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The production of pharmaceutical cannabis is a complex and dynamic industry that has to meet critical challenges concerning product quality, compliance, traceability, food safety, sustainability and health. Digital twins have the potential to be powerful enablers for producers to meet these challenges. However, digital twins for the pharmaceutical production of cannabis are still under exploration and not yet researched. This paper contributes to overcoming this situation by proposing a reference architecture for the development and implementation of digital twins in this domain. Based on a design-oriented methodology, it defines and applies a coherent set of architecture views for modelling digital twin-based systems. Furthermore, a proof of concept of an immersive digital twin has been developed in order to test the applicability of reference architecture. This digital twin is developed in the open, cross-industry platform Unity and includes an extensive 3D model of a cannabis production facility. It is connected with real-world data through an application programming interface integration displaying real-time sensor data from a live greenhouse. The 3D environment is fully explorable, where the user takes control of an avatar character to walk around the facility and view real-time sensor readings. The expert validation shows that the developed digital twin is a valuable and innovative first step for remote management of pharmaceutical cannabis production. Further developments are needed to leverage its full potential, especially adding more types of sensor data, developing implementation-specific 3D models, extending the digital twin with predictive and prescriptive capabilities and connecting it to actuators. [ABSTRACT FROM AUTHOR]

Companies operating with an engineer-to-order (ETO) strategy are often challenged with generating the desired profit as a consequence of product volumes and high levels of product customisation. Profit margins are seen to vary greatly from project to project, which may partly be explained by a lack of references to guide design decisions. Specifically, new product offerings are often based on reuse of design knowledge, which is often not efficiently utilised, as the knowledge transfer and reuse across projects are unstructured, incomplete, or not providing a suitable reference for design specification. To address this issue, this paper presents a method for identifying reference architectures under the consideration of profitability. The method was developed by combining and extending known methods within the fields of product architecture and complexity cost estimation to cover part of the ETO domain. The method was tested in two companies, one producing industrial spray drying plants and the other providing solutions for the production of confectionary products. The findings suggest that a limited understanding of 'preferred solutions' existed in the two case companies, and applying the suggested method to identifying reference architectures could potentially support a more profitable project execution. [ABSTRACT FROM AUTHOR]

Industry 4.0 is a new paradigm that is transforming the industrial scenario. It has generated a large amount of scientific studies, commercial equipment and, above all, high expectations. Nevertheless, there is no single definition or general agreement on its implications, specifically in the field of automation and supervision systems. In this paper, a review of the Industry 4.0 concept, with equivalent terms, enabling technologies and reference architectures for its implementation, is presented. It will be shown that this paradigm results from the confluence and integration of both existing and disruptive technologies. Furthermore, the most relevant trends in industrial automation and supervision systems are covered, highlighting the convergence of traditional equipment and those characterized by the Internet of Things (IoT). This paper is intended to serve as a reference document as well as a guide for the design and deployment of automation and supervision systems framed in Industry 4.0. [ABSTRACT FROM AUTHOR]

Hospital information system, as an integrated system consists of complex, diverse, and heterogeneous information systems, which supports all clinical, administrative, and financial activities of patients; therefore, it faces interoperability problems, which is a critical feature of data sharing and integration. In this regard, a reference architecture will be presented for the integration of different systems in the hospital which comprises system, information and software architecture. This architecture emphasizes interoperability with eight layers of user interface and application, services, data collection and storage, integration, external application systems, communication and information infrastructure, management, and security/privacy, based on service orientation. It will be evaluated by ATAM method, based on ten scenarios. It shows the presented architecture will satisfy all functional and non-functional requirements such as interoperability between different information systems, reduction of information redundancy and development cost and time, scalability and accessibility. [ABSTRACT FROM AUTHOR]

Microservice architecture (MSA) is an architectural style that is designed to support the modular development of software systems within a particular domain. It is characterized by the use of small, independently deployable services, which can be developed and deployed autonomously. The benefits of MSA include improved scalability, fault‐tolerance, and ease of deployment and maintenance. However, developing MSA for a specific domain can be challenging and requires a thorough consideration of various concerns such as service boundaries, communication protocols, and security. To support the easy development and guidance of an MSA for practitioners, we present a reference architecture design for MSA. The reference architecture has been designed after a comprehensive domain analysis of MSA in the literature and the MSAs of key vendors. This analysis has been used to identify best practices and common patterns that can be applied to the development of MSA. Additionally, relevant architecture viewpoints have been selected to model the corresponding architecture views, providing a clear and comprehensive understanding of the architecture. To validate the proposed reference architecture, a multi‐case study research approach has been used. In this approach, two industrial case studies have been used to demonstrate the practical applicability of the proposed reference architecture. The results of these case studies have shown that the reference architecture can be used to effectively guide the development of MSA in real‐world scenarios. [ABSTRACT FROM AUTHOR]

