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In response to the practical demands for data sharing and exchange in the field of rack railway systems engineering, as well as to address the gaps in the rack railway domain within the framework of the IFC4 standard, we extend and define the rack railway domain through entity extension and custom attribute sets. By utilizing the ongoing construction of the Dujiangyan to Mount Siguniang Railway as a case study, we validate the utility of this IFC extension and modeling approach. Leveraging IfcOpenShell, we incorporate the extended data content into the generated IFC file. We present a process for extension tailored to the characteristics of rack railway engineering. This study aims to provide broader information support for the digital construction of track structures in the design phase of rack railway engineering and to facilitate more efficient data exchange and sharing. [ABSTRACT FROM AUTHOR]

Effective data exchange holds the potential to bridge information gaps between organizations, creating essential prerequisites for enhanced collaboration. However, in cross-organizational database systems, ensuring strong consistency is often challenging. Inconsistent query results may be returned from different databases if data records are not timely synchronized, degrading mutual trust and collaboration efficiency among organizations. To address this issue, a novel cross-organizational data exchange approach is proposed. Specifically, consortium blockchain is leveraged as a Write-Ahead Log, enabling different organizations to trace relevant requests failed to be executed in real-time, thereby promptly providing consistent query results for users. Detailed settings on protocol level are designed for the blockchain platform to facilitate data exchange regulation, including data structures, consensus algorithms and an access control mechanism. Extensive simulation experiments are conducted to evaluate the performance of the proposed approach and investigate the impact of different parameters on data consistency and system availability. [ABSTRACT FROM AUTHOR]

Abstract In response to the practical demands for data sharing and exchange in the field of rack railway systems engineering, as well as to address the gaps in the rack railway domain within the framework of the IFC4 standard, we extend and define the rack railway domain through entity extension and custom attribute sets. By utilizing the ongoing construction of the Dujiangyan to Mount Siguniang Railway as a case study, we validate the utility of this IFC extension and modeling approach. Leveraging IfcOpenShell, we incorporate the extended data content into the generated IFC file. We present a process for extension tailored to the characteristics of rack railway engineering. This study aims to provide broader information support for the digital construction of track structures in the design phase of rack railway engineering and to facilitate more efficient data exchange and sharing.

In order to meet the data storage and access needs of coal mine personnel precise positioning system based on new positioning technologies such as UWB, the data structure, sampling frequency, data volume and storage space occupied by the personnel precise positioning system are analyzed, and the main features for system data generation and use are summarized, a hybrid data storage architecture based on Redis, MySQL and files to respectively store hot data, warm data and cold data is proposed, and the key design of Redis, MySQL, file storage, data encryption and data query method based on Web API data interaction service are described in detail. By using simulated data testing, it was verified that the storage solution has high data access efficiency, can meet the needs of data storage and business function data query.

Abstract Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap‐derived Big Data are becoming increasingly solvable with the help of scalable cyber‐infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media‐based and event‐based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in‐depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard.

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a 'data train' and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data. [ABSTRACT FROM AUTHOR]

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap‐derived Big Data are becoming increasingly solvable with the help of scalable cyber‐infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, "Camera Trap Metadata Standard" (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media‐based and event‐based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in‐depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard. [ABSTRACT FROM AUTHOR]

In the context of the digital evolution of the logistics industry, the interconnection of logistics information systems and associated data have become an obstacle of business collaboration among various stakeholders. A critical challenge in this domain is ensuring controllable access to logistics business data, given the industry's current state characterized by independence, autonomy, disconnection, and heterogeneity, alongside the non-negotiable requirement for data privacy. We propose a novel model of trusted data access control based on of logistics business collaboration semantics. This approach incorporates semantic inference technologies into attribute-based access control mechanisms, thereby enabling the streamlined formulation of access control policies and facilitating unified authorization and control. Moreover, the method addresses the issue of access control policy management and maintenance at the semantic level. The proposed solution can pave the way for enhanced business collaboration between business entities, and further enable the building of a data exchange service platform within the logistics industry. [ABSTRACT FROM AUTHOR]

