Enabler For Interoperability Research Articles

Paving the way to establishing the digital-friendly health and care information model in Kazakhstan

IntroductionKazakhstan has made significant strides in digital health implementation since 2013, transitioning from paper-based systems to wide implementation of digital solutions. However, challenges persist, notably the misalignment between existing data collection requirements and ongoing digital transformations. To address this obstacle, the development of a new digital-friendly requirements for health data collection at provider levels was initiated. Material and methodsA comparative analysis of all existing requirements on health and care data collection set a foundation for further actions. A dedicated technical working group, established by the Ministry of Healthcare, oversaw this process, while several specialized expert groups participated in detailed discussions to ensure alignment with healthcare needs. We took as a basis the legislative act enforcing use of data forms inherited from pre-digital era. Data elements from most used forms were cataloged, checked for consistency, and standardized. ISO 13940 standard guided transformation of rigid paper-based forms into flexible digital-friendly data sets. ResultsAnalysis of the healthcare legislation reveals significant optimization opportunities. We categorized 157 forms into four groups by their content and role and focusing on clinical and administrative records for transformation. Data elements’ analysis led to developing 209 standardized classifications with data values. 83 data sets, encompassing clinical and administrative domains, were developed to substitute 63 (out of 157) forms. Therefore, the foundation for better data and structure interoperability was set. DiscussionThe top-down approach to digital health standardization, combined with open market policies, results in inconsistent data collection practices. Developed data sets align with the goal of developing the national Electronic Health Records system as enabler for interoperability and adds a bottom-up perspective to digital health standardization. This effort addresses the lack of guidance for digital data model development, however additional efforts required to change the current practice and finalize the national legislation transformation into digital-friendly mode.

Data sharing in agricultural supply chains: Using semantics to enable sustainable food systems

The agrifood system faces a great many economic, social and environmental challenges. One of the biggest practical challenges has been to achieve greater data sharing throughout the agrifood system and the supply chain, both to inform other stakeholders about a product and equally to incentivise greater environmental sustainability. In this paper, a data sharing architecture is described built on three principles (a) reuse of existing semantic standards; (b) integration with legacy systems; and (c) a distributed architecture where stakeholders control access to their own data. The system has been developed based on the requirements of commercial users and is designed to allow queries across a federated network of agrifood stakeholders. The Ploutos semantic model is built on an integration of existing ontologies. The Ploutos architecture is built on a discovery directory and interoperability enablers, which use graph query patterns to traverse the network and collect the requisite data to be shared. The system is exemplified in the context of a pilot involving commercial stakeholders in the processed fruit sector. The data sharing approach is highly extensible with considerable potential for capturing sustainability related data.

Distributed cyber-physical systems that enhance local-based frugal innovation toward a sustainable built environment

The paper debates the comparison between centralized cyber-physical systems and distributed cyber-physical systems (CPS). Centralized CPS implies a system where a single player standardizes data format and protocol together with core services. Distributed CPS implies a system where varieties of digitalization systems by multiple vendors are interconnected to adapt to specific local contexts. Then the paper identifies that distributed CPS has practical advantages over centralized CPS. However, distributed CPS has potential disadvantages that threaten interconnectivity among digitalization systems by multiple vendors. The paper illustrates how such fragmentation could be avoided; it presents how interoperable linkage among multiple systems is realized. IoT-Hub, a sort of data conversion system, is an enabler of interoperability. The paper illustrates the framework of distributed CPS. That comprises several layers that could be managed autonomously by independent players regardless of activities in other layers. The paper exemplifies local-based frugal innovation by such distributed CPS. One example is IoT-based proactive energy demand control system. The system is composed of sensing systems, component systems and application software. The distributed CSP that deploys IoT-Hub enables adaptable coordination of building elements and digitalized systems respecting local specific contexts. In such a way, distributed CPS provides a comfortable indoor climate with optimized energy use. The other example is IoT-based inventory system for building materials. The system is composed of manufacturing process monitoring systems and logistics monitoring systems. The integrated system could provide reportable and verifiable inventory data of building materials. The system can facilitate responsible use of building materials by providing inventory data that is a piece of essential information for environmental declaration. Exemplified cases suggest how distributed CPS strategy has the potential to encourage a broad range of entrepreneurs to commit to frugal innovation toward a sustainable built environment.