The field of cloud computing has witnessed tremendous progress, with commercial cloud providers offering powerful distributed infrastructures to small and medium enterprises (SMEs) through their revolutionary pay-as-you-go model. Simultaneously, the rise of containers has empowered virtualisation, providing orchestration technologies for the deployment and management of large-scale distributed systems across different geolocations and providers. Big data is another research area which has developed at an extraordinary pace as industries endeavour to discover innovative and effective ways of processing large volumes of structured, semi-structured, and unstructured data. This research aims to integrate the latest advances within the fields of cloud computing, virtualisation, and big data for a systematic approach to stream processing. The novel contributions of this research are: (1) MC-BDP, a reference architecture for big data stream processing in a containerised, multi-cloud environment; (2) a case study conducted with the Estates and Sustainability departments at Leeds Beckett University to evaluate an MC-BDP prototype within the context of energy efficiency for smart buildings. The study found that MC-BDP is scalable and fault-tolerant across cloud environments, key attributes for SMEs managing resources under budgetary constraints. Additionally, our experiments on technology agnosticism and container co-location provide new insights into resource utilisation, cost implications, and optimal deployment strategies in cloud-based big data streaming, offering valuable guidelines for practitioners in the field. [ABSTRACT FROM AUTHOR]

Currently, software systems must be appropriately developed to support an amount of variability for accommodating different requirements. To support such development, a diversity of tools has already been designed for variability management (i.e., identification, modeling, evaluation, and realization). However, due to this diversity, there is a lack of consensus on what in fact software variability tools are and even what functionalities they should provide. Besides that, the building of new tools is still an effort- and time-consuming task. To support their building, we present VMTools-RA, a reference architecture that encompasses knowledge and practice for developing and evolving variability tools. Designed in a systematic way, VMTools-RA was evaluated throughout: a controlled experiment with software developer practitioners; and an instantiation of the VMTools-RA architecture to implement a software variability tool, named SMartyModeling. As a result, VMTools-RA is evidenced to be feasible and it can be considered an important contribution to the software variability and developers of variability-intensive software systems community, which require specific tools developed in a faster manner with less risk, what a reference architecture could provide.

For several years, the use of the BIM method has been mandatory for public new construction and replacement projects of the transport infrastructure in the Federal Republic of Germany. As a result, about 20 use cases (UC) for the application of digital models have been defined. Most of them focus on the planning and execution phase. Despite the importance and long duration of the operational phase, there are isolated definitions for use case for operational phase and therefore underrepresented in the overall context. Moreover, none of the published use cases so far consider the specifics of bridge structures. For this reason, a further definition of specific BIM use cases for the operation of bridge structures is needed. In this article, BIM use cases for the use of digital models of bridge structures in the operation and maintenance phase are defined based on a qualitative empirical study. First, the current state of the art is elaborated by means of a literature analysis. Based on this, a expert interviews are conducted and systematically evaluated. The BIM use cases for operation are derived from the results. In addition, requirements and artifacts are defined. This results in a further specification of the use of BIM models in the operational phase of bridge structures and promotes the digitalization of maintenance management. [ABSTRACT FROM AUTHOR]

Manufacturing as a Service (MaaS) enables a paradigm shift in the current manufacturing landscape, from integrated production and inflexible, fragile supply chains to open production and flexible, robust supply chains. As part of this evolution, new scaling effects for production capacities and customer segments are possible. This article describes how to accomplish this paradigm shift for the automotive industry by building a digital MaaS ecosystem for the large-scale automotive innovation project Catena-X, which aims at a standardized global data exchange based on European values. A digital MaaS ecosystem can not only achieve scaling effects, but also realize new business models and overcome current and future challenges in the areas of legislation, sustainability, and standardization. This article analyzes the state-of-the-art of MaaS ecosystems and describes the development of a digital MaaS ecosystem based on an updated and advanced version of the reference architecture for smart connected factories, called the Smart Factory Web. Furthermore, this article describes a demonstrator for a federated MaaS marketplace for Catena-X which leverages the full technological potential of this digital ecosystem. In conclusion, the evaluation of the implemented digital ecosystem enables the advancement of the reference architecture Smart Factory Web, which can now be used as a blueprint for open, sustainable, and resilient digital manufacturing ecosystems. [ABSTRACT FROM AUTHOR]