Purpose: Data governance frameworks have typically been discussed within the confines of an organization, with less focus on inter-organizational contexts. However, due to factors like the rise of electronic government applications and the growth of inter-organizational collaboration in competitive markets, data exchange among organizations is on the rise. This current research aims to address this gap by proposing a data governance framework for data exchange centers. Given the continuous growth of e-government applications and interactions, along with the significant role and value of data within them, implementing this framework can enhance the accuracy and efficiency of data and information exchange. Method: This research is qualitative and its method is grounded theory. Initially, the fundamentals of the research were examined. This involved reviewing both scientific and academic research as well as frameworks provided by technical and specialized associations. By exploring the basics and background of the research, foundational knowledge was acquired for subsequent steps. Subsequently, through conducting semi-structured interviews with experts and documenting them, over 400 phrases were collected, and categorized into 100 concepts. These were then analyzed using open coding (resulting in 44 subcategories), theoretical coding (leading to 15 categories), and the development of a theoretical framework. The data was sourced from national data exchange centers. Given the qualitative nature of the study, methods such as participant review, triangulation, and the Delphi technique were employed to ensure the validity and reliability of the findings. Findings: The data governance framework in the data exchange center comprises 15 components, categorized into "main components of governance, "main components in the business of data exchange centers, and "supporting components in the business of data exchange centers. Some of these components include "roles, responsibilities, and rights, "standards and policies, "change management. Conclusion: Based on the results of this research, "roles, responsibilities, and rights, "standards and policies, and "monitoring and auditing" are the main components of a data governance framework in data exchange centers. Additionally, "stakeholder collaboration" and "commercialization" also distinguish it from other data governance frameworks. Although this framework is developed for data exchange centers, it can also be used in similar inter-organizational contexts that require data exchange. [ABSTRACT FROM AUTHOR]

In view of the conflict of task scheduling and data exchange between multiple embedded AI(Artificial Intelligence) processors and improving the reliability and efficiency of stack expansion of multiple AI processors, a high speed data exchange technology and data frame structure of multiple embedded AI processors with wormhole switching structure are proposed in this study. Based on the PCIE(PCI Express) high-speed data interface, the data is transmitted in the form of data unit, and the multi-weight decision algorithm is designed to avoid the conflict in data transmission and realize the concurrent multi-threading of the task.The FPGA(Field Programmable Gate Array) platform is designed and tested. The results show that the transmission bandwidth utilization efficiency of PCIE reaches more than 85%, the data exchange delay is less than 20 μs, and the average maximum delay time of interrupt task response is 8.775 μs. The technology is suitable for high-speed switching circuits with multi-processor collaboration and can be extended to hybrid PCIE and RapidIO switching circuit architectures. [ABSTRACT FROM AUTHOR]

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data.

Purpose: Data governance frameworks have typically been discussed within the confines of an organization, with less focus on inter-organizational contexts. However, due to factors like the rise of electronic government applications and the growth of inter-organizational collaboration in competitive markets, data exchange among organizations is on the rise. This current research aims to address this gap by proposing a data governance framework for data exchange centers. Given the continuous growth of e-government applications and interactions, along with the significant role and value of data within them, implementing this framework can enhance the accuracy and efficiency of data and information exchange. Method: This research is qualitative and its method is grounded theory. Initially, the fundamentals of the research were examined. This involved reviewing both scientific and academic research as well as frameworks provided by technical and specialized associations. By exploring the basics and background of the research, foundational knowledge was acquired for subsequent steps. Subsequently, through conducting semi-structured interviews with experts and documenting them, over 400 phrases were collected, and categorized into 100 concepts. These were then analyzed using open coding (resulting in 44 subcategories), theoretical coding (leading to 15 categories), and the development of a theoretical framework. The data was sourced from national data exchange centers. Given the qualitative nature of the study, methods such as participant review, triangulation, and the Delphi technique were employed to ensure the validity and reliability of the findings. Findings: The data governance framework in the data exchange center comprises 15 components, categorized into "main components of governance, "main components in the business of data exchange centers, and "supporting components in the business of data exchange centers. Some of these components include "roles, responsibilities, and rights, "standards and policies, "change management. Conclusion: Based on the results of this research, "roles, responsibilities, and rights, "standards and policies, and "monitoring and auditing" are the main components of a data governance framework in data exchange centers. Additionally, "stakeholder collaboration" and "commercialization" also distinguish it from other data governance frameworks. Although this framework is developed for data exchange centers, it can also be used in similar inter-organizational contexts that require data exchange.