A collaborative semantic framework based on activities for the development of applications in Smart Home living labs

An essential element to improve the quality of life at home is to understand the behavior of its inhabitants and the activities they perform on a daily basis. The collection and analysis of this information in Smart Home environments poses several challenges, mainly data variability, and the management and synchronization of devices, which have limited the adoption of this kind of solutions. Researchers tend to work focused on providing solutions to specific issues and, in research environments that share infrastructure, such as living labs, it is common that previous developments of other teams are not reused. This process is suboptimal and does not allow understanding the Smart Home as a single space, but as a set of functional islands. To overcome these obstacles, a novel collaborative semantic framework is proposed for the extraction, characterization, and formalization of data to enable its reutilization and interpretation. The framework is based on the concept of activity, decomposed as a series of actions and events, and follows current trends in the domain of Activities of Daily Living and Smart Homes. A set of interoperability enablers based on JSON schemas and formalized descriptions of the domain have been proposed as the main facilitators of collaboration and the integration of elements coexisting in the Smart Home environment. The evaluation of the framework through the development of two research projects showed significant benefits, improving the overall quality of the solutions and enriching the extraction of insights through the correlated analysis of data.

Distribution Management Systems for Smart Grid: Architecture, Work Flows, and Interoperability

The smart grid integrates advanced sensors, a twoway communication infrastructure, and high-performance computation-based control. The distribution management systems for smart grid include several functions for manipulating legacy voltage control devices and distributed energy resources through closed-loop volt/var control, leading to wide-area regulation of voltages in the presence of fluctuating power. The other primary distribution network analysis application is concerned with automatic fault location and service restoration following fault events, aiming to provide the grid with autonomous intelligence for self-healing. Communication technologies are vital to enable the computing applications of distribution networks, whether they work in centralized or distributed modes. This paper presents the state of the art in distribution management system architectures and modern workflows showing data exchange, practical parallel implementations designed to handle large amounts of data, in addition to communication standards that serve as interoperability enablers. It demystifies the relationship between different functions developed independently by power system researchers and shows their operation as a complete system, thus placing them in a better context for future research and development.

Manufacturing Execution System Integration through the Standardization of a Common Service Model for Cyber-Physical Production Systems

Digital transformation and artificial intelligence are creating an opportunity for innovation across all levels of industry and are transforming the world of work by enabling factories to embrace cutting edge Information Technologies (ITs) into their manufacturing processes. Manufacturing Execution Systems (MESs) are abandoning their traditional role of legacy executing middle-ware for embracing the much wider vision of functional interoperability enablers among autonomous, distributed, and collaborative Cyber-Physical Production System (CPPS). In this paper, we propose a basic methodology for universally modeling, digitalizing, and integrating services offered by a variety of isolated workcells into a single, standardized, and augmented production system. The result is a reliable, reconfigurable, and interoperable manufacturing architecture, which privileges Open Platform Communications Unified Architecture (OPC UA) and its rich possibilities for information modeling at a higher level of the common service interoperability, along with Message Queuing Telemetry Transport (MQTT) lightweight protocols at lower levels of data exchange. The proposed MES architecture has been demonstrated and validated in several use-cases at a research manufacturing laboratory of excellence for industrial testbeds.

Data Spine: A Federated Interoperability Enabler for Heterogeneous IoT Platform Ecosystems.