Currently, software systems must be appropriately developed to support an amount of variability for accommodating different requirements. To support such development, a diversity of tools has already been designed for variability management (i.e., identification, modeling, evaluation, and realization). However, due to this diversity, there is a lack of consensus on what in fact software variability tools are and even what functionalities they should provide. Besides that, the building of new tools is still an effort- and time-consuming task. To support their building, we present VMTools-RA, a reference architecture that encompasses knowledge and practice for developing and evolving variability tools. Designed in a systematic way, VMTools-RA was evaluated throughout: a controlled experiment with software developer practitioners; and an instantiation of the VMTools-RA architecture to implement a software variability tool, named SMartyModeling. As a result, VMTools-RA is evidenced to be feasible and it can be considered an important contribution to the software variability and developers of variability-intensive software systems community, which require specific tools developed in a faster manner with less risk, what a reference architecture could provide. [ABSTRACT FROM AUTHOR]

Industry 4.0 is a new paradigm that is transforming the industrial scenario. It has generated a large amount of scientific studies, commercial equipment and, above all, high expectations. Nevertheless, there is no single definition or general agreement on its implications, specifically in the field of automation and supervision systems. In this paper, a review of the Industry 4.0 concept, with equivalent terms, enabling technologies and reference architectures for its implementation, is presented. It will be shown that this paradigm results from the confluence and integration of both existing and disruptive technologies. Furthermore, the most relevant trends in industrial automation and supervision systems are covered, highlighting the convergence of traditional equipment and those characterized by the Internet of Things (IoT). This paper is intended to serve as a reference document as well as a guide for the design and deployment of automation and supervision systems framed in Industry 4.0.

Cyber Threat intelligence (CTI) systems offer new capabilities in the arsenal of information security experts, who can explore new sources of data that were partially exploited during the past decades. This paper deals with the exploitation of discussion forums as a source of raw data for a cyber threat intelligence process. Specifically, it analyzes the discussion forums’ characteristics and investigates their relationship with CTI. It proposes a semantic schema for the representation of data collected from discussion forums. Then, it applies a systematic methodology to design the reference architecture of the SECDFAN system, which handles the creation of CTI products following a comprehensive approach from the source selection to CTI product sharing and security experts’ collaboration. The final product of this work is the SECDFAN reference architecture. The contribution of this paper is the development of a CTI reference architecture of a system that, by design, handles all CTI-related issues for creating CTI products by analyzing the content of discussion forums.

The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used. DEMETER (Building an Interoperable, Data-Driven, Innovative and Sustainable European Agri-Food Sector) addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources (e.g., devices, networks, platforms) and enables the seamless sharing of data and knowledge throughout the agri-food chain. This paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers, which is validated via two rounds of 20 large-scale pilots along the DEMETER lifecycle. This paper elaborates on the two pilots carried out in region of Murcia in Spain, which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.

This paper presents a novel reference architecture for blockchain-enabled federated learning (BCFL), a state-of-the-art approach that amalgamates the strengths of federated learning and blockchain technology. We define smart contract functions, stakeholders and their roles, and the use of interplanetary file system (IPFS) as key components of BCFL and conduct a comprehensive analysis. In traditional centralized federated learning, the selection of local nodes and the collection of learning results for each round are merged under the control of a central server. In contrast, in BCFL, all these processes are monitored and managed via smart contracts. Additionally, we propose an extension architecture to support both cross-device and cross-silo federated learning scenarios. Furthermore, we implement and verify the architecture in a practical real-world Ethereum development environment. Our BCFL reference architecture provides significant flexibility and extensibility, accommodating the integration of various additional elements, as per specific requirements and use cases, thereby rendering it an adaptable solution for a wide range of BCFL applications. As a prominent example of extensibility, decentralized identifiers (DIDs) have been employed as an authentication method to introduce practical utilization within BCFL. This study not only bridges a crucial gap between research and practical deployment but also lays a solid foundation for future explorations in the realm of BCFL. The pivotal contribution of this study is the successful implementation and verification of a realistic BCFL reference architecture. We intend to make the source code publicly accessible shortly, fostering further advancements and adaptations within the community.

