Interoperability Challenges Research Articles

An iterative and interdisciplinary categorisation process towards FAIRer digital resources for sensitive life-sciences data

For life science infrastructures, sensitive data generate an additional layer of complexity. Cross-domain categorisation and discovery of digital resources related to sensitive data presents major interoperability challenges. To support this FAIRification process, a toolbox demonstrator aiming at support for discovery of digital objects related to sensitive data (e.g., regulations, guidelines, best practice, tools) has been developed. The toolbox is based upon a categorisation system developed and harmonised across a cluster of 6 life science research infrastructures. Three different versions were built, tested by subsequent pilot studies, finally leading to a system with 7 main categories (sensitive data type, resource type, research field, data type, stage in data sharing life cycle, geographical scope, specific topics). 109 resources attached with the tags in pilot study 3 were used as the initial content for the toolbox demonstrator, a software tool allowing searching of digital objects linked to sensitive data with filtering based upon the categorisation system. Important next steps are a broad evaluation of the usability and user-friendliness of the toolbox, extension to more resources, broader adoption by different life-science communities, and a long-term vision for maintenance and sustainability.

Survey of Interoperability Challenges in the Internet of Vehicles

The Internet of Vehicles (IoV) is an active area for innovation and an essential tool in achieving smart cities through the integration of vehicles with the Internet of Things (IoT). IoV is a distributed network that aids in handling the data generated by vehicular sensors and vehicle-to-everything communication (V2X), thus enabling novel applications such as autonomous driving and platooning while increasing safety and energy efficiency. In IoV, the sensors and the interdependent devices relay critical information for the efficient implementation of real-time applications in the ecosystem. Despite all these advancements, a vital challenge is establishing smooth communication among interconnected devices, concretely, interoperability in the IoV—a deceptively simple notion that is not yet fully addressed to achieve a fully integrated ecosystem. This is mainly because the networked domains, such as home, grid, and health care, are developed in silos, operating independently with diverse processes and protocols. Hence, seamless exchange of information is yet to be achieved across the ecosystem, hindering the maximization of the full promise of IoV. In this paper, we provide an in-depth analysis of the present state of interoperability and comprehensively survey the challenges in IoV. We present a taxonomy of interoperability approaches, review solutions that prior work have proposed, and provide insights on how to address the current challenges. Finally, we identify open problems that persist and future directions for research.

Electronic Health Records at People's Hands Across Europe: The InteropEHRate Protocols.

Sharing of personal health data could facilitate and enhance the quality of care and the conduction of further research studies. However, these data are still underutilized due to legal, technical, and interoperability challenges, whereas the data subjects are not able to manage, interact, and decide on what to share, with whom, and for what purposes. This barrier obstacles continuity of care across in the European Union (EU), and neither healthcare providers nor data researchers nor the citizens are benefiting through efficient healthcare treatment and research. Despite several national-level EU studies and research activities, cross-border health data exchange and sharing is still a challenging task, which is addressed only under specific cases and scenarios. This manuscript presents the InteropEHRate research project along with its key innovations, aiming to offer Electronic Health Records (EHRs) at peoples' hands across the EU, via the exploitation of three (3) different protocol families, namely the Device-to-Device (D2D), Remote-to-Device (R2D), and Research Data Sharing (RDS) protocols. These protocols facilitate efficient, secure, privacy preserving, and General Data Protection Regulation (GDPR) compliant health data sharing across the EU, covering different real-world use cases.

Smart Grid Cyber Security Enhancement: Challenges and Solutions—A Review

The incorporation of communication technology with Smart Grid (SG) is proposed as an optimal solution to fulfill the requirements of the modern power system. A smart grid integrates multiple energy sources or microgrids and is supported by an extensive control and communication network using the Internet of Things (IoT) for a carbon-free, more reliable, and intelligent energy system. Along with many benefits, the system faces novel security challenges, data management, integration, and interoperability challenges. The advanced control and communication network in the smart grid is susceptible to cyber and cyber-physical threats. A lot of research has been done to improve the cyber security of the smart grid. This review aims to provide an overview of the types of cyber security threats present for smart grids with an insight into strategies to overcome the challenges. As the selection of techniques and technologies may vary according to the threats faced, therefore the adoption of researched methods is compared and discussed. As cyber-security is the greatest challenge in smart grid implementation, this review is beneficial during the planning and operation of smart grids for enhanced security.