Today, the Internet of Things (IoT) is pervasive and characterized by the rapid growth of IoT platforms across different application domains, enabling a variety of business models and revenue streams. This opens new opportunities for companies to extend their collaborative networks and develop innovative cross-platform and cross-domain applications. However, the heterogeneity of today’s platforms is a major roadblock for mass creation of IoT platform ecosystems, pointing at the current absence of technology enablers for an easy and innovative composition of tools/services from the existing platforms. In this paper, we present the Data Spine, a federated platform enabler that bridges IoT interoperability gaps and enables the creation of an ecosystem of heterogeneous IoT platforms in the manufacturing domain. The Data Spine allows the ecosystem to be extensible to meet the need for incorporating new tools/services and platforms. We present a reference implementation of the Data Spine and a quantitative evaluation to demonstrate adequate performance of the system. The evaluation suggests that the Data Spine provides a multitude of advantages (single sign-on, provision of a low-code development environment to support interoperability and an easy and intuitive creation of cross-platform applications, etc.) over the traditional approach of users joining multiple platforms separately.

Towards Asset Administration Shell-Based Resource Virtualization in 5G Architecture-Enabled Cyber-Physical Production Systems

One core characteristic of cyber-physical production systems (CPPS) is their architecture, which is based on service-oriented paradigms interconnecting operational technology (OT) and information technology (IT) components. With the advent of 5G architectures in production environments communication technology components become more prevalent and integral parts of a CPPS. To keep the complexity manageable all components of the ICT and OT realms need to be integrated in a unifying approach. This paper proposes a concept on how to virtualize ICT and OT resources by using Industrie 4.0 Asset Administration Shells and their respective submodels as an enabler for interoperability in CPPS.

Literature review on autonomous production control methods

ABSTRACT Production environments are becoming more complex and dynamics. This is influenced by external factors related with products’ characteristics and costumers’ requirements and internal factors related with processing times variability, machine failures, setup times, between others. To face this increasing complexity and dynamics, it is crucial to have effective production control methods, considering Interoperability Enablers for Cyber-Physical Systems. However, production control methods most in used today, are focused on centralised decision-making and planning, and considered inadequate to deal with the increasing dynamics of these systems. Autonomous Production Control (APC) may be an adequate alternative to face this complexity, allowing flexible and rapid reaction to possible disturbances that may occur in the production system. However, as APC is the relatively new concept, there are no existing surveys. Therefore, we review and discuss the literature on APC methods to bring more attention to this promising topic of research, highlighting future research directions.

Ontology - based context resolution in internet of things enabled diagnostics

Internet of things (IoT)-generated data from industrial systems are often collected in non-actionable form, thus not directly aiding maintenance actions. Context information management is often seen as an enabler for interoperability and context-based service adaptation, acting as a mechanism for linking data with knowledge to adaptive data and services. Ontology-based approaches for semantic maintenance have been proposed in the past as a data and service mediation mechanism and are adopted here as the starting point employed to develop a context resolution service for industrial diagnostics. The underlying ontology of the context resolution mechanism is relevant to failure analysis of mechanical components. The terminology and relationship between concepts are structured on the basis of relevant standards with a reliability-oriented knowledge grounding. A reasoning mechanism is employed to deliver context resolution and the derived context can add a metadata layer on data or events generated by automated and human-driven means. The approach is applied on a gearbox test rig appropriate for emulating complex misalignment cases met in many manufacturing and aerospace applications.

SAREF4INMA: A SAREF extension for the industry and manufacturing domain

The IoT landscape is characterized by a fragmentation of standards, platforms and technologies, often scattered among different vertical domains. To prevent the market to continue to be fragmented and power-less, a protocol-independent semantic layer can serve as enabler of interoperability among the various smart devices from different manufacturers that co-exist in a specific industry domain, but also across different domains. To that end, the SAREF ontology was created in 2015 with the intention to interconnect data, enabling the communication between IoT devices that use different protocols and standards. A number of industrial sectors consequently expressed their interest to extend SAREF into their domains in order to fill the gaps of the semantics not yet covered by their communication protocols. Therefore, the SAREF4INMA ontology was recently created to extend SAREF for describing the Smart Industry & Manufacturing domain. SAREF4INMA is based on several standards and IoT initiatives, as well as on real use cases, and includes classes, properties and instances specifically created to cover the industry and manufacturing domain. This work describes the approach followed to develop this ontology, specifies its requirements and also includes a practical example of how to use it.