The emerging availability of quantum compute resources fosters the examination of its exploitation possibilities in different scientific domains, like artificial intelligence, manufacturing or finance. A significant number of research scientists primarily rely on cloud computing infrastructures while conducting research, whereas access to real (mostly remote) quantum hardware resources requires the deployment and proper configuration of different software components. In this paper we present a hybrid, cloud-based reference architecture that lowers the entry barrier to start new experiments with a wide range of quantum compute resources. The solution facilitates the execution of distributed quantum computing simulations in traditional cloud environments, and also access to several remote quantum compute resources. The reference architecture is highly portable to various cloud platforms, resulting in efficient adaptation and application possibilities by research communities. The paper describes our related experiences using commercial cloud providers and on the federated, OpenStack-based research infrastructure of the Hungarian Research Network (abbreviated as HUN-REN).

Realization of situation-awareness for autonomous robotics applications in edge computing environment is challenging. First, computing capabilities of edge devices are limited, which must be considered in the execution of machine learning (ML)-based solutions. Second, many technologies are available for realizing situation-aware capabilities, but comparison and integration of solutions creates additional challenges. Third, existing ML-based models are often not directly applicable for realizing custom applications, and model(s) may need to be re-trained with new data. The contribution of this paper is efficiency and feasibility evaluation of human pose recognition and object detection technologies in edge computing environment. Several lessons learnt covering constraints are presented regarding feasibility of the experimented technologies and data sets. The efficiency evaluation results indicated that simultaneous human pose recognition (Google’s Movenet) and object detection (Yolov5) on Jetson AGX Xavier achieved ~13-16 FPS, while GPU and CPU utilization remained at a medium level, and most of the memory remained unused (< 44 %). Object concept and human pose concept activation algorithms may be considered as an additional contribution. Realized architecture design of the prototyped system in multiple computing environments can be considered as a partial evaluation of a ML-based big data reference architecture.

Cloud architecture blueprints or reference architectures allow the reuse of existing knowledge and best practices when creating new cloud native solutions. Therefore, debugging of reference architecture candidates (or their new versions) is an extremely crucial but tedious and time-consuming task due to the deployment of complex services in typical multi-tenant and non-deterministic environments. During the debugging/testing/maintenance scenarios, we might be able to achieve greater levels of test coverage (and eventually improved reliability) by modelling and verifying at least their most fundamental building blocks and their interconnections. The main objective of our work is to integrate stochastic modelling and verification techniques based on deep learning methods into the debugging cycle in order to handle large state spaces more efficiently, i.e. by steering the process of traversing state space towards suspicious situations that may result in potential bugs in the actual system with smart steering during the traversal. For this purpose, our presented and illustrated approach combines (among others) Continuous Time Markov Chain modelling (CTMC) techniques with deep learning methods including autoencoder, Long Short-Term Memory (LSTM) and Graph Neural Network (GNN) models. Our experiences are summarized with widespread cloud design patterns including load balancing and service mesh topologies. According to the results, the debugging cycle can be partly automated through the application of deep learning methods. The autoencoders are able to detect erroneous load balancer behaviors (anomalies) in complex configurations; the LSTMs demonstrate implicitly some random nature of the inspected processes, and GNNs exploit the additional topology-related information in service meshes.

Reference architectures (RAs) are successfully used to represent families of concrete software architectures in several domains such as automotive, banking, and the Internet of Things. RAs inspire architects when designing concrete architectures, and they help to guarantee compliance with architectural decisions, regulatory requirements, as well as architectural qualities. Despite their importance, reference architectures still suffer from a number of open technical issues, including (i) the lack of a common interpretation, a precise notation for their representation and documentation, and (ii) the lack of conformance mechanisms for checking the compliance of concrete architectures to their related reference architecture, architectural decisions, regulatory requirements, etc. This paper addresses these two issues by introducing a model-driven approach that leverages (i) a domain-independent metamodel for the representation of reference architectures and (ii) the combination of model transformation and weaving techniques for the automatic conformance checking of concrete architectures. We evaluate the applicability, effectiveness, and generalizability of our approach using illustrative examples from the web browsers and automotive domains, including an assessment from an independent practitioner. [ABSTRACT FROM AUTHOR]