Challenges of Digital Building Data Usage with a Focus on the Digital Documentation of Heritage Buildings—Results from an Online Survey

The AEC industries as well as the heritage sector are facing a number of issues that relate to the management of building digital data. Two of the most prominent ones are the interoperability of data and data longevity. In order to better understand the extent of these issues for the general AEC industry and heritage buildings sectors, an online survey was designed to help quantify them and reveal the opinions of professionals and academics in the field. The online survey highlighted a clear latency in BIM adoption in the heritage sector as only 51% of the heritage participants use BIM in their projects compared to 63% of AEC participants. The reasons for this were further explored in the participants’ comments, as most of the reasons revolved around the issues of BIM data interoperability and longevity, considering the complex and interdisciplinary nature of heritage projects. The survey responses highlighted that data longevity is a crucial challenge for the heritage sector in particular as the need for future re-accessibility of digital data is clear in the results, showing that more than 82% of the heritage participants need to re-access their data in the future. The results also showed the prevalence of BIM interoperability issues and highlighted that the heritage sector is more prone to interoperability issues compared to the general AEC industry as 67% of heritage BIM participants and 50% of AEC BIM participant have faced some issues of BIM interoperability. In total, 72% of the standardised BIM participants agreed that standardised BIM formats could be a promising solution to mitigate the interoperability challenges, while only 57% thought that standardised BIM formats are reliable in their current status. Moreover, the online survey explored the variation in the needs of different disciplinary groups including rates of BIM adoption, use of standardised BIM formats, and needs for access to different heritage buildings data categories. Participants also presented their views on what would be an ideal medium for long-term storage of heritage buildings digital documentation data for future access, with some views being sceptical concerning BIM in its current status. This paper presents the findings of this extensive online survey.

Blockchain-of-blockchains: An interoperable blockchain platform for ensuring IoT data integrity in smart city

We propose a hierarchical blockchain-based platform for ensuring the integrity of smart city Internet-of-Things (IoT) data and blockchain interoperability in this paper. The well-defined structural hierarchy of managing organizations in a smart city face several data management issues. The integration of emerging technologies, such as (IoT), has introduced more complexity to data maintenance in the smart city. At present, cloud-based information systems have become the norm for managing IoT data. Due to the centralized administrative control, the cloud-based information management is untrusted. Hence, it fails to guarantee the integrity of IoT data and traceability of operations to achieve transparency within the smart city organizations. Adoption of blockchain-based information systems can be viable solution to address these challenges. However, it introduces a new challenge of interoperability of transactions among different smart city organizations. In this paper, we introduce a decentralized hierarchy of blockchains, named Blockchain-of-Blockchains (BoBs), for ensuring data integrity and blockchain interoperability at the same time. We implement the proposed concept using Hyperledger Fabric and Ethermint as a proof-of-concept for evaluating the performance of the proposed concept.

The Challenge of Ethical Interoperability

Defense organizations are increasingly developing ethical principles to guide the design, development, and use of responsible AI, most notably for defense, security, and intelligence uses. While these principles have the potential to lead to more ethical and responsible uses of AI, they also create a novel issue that we term the challenge of ethical interoperability. In particular, we start with the observation that the frequent necessity for collaboration between defense organizations results in their possible need to use one another’s AI systems, either directly or indirectly. In such cases, the AI system presumably satisfies the originator organization’s ethical principles, but the adopting organization should only use it if it also satisfies their AI principles. One might naturally consider using the operating characteristics of the AI system to establish ethical interoperability, as those parallel the features used for technical interoperability. However, we argue that if the operating characteristics are sufficient to enable such assurance, then they will be too detailed to be disclosed. Instead, we propose a system of self-certification that provides adopting organizations with assurances that a system satisfies their ethical AI principles. We argue that our proposed framework properly aligns incentives to ensure ethical interoperability between defense organizations. Moreover, although this challenge is particularly salient for defense organizations, ethical interoperability must also be addressed in non-defense settings by organizations that have developed ethical AI principles.