Data sharing and interoperability: Fostering innovation and competition through APIs

Application Programming Interfaces (APIs) have been identified by the European Commission as a key enabler of interoperability among private and public undertakings. Further, a systematic adoption of open and standardized APIs by firms and developers appears crucial to unlock competition and ultimately promote the flourishing of Artificial Intelligence (AI) and Internet of Things (IoT) innovation.Analysing the main European regulatory initiatives which have so far surfaced in the realm of data governance (right to personal data portability, free flow of non-personal data, access to customer account data rule, re-use of government data), it seems that the EU legislator is not tackling the matter consistently. Indeed, on one side, all these initiatives share a strong reliance on APIs as a key facilitator to ensure a sound and effective data sharing ecosystem. However, on the other side, all these attempts are inherently different in terms of rationale, scope and implementation. The article stresses that data sharing via APIs requires a complex implementation process and sound standardization initiatives are essential for its success. Moreover, data pooling agreements need to be targeted in advance by competition law so to incentivize their adoption and leverage their pro-competitive potential. As for pricing and compensation issues, we point out that placing excessive reliance on fair, reasonable and non-discriminatory (FRAND) terms might be counterproductive.

Software-Defined Underwater Acoustic Modems: Historical Review and the NILUS Approach

Flexible/adaptive acoustic modems that are reprogrammable/reconfigurable at all layers of the communication stack, either by a user or by means of autonomous decisions, are considered as an important enabler for interoperability and cognitive networking in the underwater domain. In this paper, we review the existing literature on software-defined acoustic modems (SDAMs) for underwater communications and networking, considering past and ongoing academic efforts, as well as industrial developments and European collaborations centered on software-defined modem structures and functionalities. We then zoom in on relevant R&D efforts currently taking place in a defense cooperation between The Netherlands and Norway, targeting the design of a software-defined modem for the NILUS MK 2 sensor node. This modem is built using general-purpose (GP) computing architectures running open-source operating system and tools, thereby making a further step toward software-defined open-architecture underwater acoustic modems. The first field tests of the NILUS MK 2 node in multihop underwater acoustic networks are presented, showing satisfactory performance in shallow and open waters.

Towards a sustainable interoperability in networked enterprise information systems: Trends of knowledge and model-driven technology

In a turbulent world, global competition and the uncertainty of markets have led organizations and technology to evolve exponentially, surpassing the most imaginary scenarios predicted at the beginning of the digital manufacturing era, in the 1980s. Business paradigms have changed from a standalone vision into complex and collaborative ecosystems where enterprises break down organizational barriers to improve synergies with others and become more competitive. In this context, paired with networking and enterprise integration, enterprise information systems (EIS) interoperability gained utmost importance, ensuring an increasing productivity and efficiency thanks to a promise of more automated information exchange in networked enterprises scenarios. However, EIS are also becoming more dynamic. Interfaces that are valid today are outdated tomorrow, thus static interoperability enablers and communication software services are no longer the solution for the future. This paper is focused on the challenge of sustaining networked EIS interoperability, and takes up input from solid research initiatives in the areas of knowledge management and model driven development, to propose and discuss several research strategies and technological trends towards next EIS generation.

Secure Data Sharing and Processing in Heterogeneous Clouds

Abstract The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs.