With the diffusion of integrated design environments and tools for visual threat modeling for critical infrastructures, the concept of Digital Twin (DT) is gaining momentum in the field of cybersecurity. Its main use is for enabling attack simulations and evaluation of countermeasures, without causing outage of the physical system. However, the use of a DT is considered foremost as a facilitator of system operation rather than an integral part of its architecture design. In this work, we introduce a specific architecture view in the system representation, called Cybersecurity View. From it, we derive a cybersecurity Digital Twin as part of the security-by-design practice for Industrial Automation and Control Systems used in Critical Infrastructures. Not only this digital twin serves the purpose of simulating cyber-attacks and devising countermeasures, but its design and function are also directly tied to the architecture model of the system for which the cybersecurity requirements are posed. Moreover, this holds regardless of whether the model is generated as part of the development cycle or through an empirical observation of the system as-is. With this, we enable the identification of adequate cybersecurity measures for the system, while improving the overall system design. To demonstrate the practical usefulness of the proposed methodology, its application is illustrated through two real-world use cases: the Cooperative Intelligent Transport System (C-ITS) and the Road tunnel scenario. [ABSTRACT FROM AUTHOR]

The field of cloud computing has witnessed tremendous progress, with commercial cloud providers offering powerful distributed infrastructures to small and medium enterprises (SMEs) through their revolutionary pay-as-you-go model. Simultaneously, the rise of containers has empowered virtualisation, providing orchestration technologies for the deployment and management of large-scale distributed systems across different geolocations and providers. Big data is another research area which has developed at an extraordinary pace as industries endeavour to discover innovative and effective ways of processing large volumes of structured, semi-structured, and unstructured data. This research aims to integrate the latest advances within the fields of cloud computing, virtualisation, and big data for a systematic approach to stream processing. The novel contributions of this research are: (1) MC-BDP, a reference architecture for big data stream processing in a containerised, multi-cloud environment; (2) a case study conducted with the Estates and Sustainability departments at Leeds Beckett University to evaluate an MC-BDP prototype within the context of energy efficiency for smart buildings. The study found that MC-BDP is scalable and fault-tolerant across cloud environments, key attributes for SMEs managing resources under budgetary constraints. Additionally, our experiments on technology agnosticism and container co-location provide new insights into resource utilisation, cost implications, and optimal deployment strategies in cloud-based big data streaming, offering valuable guidelines for practitioners in the field.

Cyber Threat intelligence (CTI) systems offer new capabilities in the arsenal of information security experts, who can explore new sources of data that were partially exploited during the past decades. This paper deals with the exploitation of discussion forums as a source of raw data for a cyber threat intelligence process. Specifically, it analyzes the discussion forums' characteristics and investigates their relationship with CTI. It proposes a semantic schema for the representation of data collected from discussion forums. Then, it applies a systematic methodology to design the reference architecture of the SECDFAN system, which handles the creation of CTI products following a comprehensive approach from the source selection to CTI product sharing and security experts' collaboration. The final product of this work is the SECDFAN reference architecture. The contribution of this paper is the development of a CTI reference architecture of a system that, by design, handles all CTI-related issues for creating CTI products by analyzing the content of discussion forums. [ABSTRACT FROM AUTHOR]

Agriculture is one of the major sectors of the global economy and also a software-intensive domain. The digital landscape of agriculture is composed of multiple digital ecosystems, which together constitute an agricultural domain ecosystem, also referred to as the "Agricultural Data Space" (ADS). As the domain is so huge, there are several sub-domains and specialized solutions, and each of them poses challenges to interoperability. Additionally, farmers have increasing concerns about data sovereignty. In the context of the research project COGNAC, we elicited architecture drivers for interoperability and data sovereignty in agriculture and designed a reference architecture of a platform that aims to address these qualities in the ADS. In this paper, we present the solution concepts and design decisions that characterize the reference architecture. Early prototypes have been developed and made available to support the validation of the concept. [ABSTRACT FROM AUTHOR]