A GEOSPATIAL KNOWLEDGE GRAPH PROTOTYPE FOR NATIONAL TOPOGRAPHIC MAPPING

Abstract. Knowledge graphs are a form of database representation and handling that show the potential to better meet the challenges of data interoperability, semi-automated information reasoning, and information retrieval. Geospatial knowledge graphs (GKG) have at their core specialized forms of applied ontology that provide coherent spatial context to a domain of information including non-spatial attributes. This paper discusses research toward the development of a prototype GKG based on national topographic databases of geospatial feature instances, attributes, properties, metadata, and annotations. The challenges are to capture and represent geographic semantics inherent in the source data, to align such graph models with standards where possible, to test logical computations, and to visualize the data using a cartographic user interface. Data integration from outside sources was tested through SPARQL and GeoSPARQL queries. Called the MapKB, the approaches applied in this prototype use a number of software components to build a system architecture aligned with those objectives and are composed entirely of free and open-source software. The system and ontology design were validated through reasoning and competency questions. Technical aspects of the prototype software succeeded, but customization was found to be needed for user-based design.

Towards a co-creation approach in the European Interoperability Framework

PurposeThe purpose of this paper is to propose an enhanced conceptual model for the integrated public service (IPS) functionality of the European interoperability framework (EIF). The enhanced model incorporates co-creation within the three stages of the IPS cycle. While co-creation can provide innovative routes to overcome interoperability challenges, how co-creation can be a part of the EIF has not been tackled before (Casiano Flores, et al., 2021).Design/methodology/approachA preferred Reporting Items for systematic reviews and meta-analyses scoping literature review was used to develop the model and identify decisive aspects of co-creation, service users and service providers. Next, a purposive snowball sampling of grey literature comprising primarily of official documentation produced by the European Union was then undertaken to further inform the central argument. Finally, the subsequent validation of the model and derived conclusions was undertaken both internally and externally by peers and experts.FindingsRelationships between key sets of actors during co-creation are bi-directional. Furthermore, different sets of actors are, in turn, service providers and service users depending on the service provided and the stage in the public service cycle under consideration. Understanding these bi-directional interrelationships can help improve public services provided by governmental actors through collaboration with users.Originality/valueMost public service delivery models see relationships between key stakeholders as unidirectional and one-dimensional. By contrast, this study proposes a shift in paradigm where IPS users are not passive actors and mere consumers of services but instead are key stakeholders actively participating in IPS provision.

Systematic Assessment of the Interoperability Requirements and Challenges of Secure Blockchain-Based Electronic Health Records

A peer-to-peer (P2P) decentralized information-sharing network is used to share data and maintain security, privacy, and integrity standards called blockchain. In this case, information sharing and updating require regular simplification. The presented systematic review mainly focuses on the interoperability of electronic health records (EHRs) using blockchain. Correspondingly, 18 blockchain-based solutions were selected to address the interoperability challenges of EHRs. The limitation of solutions includes reliability, privacy, integrity, sharing, and standards. This systematic review contains six phase’s research question, research phase, article selection, abstract-based keyword, data extraction, and progress tracking. Various Web resources such as Google Scholar, Web of Science, and IEEE are used to extract the relevant manuscripts. Primarily, 18 articles were selected to present the interoperable requirements of EHRs using blockchain, standards of blockchain-based EHRs, and solutions for interoperability of EHRs using blockchain. The conducted study explains the best available interoperable blockchain-based EHR standards, implementations, applications, and challenges.

Internet of Things data management: A systematic literature review, vision, and future trends

SummaryThe Internet of Things (IoT) is expected to connect devices with unique identifiers over a network to create an equilibrium system with high speeds and volumes of data while presenting an interoperability challenge. The IoT data management system is indispensable for attaining effective and efficient performance because IoT sensors generate and collect large amounts of data used to express large data sets. IoT data management has been analyzed from various perspectives in numerous studies. In this study, a Systematic Literature Review (SLR) method was used to investigate the various topics and key areas that have recently emerged in IoT data management. This study aims to classify and evaluate studies published between 2015 and 2021 in IoT data management. Therefore, the classification of studies includes five categories, data processing, data smartness application, data collection, data security, and data storage. Then, studies in each field are compared based on the proposed classification. Each study investigates novel findings, simulation/implementation, data set, application domain, experimental results, advantages, and disadvantages. In addition, the criteria for evaluating selected articles for each domain of IoT data management are examined. Big data accounts for the highest percentage of data processing fields in IoT data management, at 34%. In addition, fast data processing, distributed data, artificial intelligence data with 22%, and data uncertainty analysis account for 11% of the data processing field. Finally, studies highlight the challenges of IoT data management and its future directions.

