Interoperability Challenges Research Articles

Interopérabilité et automatisme dans les etudes du Bâtiment

Les professionnels constatent des difficultés dans l’exploitation de la norme ISO dite « IFC » d’échange de données du Bâtiment, ainsi que dans la maquette numérique des projets (BIM)telle qu’elle existe aujourd’hui. Deux disciplines qui selon les auteurs sont devenues inséparables dans la conception des ouvrages. Ajouter de l’information numérique dans cette maquette ne résout pas l’essentiel attendu : son partage et sa synthèse2 entre les métiers. Pour relever le défi d’une veritable interopérabilité dans les échanges de données entre métiers, qui supposent des procédures automatisées, les auteurs imaginent un outil logiciel.

A semantic interoperability framework for distributed electronic health record based on fuzzy ontology

To achieve an efficient healthcare process; the professionals and doctors need to access the complete data about their patients in the suitable time. In the face of that issue; healthcare semantic interoperability is still a huge problem without solving. In this paper, a unified semantic interoperability framework for distributed EHR based on fuzzy ontology is proposed. The lowest layer stores the EHRs heterogeneous data with different models. In the middle layer, the local ontologies are mapped to a global crisp one. The global reference ontology combines and integrates all local ontologies and therefore describes all data. In the user interface layer, any linguistic or semantic queries can be done by dealing with only the global reference fuzzy ontology. We expect that our framework will handle the current EHR semantic interoperability challenges, reduce the cost of the integration process, and get a higher acceptance and accuracy rate than previous studies.

Application Programming Interfaces in Health Care: Findings from a Current-State Sociotechnical Assessment.

Objective Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current state of API use for data access and exchange in health care: (1) API use cases and standards; (2) challenges and facilitators for read and write capabilities; and (3) outlook for development of write capabilities. Methods We employed four methods: (1) literature review; (2) expert interviews with 13 API stakeholders; (3) review of electronic health record (EHR) app galleries; and (4) a technical expert panel. We used an eight-dimension sociotechnical model to organize our findings. Results The API ecosystem is complicated and cuts across five of the eight sociotechnical model dimensions: (1) app marketplaces support a range of use cases, the majority of which target providers' needs, with far fewer supporting patient access to data; (2) current focus on read APIs with limited use of write APIs; (3) where standards are used, they are largely Fast Healthcare Interoperability Resources (FHIR); (4) FHIR-based APIs support exchange of electronic health information within the common clinical data set; and (5) validating external data and data sources for clinical decision making creates challenges to provider workflows. Conclusion While the use of APIs in health care is increasing rapidly, it is still in the pilot stages. We identified five key issues with implications for the continued advancement of API use: (1) a robust normative FHIR standard; (2) expansion of the common clinical data set to other data elements; (3) enhanced support for write implementation; (4) data provenance rules; and (5) data governance rules. Thus, while APIs are being touted as a solution to interoperability challenges, they remain an emerging technology that is only one piece of a multipronged approach to data access and use.

The combined use of BIM, IR thermography and HFS for energy modelling of existing buildings and minimising heat gain through the building envelope: a case-study from a UAE building

ABSTRACT Climate change has driven energy conservation into buildings, pressuring engineers into developing newer energy efficient buildings and effectively retrofitting the older ones. This research presents a practical method of creating an energy model of a modern office building using a Building Information Modelling (BIM) – Infra-Red Thermography (IRT) – Heat Flux sensors (HFS) framework that ensures a high level of accuracy with relative ease. The energy model is created with little input of the HVAC system, simulating real-life lack-of-information scenarios, and subsequently verified with consumption data extracted from the building’s own energy metre and the district’s chiller plant it’s connected to. The calibrated model is then used to investigate various passive heat-gain reduction measures through the building envelope such as the effect of the building’s orientation, shading, insulation levels, and window performance. Limitations of conserving energy through the building envelope were highlighted through the law of diminishing returns and the SHGC was pointed out to be the single most effective thermophysical window property in conserving energy. Numerically, the replacement of the windows saved 1.6% compared to the total 2.77% of energy saved. The study focuses on the climate of the United Arab Emirates and furthermore evaluates some BIM interoperability challenges.

