four industrial partners in this research via a design science approach that includes several case studies and focus-group meetings. Later, data on key stakeholders' decisions gathered using the Value tool, plus additional input from key stakeholders, are used, in combination with the Expert-based Knowledge Engineering of Bayesian Network (EKEBN) process, coupled with the weighed sum algorithm (WSA) method, to build and validate a company-specific value estimation model. The application of our proposed framework to a real case, as part of an ongoing collaboration with a large software company (company A), is presented herein. Further, we also provide a detailed example, partially using real data on decisions, of a value estimation Bayesian network (BN) model for company A. This paper presents some empirical results from applying the VALUE Framework to a large ICT company; those relate to eliciting key stakeholders' tacit knowledge, which is later used as input to a pilot study where these stakeholders employ the Value tool to select features for one of their company's chief products. The data on decisions obtained from this pilot study is later applied to a detailed example on building a value estimation BN model for company A. We detail a framework--VALUE framework--to be used to help companies improve their value-based decisions and to go a step further and also estimate the overall value of each decision.

[Context]: To remain competitive, innovative and to grow, companies should use a value-based decision-making where decisions are the best for that company's overall value creation. However, without tool support, the use of explicit value propositions and aggregation of different key stakeholders' decisions during decision-making may be a challenge for many companies. [Goal]: The goal of this paper is to investigate the extent to which a Web-based tool for value-based decision-making can successfully support stakeholders' decision-making process. [Method]: We conducted three case studies across four software projects, during six weeks, in the contexts of feature selection, test cases execution prioritization and user interfaces design selection. Prior to using the tool, stakeholders' value propositions were elicited via focus-group meetings; later, during a post-mortem phase, data was gathered via observation, semi-structured interviews and structured questionnaires. [Results]: Participants reported an improvement of their decision-making process and quality of decisions; further, they also felt confident about using the tool, and that it can be useful to their work. [Conclusions]: Results suggested that the use of tool support by the stakeholders in the investigated company for value-based decision-making improved their decision-making process and the quality of decisions.

Numerous companies worldwide make their decisions related to software projects/products in a value neutral way, using only earned value systems, which represent short-term goals. Better decisions can be made using a value-based approach, achieving cost-effective results and reliable construction and maintenance of products. However, moving from a value-neutral to a value-based paradigm can be a challenge. We provide tool-support, which was co-created in collaboration with three software companies, to ease the paradigm shift. Our tool supports both individual and group-based decisions using several visualization mechanisms. Despite the co-creation process employed while developing the VALUE tool, there are specific issues relating to its usability that must also be assessed in order to reduce any possible drawbacks for its adoption by industry. This paper details three usability studies that were carried out to assess the VALUE tool's usability. The results also suggest that the tool is ready to be taken into use in the industry.