Interoperability of Infrastructure and Transportation Information Models: A Public Transport Case Study

The duplication of semantic data modelled in different disciplines poses interoperability challenges. Information models that benefit from the application of standards that enable data reusability and prevent redundancy and misuse should be compatible, particularly when different systems are used in the same domain-specific area, as in the case of public transportation. Transportation information models, leading and providing reliable and robust public transport services, can nowadays be enriched with information found in building information models devoted to transportation infrastructure. Therefore, in the present paper, a mapping between the standards and technical specifications that support each modelling approach is explored, analysed, and aligned to maximise the best out of the current common practices used. The information from the Industry Foundation Classes IFC specification-based models complements the conceptual and physical transportation models, where Transmodel and NeTEx are well-established, with accurate (as-built) detailed characteristics of the transportation infrastructure (stop places, quays, entrances, access spaces and equipment as ramps, staircases, and escalators). The extraction of topological information stored in IFC models allows for navigation-network extraction, information about spaces, and passages between spaces. A specific public transport case study focused on a train station is detailed to better corroborate and illustrate the advantages and uses of compatible and complementing modelling approaches. As building-information-modelling awareness and use is growing, the validated mapping approach can benefit from the future application of automation procedures.

A literature review on the analysis of symptom-based clinical pathways: Time for a different approach?

Breathlessness is a common clinical presentation, accounting for a quarter of all emergency hospital attendances. As a complex undifferentiated symptom, it may be caused by dysfunction in multiple body systems. Electronic health records are rich with activity data to inform clinical pathways from undifferentiated breathlessness to specific disease diagnoses. These data may be amenable to process mining, a computational technique that uses event logs to identify common patterns of activity. We reviewed use of process mining and related techniques to understand clinical pathways for patients with breathlessness. We searched the literature from two perspectives: studies of clinical pathways for breathlessness as a symptom, and those focussed on pathways for respiratory and cardiovascular diseases that are commonly associated with breathlessness. The primary search included PubMed, IEEE Xplore and ACM Digital Library. We included studies if breathlessness or a relevant disease was present in combination with a process mining concept. We excluded non-English publications, and those focussed on biomarkers, investigations, prognosis, or disease progression rather than symptoms. Eligible articles were screened before full-text review. Of 1,400 identified studies, 1,332 studies were excluded through screening and removal of duplicates. Following full-text review of 68 studies, 13 were included in qualitative synthesis, of which two (15%) were symptom and 11 (85%) disease focused. While studies reported highly varied methodologies, only one included true process mining, using multiple techniques to explore Emergency Department clinical pathways. Most included studies trained and internally validated within single-centre datasets, limiting evidence for wider generalisability. Our review has highlighted a lack of clinical pathway analyses for breathlessness as a symptom, compared to disease-focussed approaches. Process mining has potential application in this area, but has been under-utilised in part due to data interoperability challenges. There is an unmet research need for larger, prospective multicentre studies of patient pathways following presentation with undifferentiated breathlessness.

User-Centric BIM-Based Framework for HVAC Root-Cause Detection

In the building operation phase, the Heating, Ventilation, and Air-Conditioning (HVAC) equipment are the main contributors to excessive energy consumption unless proper design and maintenance is carried out. Moreover, HVAC problems might have an impact on occupants’ discomfort in thermal comfort. Hence, the identification of the root cause of HVAC problems is imperative for facility managers to plan preventive and corrective maintenance actions. However, due to the complex interaction between various equipment and the lack of data integration among Facility Management (FM) systems, they fail to provide necessary information to identify the root cause of HVAC problems. Building Information Modelling (BIM) is a potential solution for maintenance activities to address the challenges of information reliability and interoperability. Therefore, this paper presents a novel conceptual model and user-centric framework to determine the causes of HVAC problems implemented in BIM for its visualization. CMMS and BMS data were integrated into BIM and utilized by the framework to analyze the root cause of HVAC problems. A case study in a university building was used to demonstrate the applicability of the approach. This framework assists the FM team to determine the most probable cause of an HVAC problem, reducing the time to detect equipment faults, and providing potential actions to solve them.