Improving data sharing between acute hospitals in England: an overview of health record system distribution and retrospective observational analysis of inter-hospital transitions of care

ObjectivesTo determine the frequency of use and spatial distribution of health record systems in the English National Health Service (NHS). To quantify transitions of care between acute hospital trusts and...

A data management workflow of biodiversity data from the field to data users.

PremiseHeterogeneity of biodiversity data from the collections, research, and management communities presents challenges for data findability, accessibility, interoperability, and reusability. Workflows designed with data collection, standards, dissemination, and reuse in mind will generate better information across geopolitical, administrative, and institutional boundaries. Here, we present our data workflow as a case study of how we collected, shared, and used data from multiple sources.MethodsIn 2012, we initiated the collection of biodiversity data relating to Michigan prairie fens, including data on plant communities and the federally endangered Poweshiek skipperling (Oarisma poweshiek).ResultsOver 23,000 occurrence records were compiled in a database following Darwin Core standards. The records were linked with media and biological, chemical, and geometric measurements. We published the data as Global Biodiversity Information Facility data sets and in Symbiota SEINet portals.DiscussionWe highlight data collection techniques that optimized transcription time, including the use of predetermined and controlled vocabulary, Darwin Core terms, and data dictionaries. The validity and longevity of our data were supported by voucher specimens, metadata with measurement records, and published manuscripts detailing methods and data sets. Key to our data dissemination was cooperation among partners and the utilization of dynamic tools. To increase data interoperability, we need flexible and customizable data collection templates, coding, and enhanced communication among communities using biodiversity data.

An Empirical Evaluation of Data Interoperability—A Case of the Disaster Management Sector in Uganda

One of the grand challenges of disaster management is for stakeholders to be able to discover, access, integrate and analyze task-appropriate data together with their associated algorithms and work-flows. Even with a growing number of initiatives to publish data in the disaster management sector using open principles, integration and reuse are still difficult due to existing interoperability barriers within datasets. Several frameworks for assessing data interoperability exist but do not generate best practice solutions to existing barriers based on the assessment they use. In this study, we assess interoperability for datasets in the disaster management sector in Uganda and identify generic solutions to interoperability challenges in the context of disaster management. Semi-structured interviews and focus group discussions were used to collect qualitative data from sector stakeholders in Uganda. Data interoperability was measured to provide an understanding of interoperability in the sector. Interoperability maturity is measured using qualitative methods, while data compatibility metrics are computed from identifiers in the RDF-triple model. Results indicate high syntactic and technical interoperability maturity for data in the sector. On the contrary, there exists considerable semantic and legal interoperability barriers that hinder data integration and reuse in the sector. A mapping of the interoperability challenges in the disaster management sector to solutions reveals a potential to reuse established patterns for managing data interoperability. These include; the federated pattern, linked data patterns, broadcast pattern, rights and policy harmonization patterns, dissemination and awareness pattern, ontology design patterns among others. Thus a systematic approach to combining patterns is critical to managing data interoperability barriers among actors in the disaster management ecosystem.

Interoperability – Technical or economic challenge?

Abstract Interoperability in healthcare is a long-standing and addressed phenomenon. In the literature, it is discussed as both the cause of an insufficiently perceived digitalization and in context with an inadequate IT-based integration in healthcare. In particular, technical and organizational aspects are highlighted from the perspective of the different involved actors to achieve sufficient interoperability. Depending on the individual case, various established international industry standards in healthcare (e. g. DICOM, HL7 or FHIR) promise simple adaptation and various application advantages. In addition to the technical view, this article assumes economic challenges as the main causes for the lack of interoperability not discussed in the forefront. The economic challenges were mentioned and sparingly discussed in few cases in the literature. This article aims to fill this gap by offering a first characterization of identified and discussed economic challenges in the literature with respect to the lack of interoperability in healthcare. Based on a systematic literature search, 14 of the original 330 articles can be identified as relevant, allowing a more economic perspective on interoperability. In this context, different economic effects will be described; this includes cost-benefit decisions by individual stakeholders under different kinds of uncertainty or balancing of known individual costs for interoperability against uncertain and skewed distributed benefits within an ecosystem. Furthermore, more sophisticated cost-benefit approaches regarding interoperability challenges can be identified, including cost-benefit ratios that shift over time, or lock-in effects resulting from CRM-motivated measures that turn (non)interoperability decisions into cost considerations for single actors. Also, self-reinforcing effects through path dependencies, including direct and indirect network effects, have an impact on single and linked interoperability decisions.