Next Generation Internet of Things (NGIoT) addresses the deployment of complex, novel IoT ecosystems. These ecosystems are related to different technologies and initiatives, such as 5G/6G, AI, cybersecurity, and data science. The interaction with these disciplines requires addressing complex challenges related with the implementation of flexible solutions that mix heterogeneous software and hardware, while providing high levels of customisability and manageability, creating the need for a blueprint reference architecture (RA) independent of particular existing vertical markets (e.g., energy, automotive, or smart cities). Different initiatives have partially dealt with the requirements of the architecture. However, the first complete, consolidated NGIoT RA, covering the hardware and software building blocks, and needed for the advent of NGIoT, has been designed in the ASSIST-IoT project. The ASSIST-IoT RA delivers a layered and modular design that divides the edge-cloud continuum into independent functions and cross-cutting capabilities. This contribution discusses practical aspects of implementation of the proposed architecture within the context of real-world applications. In particular, it is shown how use of cloud-native concepts (microservices and applications, containerisation, and orchestration) applied to the edge-cloud continuum IoT systems results in bringing the ASSIST-IoT concepts to reality. The description of how the design elements can be implemented in practice is presented in the context of an ecosystem, where independent software packages are deployed and run at the selected points in the hardware environment. Both implementation aspects and functionality of selected groups of virtual artefacts (micro-applications called enablers) are described, along with the hardware and software contexts in which they run. [ABSTRACT FROM AUTHOR]

Modeling and simulation (M&S) techniques are effectively used in many application domains to support various operational tasks ranging from system analyses to innovative training activities. Any (M&S) effort might strongly benefit from the adoption of service orientation and cloud computing to ease the development and provision of M&S applications. Such an emerging paradigm is commonly referred to as M&S-as-a-Service (MSaaS). The need for orchestrating M&S services provided by different partners in a heterogeneous cloud infrastructure introduces new challenges. In this respect, the adoption of an effective architectural approach might significantly help the design and development of MSaaS infrastructure implementations that cooperate in a federated environment. In this context, this work introduces a MSaaS reference architecture (RA) that aims to investigate innovative approaches to ease the building of inter-cloud MSaaS applications. Moreover, this work presents ArTIC-MS, a conceptual architecture that refines the proposed RA for introducing the TOSCA (topology and orchestration specification for cloud applications) standard. ArTIC-MS's main objective is to enable effective portability and interoperability among M&S services provided by different partners in heterogeneous federations of cloud-based MSaaS infrastructure. To show the validity of the proposed architectural approach, the results of concrete experimentation are provided. [ABSTRACT FROM AUTHOR]

Process Industry is one of the leading sectors of the world economy, characterized however by intense environmental impact, and very high-energy consumption. Despite a traditional low innovation pace in PI, in the recent years a strong push at worldwide level towards the dual objective of improving the efficiency of plants and the quality of products, significantly reducing the consumption of electricity and CO2 emissions has taken momentum. Digital Technologies (namely Smart Embedded Systems, IoT, Data, AI and Edge-to-Cloud Technologies) are enabling drivers for a Twin Digital-Green Transition, as well as foundations for human centric, safe, comfortable and inclusive workplaces. Currently, digital sensors in plants produce a large amount of data, which in most cases constitutes just a potential and not a real value for Process Industry, often locked-in in close proprietary systems and seldomly exploited. Digital technologies, with process modelling-simulation via digital twins, can build a bridge between the physical and the virtual worlds, bringing innovation with great efficiency and drastic reduction of waste. In accordance with the guidelines of Industrie 4.0 this work proposes a modular and scalable Reference Architecture, based on open source software, which can be implemented both in brownfield and greenfield scenarios. The ability to distribute processing between the edge, where the data have been created, and the cloud, where the greatest computational resources are available, facilitates the development of integrated digital solutions with cognitive capabilities. The reference architecture is being validated in the three pilot plants, paving the way to the development of integrated planning solutions, with scheduling and control of the plants, optimizing the efficiency and reliability of the supply chain, and balancing energy efficiency. [ABSTRACT FROM AUTHOR]

Introduction: Hospital information system (HIS) as an integrated information system is used for daily operations, planning, care, and treatment of patients. Due to the existence of various and heterogeneous healthcare information systems, HIS encounters interoperability problems. In this regard, this study aimed to propose an integrated architecture for HIS based on the interoperability model. Method: This research is a strategic-applied study for achieving an integrated HIS architecture, focusing on clinical information systems (CIS). First, the requirements of clinical information systems were carried out through library studies, the review of the statistics office of the Ministry of Health, Treatment and Medical Education, and it was also reviewed and confirmed by information technology experts. Then, different interoperability frameworks and HIS architecture models were studied. Finally, the integrated HIS architecture model was proposed based on the interoperability model. Results: The integrated HIS architecture based on the interoperability model includes three architecture models as follows: references, software, and information. Reference architecture is proposed generally for the HIS and customized for CIS. For implementing various HISs, software architecture is proposed. And information architecture is used for storing, processing, and transmitting the information. Conclusion: Considering the necessity of integration in the health system, this study creates the possibility of interoperability and integration between HIS systems by applying the guidelines of integration in the architecture, which leads to cost reduction, quality improvement, and timely decision-making.