Enhancing global health security in Thailand: Strengths and challenges of initiating a One Health approach to avian influenza surveillance

Infectious disease surveillance systems support early warning, promote preparedness, and inform public health response. Pathogens that have human, animal, and environmental reservoirs should be monitored through systems that incorporate a One Health approach. In 2016, Thailand's federal government piloted an avian influenza (AI) surveillance system that integrates stakeholders from human, animal, and environmental sectors, at the central level and in four provinces to monitor influenza A viruses within human, waterfowl, and poultry populations. This research aims to describe and evaluate Thailand's piloted AI surveillance system to inform strategies for strengthening and building surveillance systems relevant to One Health. We assessed this surveillance system using the United States Centers for Disease Control and Prevention's (U.S. CDC) “Guidelines for Evaluating Public Health Surveillance Systems” and added three novel metrics: transparency, interoperability, and security. In-depth key informant interviews were conducted with representatives among six Thai federal agencies and departments, the One Health coordinating unit, a corporate poultry producer, and the Thai Ministry of Public Health-U.S. CDC Collaborating Unit. Thailand's AI surveillance system demonstrated strengths in acceptability, simplicity, representativeness, and flexibility, and exhibited challenges in data quality, stability, security, interoperability, and transparency. System efforts may be strengthened through increasing laboratory integration, improving pathogen detection capabilities, implementing interoperable systems, and incorporating sustainable capacity building mechanisms. This innovative piloted surveillance system provides a strategic framework that can be used to develop, integrate, and bolster One Health surveillance approaches to combat emerging global pathogen threats and enhance global health security.

Developing a Dietary Lifestyle Ontology to Improve the Interoperability of Dietary Data: Proof-of-Concept Study

BackgroundDietary habits offer crucial information on one's health and form a considerable part of the patient-generated health data. Dietary data are collected through various channels and formats; thus, interoperability is a significant challenge to reusing this type of data. The vast scope of dietary concepts and the colloquial expression style add difficulty to standardizing the data. The interoperability issues of dietary data can be addressed through Common Data Elements with metadata annotation to some extent. However, making culture-specific dietary habits and questionnaire-based dietary assessment data interoperable still requires substantial efforts.ObjectiveThe main goal of this study was to address the interoperability challenge of questionnaire-based dietary data from different cultural backgrounds by combining ontological curation and metadata annotation of dietary concepts. Specifically, this study aimed to develop a Dietary Lifestyle Ontology (DILON) and demonstrate the improved interoperability of questionnaire-based dietary data by annotating its main semantics with DILON.MethodsBy analyzing 1158 dietary assessment data elements (367 in Korean and 791 in English), 515 dietary concepts were extracted and used to construct DILON. To demonstrate the utility of DILON in addressing the interoperability challenges of questionnaire-based multicultural dietary data, we developed 10 competency questions that asked to identify data elements sharing the same dietary topics and assessment properties. We instantiated 68 data elements on dietary habits selected from Korean and English questionnaires and annotated them with DILON to answer the competency questions. We translated the competency questions into Semantic Query-Enhanced Web Rule Language and reviewed the query results for accuracy.ResultsDILON was built with 262 concept classes and validated with ontology validation tools. A small overlap (72 concepts) in the concepts extracted from the questionnaires in 2 languages indicates that we need to pay closer attention to representing culture-specific dietary concepts. The Semantic Query-Enhanced Web Rule Language queries reflecting the 10 competency questions yielded correct results.ConclusionsEnsuring the interoperability of dietary lifestyle data is a demanding task due to its vast scope and variations in expression. This study demonstrated that we could improve the interoperability of dietary data generated in different cultural contexts and expressed in various styles by annotating their core semantics with DILON.