A traceability proposal for industry 4.0

This research examines traceability and its model in industry 4.0. Hence, this paper introduces the main design features of this model. The fourth industrial revolution is an environment that combines manufacturing with the Internet of Things and cyber-physical Systems. In such an environment, various sources (i.e., smart products, intelligent agents, and sensors) generate an increasing amount of data, which is essential for effective traceability. However, due to these heterogeneous sources, a traceability system should face the interoperability challenge and overcome the data integration issue. Moreover, the incorporation of this information in a traceability tool is motivated by the requirement to have access to a maximum amount of accurate product data. Thus, this article proposes to take advantage of industry 4.0 information. Also, the present study advocates that traceability should not only allow trace and track but also ensure product safety and quality. Accordingly, the proposal includes an intelligent traceability description, an ontology-based modeling, and a cloud-based application. This system provides users with a common knowledge base to access and represent data. Also, this model enables users to share and query remotely the traceable information using the cloud.

ChainSDI: A Software-Defined Infrastructure for Regulation-Compliant Home-Based Healthcare Services Secured by Blockchains

Healthcare networking and computing infrastructure is rapidly changing from closed environments to open environments that incorporate ubiquitous medical devices and novel application scenarios. For example, home-based healthcare involves the collection and analysis of data from pervasive sensors (often in real time) to guide therapy or to perform medical interventions. In this article, we address the challenges of data interoperability and regulatory compliance when designing and deploying healthcare applications in a heterogeneous home-edge-cloud environment. We propose the ChainSDI framework that leverages the blockchain technique along with abundant edge computing resources to manage secure data sharing and computing on sensitive patient data. We implement programmable ChainSDI application programming interfaces to facilitate the specification of home-based healthcare services running on a software-defined infrastructure (SDI). This article is a collaboration between computer scientists, medical researchers, healthcare IT professionals as well as healthcare providers with the goal of increasing the availability of SDI infrastructures while meeting the performance and regulatory requirements of healthcare applications. Our prototype demonstrates the feasibility of the framework and serves as a testbed for novel experimental studies in the context of emerging healthcare applications.

Internet of Things Architectures, Technologies, Applications, Challenges, and Future Directions for Enhanced Living Environments and Healthcare Systems: A Review

Internet of Things (IoT) is an evolution of the Internet and has been gaining increased attention from researchers in both academic and industrial environments. Successive technological enhancements make the development of intelligent systems with a high capacity for communication and data collection possible, providing several opportunities for numerous IoT applications, particularly healthcare systems. Despite all the advantages, there are still several open issues that represent the main challenges for IoT, e.g., accessibility, portability, interoperability, information security, and privacy. IoT provides important characteristics to healthcare systems, such as availability, mobility, and scalability, that offer an architectural basis for numerous high technological healthcare applications, such as real-time patient monitoring, environmental and indoor quality monitoring, and ubiquitous and pervasive information access that benefits health professionals and patients. The constant scientific innovations make it possible to develop IoT devices through countless services for sensing, data fusing, and logging capabilities that lead to several advancements for enhanced living environments (ELEs). This paper reviews the current state of the art on IoT architectures for ELEs and healthcare systems, with a focus on the technologies, applications, challenges, opportunities, open-source platforms, and operating systems. Furthermore, this document synthesizes the existing body of knowledge and identifies common threads and gaps that open up new significant and challenging future research directions.