Cloud deployment architectures have become a preferable computation model of Big Data (BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a such deployment model, the data are no longer physically maintained under the user’s direct control, which raises new security concerns. In this context, BD security plays a decisive role in the widespread adoption of cloud architectures. However, it is challenging to develop a comprehensive security plan unless it is based on a preliminary analysis that ensures a realistic secure assembly and addresses domain-specific vulnerabilities. This article presents a novel security-by-design framework for BD frameworks deployment over cloud computing (BigCloud). In particular, it relies on a systematic security analysis methodology and a completely automated security assessment framework. Our framework enables the mapping of BigCloud security domain knowledge to the best practices in the design phase. We validated the proposed framework by implementing an Apache Hadoop stack use case. The study findings demonstrate its effectiveness in improving awareness of security aspects and reducing security design time. It also evaluates the strengths and limitations of the proposed framework, from which it highlights the main existing and open challenges in the BigCloud-related area. [ABSTRACT FROM AUTHOR]

Future data-intensive intelligent applications are required to traverse across the cloud-to-edge-to-IoT continuum, where cloud and edge resources elegantly coordinate, alongside sensor networks and data. However, current technical solutions can only partially handle the data outburst associated with the IoT proliferation experienced in recent years, mainly due to their hierarchical architectures. In this context, this paper presents a reference architecture of a meta-operating system (RAMOS), targeted to enable a dynamic, distributed and trusted continuum which will be capable of facilitating the next-generation smart applications at the edge. RAMOS is domain-agnostic, capable of supporting heterogeneous devices in various network environments. Furthermore, the proposed architecture possesses the ability to place the data at the origin in a secure and trusted manner. Based on a layered structure, the building blocks of RAMOS are thoroughly described, and the interconnection and coordination between them is fully presented. Furthermore, illustration of how the proposed reference architecture and its characteristics could fit in potential key industrial and societal applications, which in the future will require more power at the edge, is provided in five practical scenarios, focusing on the distributed intelligence and privacy preservation principles promoted by RAMOS, as well as the concept of environmental footprint minimization. Finally, the business potential of an open edge ecosystem and the societal impacts of climate net neutrality are also illustrated. [ABSTRACT FROM AUTHOR]

Manufacturing as a Service (MaaS) enables a paradigm shift in the current manufacturing landscape, from integrated production and inflexible, fragile supply chains to open production and flexible, robust supply chains. As part of this evolution, new scaling effects for production capacities and customer segments are possible. This article describes how to accomplish this paradigm shift for the automotive industry by building a digital MaaS ecosystem for the large-scale automotive innovation project Catena-X, which aims at a standardized global data exchange based on European values. A digital MaaS ecosystem can not only achieve scaling effects, but also realize new business models and overcome current and future challenges in the areas of legislation, sustainability, and standardization. This article analyzes the state-of-the-art of MaaS ecosystems and describes the development of a digital MaaS ecosystem based on an updated and advanced version of the reference architecture for smart connected factories, called the Smart Factory Web. Furthermore, this article describes a demonstrator for a federated MaaS marketplace for Catena-X which leverages the full technological potential of this digital ecosystem. In conclusion, the evaluation of the implemented digital ecosystem enables the advancement of the reference architecture Smart Factory Web, which can now be used as a blueprint for open, sustainable, and resilient digital manufacturing ecosystems.

Each person on the Internet typically has several digital accounts, which are associated with different identity information. During the last years, various identity and access management (I&AM) approaches were established to help manage all these digital identities and operate online services within an organization and beyond. This development has led to heterogeneity, making it hard to differentiate between, comply with, and combine these approaches. In this article, we propose a novel reference service model framework for different I&AM flavors designed with the open enterprise modeling language ArchiMate. The proposed identity management service model framework (IMSMF) consists, on the one hand, of a meta-model and several models for various protocols and implementations, and, on the other hand, models, which were designed in a generic service-oriented way. These models lead to a universal model to indicate additional components for an enhanced I&AM. IMSMF has been evaluated through several rounds of expert interviews. IMSMF helps to establish, enhance, and change I&AM systems while also being a base for profound further research.