BIM and Asset Management (AM) Interoperability Towards the Adoption of Digital Twins

Digital Twin (DT) is seen as the new shift paradigm for digital transformation in the post-pandemic-built environment sector. Learning from the implementation of Building Information Modelling (BIM) for Asset Management (AM), there are recurring themes that the interoperability challenge is the key barrier to firstly overcome. The absence of a critical overview of issues and research related to BIM-AM interoperability, is hindering the achievement of sustainable and effective integration between the two systems. Therefore, the aim of this paper is to review and analyse the trends and overview of the BIM-AM interoperability publications, identifies and classifies the major research topics on BIM-AM interoperability and finally, proposes future research interoperability directions for DT initiative adoption. To achieve the research aim, a systematic review of the work done to achieve interoperability using a wide range of digital technologies published between 2010 and 2020 related to the interoperability challenges between BIM, and AM and real-time data sources was conducted.

DIGITAL BUILDING DATA LONGEVITY AND INTEROPERABILITY CHALLENGES IN THE DOCUMENTATION OF HERITAGE BUILDINGS

Abstract. One of the major motivations behind the introduction of BIM (Building Information Modelling) was to mitigate the challenges of interoperability and interdisciplinary interaction between different stakeholders, this is particularly critical in the heritage buildings sector that involves more diverse stakeholders in a wide range of disciplines compared to a standard construction project. A crucial concern in dealing with heritage buildings is the longevity and safeguarding of the digital documentation data that is usually required to be kept as a digital record for the future. This is especially challenging in the digital medium due to the diversity of the software tools, and the fast-advancing and changing software market.In order to assess the needs and challenges facing the heritage buildings sector in terms of data longevity and interoperability and to assess the interdisciplinary interaction needs of relevant disciplines, the authors designed an online survey targeting professionals and academics in the heritage buildings sector and the wider AEC industries. This paper presents the preliminary findings of this survey.

EASE-DGGS: a hybrid discrete global grid system for Earth sciences

ABSTRACT Although we live in an era of unprecedented quantities and access to data, deriving actionable information from raw data is a hard problem. Earth observation systems (EOS) have experienced rapid growth and uptake in recent decades, and the rate at which we obtain remotely sensed images is increasing. While significant effort and attention has been devoted to designing systems that deliver analytics ready imagery faster, less attention has been devoted to developing analytical frameworks that enable EOS to be seamlessly integrated with other data for quantitative analysis. Discrete global grid systems (DGGS) have been proposed as one potential solution that addresses the challenge of geospatial data integration and interoperability. Here, we propose the systematic extension of EASE-Grid in order to provide DGGS-like characteristics for EOS data sets. We describe the extensions as well as present implementation as an application programming interface (API), which forms part of the University of Minnesota’s GEMS (Genetic x Environment x Management x Socioeconomic) Informatics Center’s API portfolio.

MDAnalysis 2.0 and beyond: fast and interoperable, community driven simulation analysis

Continued improvements in computational power have enabled the running of molecular dynamics simulations of increasingly complex nature, necessitating a corresponding evolution of analysis workflows to handle and extract features from the simulation data. MDAnalysis (https://www.mdanalysis.org) is a free open-source Python library for molecular simulations analysis, with support for over 40 file formats covering most popular simulation packages. It allows users to read, write and manipulate trajectories or individual structures, offers a variety of common analysis methods such as RMSD and hydrogen bonding, and is easily extensible to match individual needs. Here, we present the core aspects of MDAnalysis and how it can be leveraged to explore simulation data. We focus on recent and ongoing improvements to handle the evolving landscape of molecular simulations, including larger datasets and more diverse analysis needs. In particular, we recently introduced a “converter” framework to enable direct conversion of data between MDAnalysis and other popular simulation and analysis packages (such as ParmEd and RDKit), without the need for intermediate files - addressing the common challenge of interoperability. We will also present our upcoming “MDAKit” system, which will simplify/streamline the creation and maintenance of packages built with MDAnalysis to empower scientists to develop features, encouraging new contributions and broadening the scope of MDAnalysis. MDAKits may include analysis and trajectory manipulation, such as our new tools for membrane curvature and solvation analysis.