Interoperable Health Care System Using Blockchain Technology

The need for integration is not new but it existed since applications moved from central processors to distributed systems and networks. This need has emerged as disparate Information Systems (IS) that automate business processes which run on different computer platforms and have been based on a diversity of standards, operating systems and computer languages. In healthcare, interoperability is the important because of different information systems (IS) to communicate, interchange data, and use of the exchanged information among systems. Blockchain technology can address the interoperability challenges in healthcare systems; it can help healthcare providers, healthcare stakeholders and researchers to share health data in secure way. In this paper, we have proposed a Blockchain based healthcare systems which can address the interoperability issues in healthcare in secure in transparent way.

New Blockchain-Based Architecture for Service Interoperations in Internet of Things

Internet of Things (IoT) is able to integrate the computation and physical processes as services in the social world. The number of services at the edge of IoT is rising rapidly due to the prevalent uses of smart devices and cyber-physical systems (CPSs). To explore the promising applications of IoT services, one of the challenges is to enable the interoperability of the services in a decentralized environment. The blockchain technology (BCT) has been proven as a promising solution to establish the trust of data and call for executions; theoretically, it can be used to support the interoperability of services. BCT verifies data or a process and stores it as a transaction in a distributed ledger. Similar to the topology to IoT, applying BCT at the edges of the network exhibits the distributed characteristic. However, currently, BCT is still facing the challenges for interoperability due to a number of factors such as consensus protocols, block sizes, and interval of blocks. Prominent protocols such as proof-of-work (PoW) may cause excessive delays in finality settlement. One promising protocol Practical Byzantine Fault Tolerant offers a fast finality settlement and uses hyperledger to support the scalability; however, the trust might also be a concern if the validators are chosen improperly. This paper discusses the interoperability of IoT services and the challenges and proposes an architecture solution by integrating BCT, service-oriented architecture (SoA), and enablers of key performance indicators (KPIs) and service selections. The proposed architecture aims to solve both interoperability and trust issues for IoT services. The feasibility of the proposed method is validated by the examples of smart contract implementations.

Interoperability Conflicts in Linked Open Statistical Data

An important part of Open Data is of a statistical nature and describes economic and social indicators monitoring population size, inflation, trade, and employment. Combining and analyzing Open Data from multiple datasets and sources enable the performance of advanced data analytics scenarios that could result in valuable services and data products. However, it is still difficult to discover and combine Open Statistical Data that reside in different data portals. Although Linked Open Statistical Data (LOSD) provide standards and approaches to facilitate combining statistics on the Web, various interoperability challenges still exist. In this paper, we propose an Interoperability Framework for LOSD, comprising definitions of LOSD interoperability conflicts as well as modelling practices currently used by six official open government data portals. Towards this end, we combine a top-down approach that studies interoperability conflicts in the literature with a bottom-up approach that studies the modelling practices of data portals. We define two types of LOSD schema-level conflicts, namely naming conflicts and structural conflicts. Naming conflicts result from using different URIs. Structural conflicts result from different practices of modelling the structure of data cubes. Only two out of the 19 conflicts are currently resolved and 11 can be resolved according to literature.

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs.

New Automated BIM Object Classification Method to Support BIM Interoperability

AbstractIndustry Foundation Classes (IFC) is widely accepted as the future of building information modeling (BIM) to take on the challenge of BIM interoperability and enable its support of various ...

Topological semantics for lumped parameter systems modeling

Behaviors of many engineering systems are described by lumped parameter models that encapsulate the spatially distributed nature of the system into networks of lumped elements; the dynamics of such a network is governed by a system of ordinary differential and algebraic equations. Languages and simulation tools for modeling such systems differ in syntax, informal semantics, and in the methods by which such systems of equations are generated and simulated, leading to numerous interoperability challenges. Logical extensions of SysML aim specifically at unifying a subset of the underlying concepts in such languages.We propose to unify semantics of all such systems using standard notions from algebraic topology. In particular, Tonti diagrams classify all physical theories in terms of physical laws (topological and constitutive) defined over a pair of dual cochain complexes and may be used to describe different types of lumped parameter systems. We show that all possible methods for generating the corresponding state equations within each physical domain correspond to paths over Tonti diagrams. We further propose a generalization of Tonti diagram that captures the behavior and supports canonical generation of state equations for multi-domain lumped parameter systems.The unified semantics provides a basis for greater interoperability in systems modeling, supporting automated translation, integration, reuse, and numerical simulation of models created in different authoring systems and applications. Notably, the proposed algebraic topological semantics is also compatible with spatially and temporally distributed models that are at the core of modern CAD and CAE systems.