Standard-based service-oriented infrastructure to integrate intelligent buildings in distributed generation and smart grids

Buildings are ecosystems that influence and are influenced by internal and external factors concerning both Distributed Generation (DG) and Distributed Energy Systems (DES). Existing communication and integration standards, tools and platforms for buildings and power systems still show several limitations in terms of data integration and correlation, applicability and vendor independence. These are required to support adequate online forecasting, management and decision, in the context of DG and DES. To overcome this drawbacks a holistic view is necessary, combining streamed (real-time) and asynchronous data communication of relevant sources of information influencing both the building and the distributed energy system, such as weather, occupancy, energy system characteristics and associated devices, among others. This work proposes a communication infrastructure supported by communication standards and by a Service-Oriented Architecture (SOA). This Standard-based Service-oriented Infrastructure (SSI) addresses the communication between buildings and power system management tools and each of the building systems, devices and sources of information. Open communication standards are used, such as IEC 61850 and Device Profile for Web Services (DPWS). The SSI becomes an interoperability enabler regarding complex systems’ management where occupants and energy production, distribution and consumption are considered, thus encouraging the development of Plug and Play and vendor independent operation.

An Efficient and Scalable Approach for Ontology Instance Matching

Ontology instance matching is a key interoperability enabler across heterogeneous data resources in the Semantic Web for integrating data semantically. Although most of the research has been emphasized on schema level matching so far, research on ontology matching is shifting from ontology schema or concept level to instance level to fulfill the vision of “Web of Data”. Ontology instances define data semantically and are kept in knowledge base. Since, heterogeneous sources of massive ontology instances grow sharply day-by-day, scalability has become a major research concern in ontology instance matching of semantic knowledge bases. In this study, we propose a method by filtering instances of knowledge base into two stages to address the scalability issue. First stage groups the instances based on the relation of concepts and next stage further filters the instances based on the properties associated to instances. Then, our instance matcher works by comparing an instance within a classification group of one knowledge base against the instances of same sub-group of other knowledge base to achieve interoperability. We experiment our proposed method with several benchmark data sets namely OAEI-2009, OAEI-2010 and OAEI-2011. On comparison with other baseline methods, our proposed method shows satisfactory result.

Web services discovery across heterogeneous military networks

NATO has identified Web services standards as a key enabler for interoperability between the different military systems used by various NATO nations. Compared to many civilian systems, military networks vary greatly in terms of computing resources, network bandwidth, mobility and stability, and distributed applications use several different networks concurrently or interact across them. In such dynamic and heterogeneous environments, runtime service discovery is a necessity. According to the W3C, discovery is the act of locating a machine-processable description of a Web service-related resource that may have been previously unknown and that meets certain functional criteria. In this article we present our approach to service discovery, where we combine Web services standards and proprietary solutions using our prototype interoperability gateway. This approach has been experimentally evaluated in a military experiment featuring both mobile ad hoc networks and fixed infrastructure networks, and the results show that transparent discovery between proprietary solutions and Web services discovery standards can be achieved.

OILing the way to machine understandable bioinformatics resources.

The complex questions and analyses posed by biologists, as well as the diverse data resources they develop, require the fusion of evidence from different, independently developed, and heterogeneous resources. The web, as an enabler for interoperability, has been an excellent mechanism for data publication and transportation. Successful exchange and integration of information, however, depends on a shared language for communication (a terminology) and a shared understanding of what the data means (an ontology). Without this kind of understanding, semantic heterogeneity remains a problem for both humans and machines. One means of dealing with heterogeneity in bioinformatics resources is through terminology founded upon an ontology. Bioinformatics resources tend to be rich in human readable and understandable annotation, with each resource using its own terminology. These resources are machine readable, but not machine understandable. Ontologies have a role in increasing this machine understanding, reducing the semantic heterogeneity between resources and thus promoting the flexible and reliable interoperation of bioinformatics resources. This paper describes a solution derived from the semantic web [a machine understandable world-wide web (WWW)], the ontology inference layer (OIL), as a solution for semantic bioinformatics resources. The nature of the heterogeneity problems are presented along with a description of how metadata from domain ontologies can be used to alleviate this problem. A companion paper in this issue gives an example of the development of a bio-ontology using OIL.