Opportunities and challenges for GeoBIM in Europe: developing a building permits use-case to raise awareness and examine technical interoperability challenges

ABSTRACTThe integration of geoinformation with BIM (GeoBIM) is critical to underpin solutions to many city-related challenges. However, to achieve an effective integration it is necessary to consider not only data and technical options but also current practice and users’ needs. This paper describes work carried out within the EuroSDR-GeoBIM project to address this challenge. After investigating potential uses for GeoBIM and existing challenges, we address a planning permits for buildings use case, to help bridging the gap between theory and practice. The resultshighlights a high-level harmonised workflow envisaging the use of GeoBIM information for automating the planning permits process.

A Hybrid Scheme for an Interoperable Identity Federation System Based on Attribute Aggregation Method

Several countries have invested in building their identity management systems to equip citizens with infrastructures and tools to benefit from e-services. However, current systems still lack the interoperability requirement, which is the core issue that could lower the wide benefits of having an identity management system. In fact, in the existing systems, the user is allowed to choose only one partial identity from an identity provider (IdP) during a single session with a service provider (SP). However, in some scenarios, an SP needs to retrieve information about user’s identities managed by multiple IdPs. The potential method to tackle these shortcomings is attribute aggregation from multiple identity providers. A number of initiatives and projects on attribute aggregation have been explored. Nevertheless, these constructions do not fulfill some identity management requirements. This paper describes a new flexible model that aims to provide the necessary mechanisms to ensure attribute aggregation in order to meet the interoperability challenges of current identity management systems. The proposed scheme is a scalable solution, based on identity federation technologies, that introduces a new IdP called an account linking provider (ALP). The purpose of this ALP is to link together different accounts, holding end users’ attributes, whenever more than one source of data is needed to grant access to the requested web resource in a single session. Furthermore, the proposed identity federation system is based on a streamlined, cost-effective, and interoperable architecture, which makes this model suitable for large-scale identity federation environments.

Incorporating Social Determinants of Health in Electronic Health Records: Qualitative Study of Current Practices Among Top Vendors.

BackgroundSocial determinants of health (SDH) are increasingly seen as important to understanding patient health and identifying appropriate interventions to improve health outcomes in what is a complex interplay between health system-, community-, and individual-level factors.ObjectiveThe objective of the paper was to investigate the development of electronic health record (EHR) software products that allow health care providers to identify and address patients’ SDH in health care settings.MethodsWe conducted interviews with six EHR vendors with large market shares in both ambulatory and inpatient settings. We conducted thematic analysis of the interviews to (1) identify their motivations to develop such software products, (2) describe their products and uses, and (3) identify facilitators and challenges to collection and use of SDH data—through their products or otherwise—either at the point of care or in population health interventions.ResultsOur findings indicate that vendor systems and their functionalities are influenced by client demand and initiative, federal initiatives, and the vendors’ strategic vision about opportunities in the health care system. Among the small sample of vendors with large market shares, SDH is a new area for growth, and the vendors range in the number and sophistication of their SDH-related products. To enable better data analytics, population health management, and interoperability of SDH data, vendors recognized the need for more standardization of SDH performance measures across various federal and state programs, better mapping of SDH measures to multiple types of codes, and development of more codes for all SDH measures of interest.ConclusionsVendors indicate they are actively developing products to facilitate the collection and use of SDH data for their clients and are seeking solutions to data standardization and interoperability challenges through internal product decisions and collaboration with policymakers. Due to a lack of policy standards around SDH data, product-specific decisions may end up being de facto policies given the market shares of particular vendors. However, commercial vendors appear ready to collaboratively discuss policy solutions such as standards or guidelines with each other, health care systems, and government agencies in order to further promote integration of SDH data into the standard of care for all health systems.