The goal of this article is to develop recommendations to assist logistic companies in formulating their B2B deployment policies as part of their engineering infrastructure strategy. It is postulated that logistic firms are likely to integrate B2B into their organizational structure in order to obtain a competitive advantage. The research examines the situation not only in the period immediately prior (2006) and after (2010) the 2008–2009 economic crisis, but also over a longer period of the following years in order to discover an eventual impact of the crisis on B2B deployment (2014, 2018). The results obtained from the 2008–2009 economic crisis are then applied analogically to the current 2020 coronavirus economic recession, where they serve as a foundation for formulating B2B deployment policy recommendations. We ascertained that B2B deployment increases in time of intensified market competition due to an economic crisis or recession and this tendency persists even in a longer horizon after the macroeconomic instability culmination. B2B systems can thus act as a significant “tool” for enhancing business competitiveness, which may be crucial for their economic “survival.”

Sharing land data from one department to the other is a continuous process. A solid structure and a set of guidelines on how to share them is to be put in place as a foundation for the development of a land administration data exchange and interoperability framework in support of data acquisition, land transactions and distribution of land data. In this research, the application of the ISO Framework for Enterprise Interoperability (FEI) as a standard is the starting point. Utilising the Land Administration Domain Model (LADM) profile for Kenya as a base, an interoperability framework in support of land administration in Kenya is developed that addresses concerns, removes barriers and selects the approach for implementation. Due to the critical nature of land, it fits into the United Nations 2030 sustainability agenda. During the development of the Kenyan profile, four country-specific issues in the context of people-to-land relationships have been identified and modeled. The mapping of those issues relevant to the sustainable development goals supports the achievement of those goals so that all related targets and indicators can be attained. Using GIS tools, the implementing and testing of the new LADM profile for Kenya is not a difficult task. By using existing land data combined with newly collected data in the LADM-compliant database, a complete and accurate workflow is assured. Integration with external databases is useful for improving efficiency and eliminating duplication. Data collection with all stakeholders and validation through public inspection are recommended. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) plays an essential contribution in connecting devices and enabling seamless data exchange, leading to increased efficiency and convenience. However, security concerns in IoT systems are significant, as compromised devices can lead to data breaches and privacy violations. Blockchain technology can enhance IoT security by providing decentralized consensus, immutability, and transparent transaction records, ensuring secure and trustworthy communication and data integrity. This review article gives a succinct but thorough understanding of blockchain technology, covering architecture of blockchain, working principles, types, applications, platforms, and its role in the IoT environment. The study highlights potential benefits of blockchain like enhanced security and privacy, and explores its integration with IoT. Additionally, the study discusses various real-world applications, examines blockchain platforms, and addresses the limitations and challenges associated with blockchain technology. This review serves as a valuable resource for researchers and practitioners seeking a deeper understanding of blockchain’s potential and its implications in the IoT landscape.

5G technology is the foundation for achieving intelligent mining construction. In response to the problem of difficult interoperability between mining 5G intelligent terminals and control platforms among different manufacturers, it is necessary to unify and standardize the data exchange and sharing process in the 5G system. The deployment architecture of '5G+intelligent mining' is proposed. The mining 5G intelligent terminals can interact and share data with servers containing control platforms through 5G base stations, switches, and 5G core networks in coal mines. This paper introduces the message types, message transmission formats, message composition, and message connection methods transmitted in the mining 5G system. For specific application scenarios in the mining field, the data in the mining 5G system is divided into voice data, video data, sensor data, and control data. The data types transmitted by the mining 5G intelligent terminal in different application scenarios are provided. This paper analyzes the basic transmission capabilities that mining 5G intelligent terminals and control platforms should have to meet data interaction. It is pointed out that the process of data interaction between mining 5G intelligent terminals and control platforms includes device information query and reporting, device upgrade, log collection, alarm issuance and processing, and platform configuration issuance and processing. It proposes the participating entities, security levels, and processes for data sharing of mining 5G intelligent terminals (including data aggregation, application, authorization, provision, and feedback). By implementing standardized processes, while ensuring communication reliability, the data exchange and sharing process under the '5G+intelligent mine' system architecture has been simplified to accelerate the intelligent construction of mines.

In the context of the digital evolution of the logistics industry, the interconnection of logistics information systems and associated data have become an obstacle of business collaboration among various stakeholders. A critical challenge in this domain is ensuring controllable access to logistics business data, given the industry’s current state characterized by independence, autonomy, disconnection, and heterogeneity, alongside the non-negotiable requirement for data privacy. We propose a novel model of trusted data access control based on of logistics business collaboration semantics. This approach incorporates semantic inference technologies into attribute-based access control mechanisms, thereby enabling the streamlined formulation of access control policies and facilitating unified authorization and control. Moreover, the method addresses the issue of access control policy management and maintenance at the semantic level. The proposed solution can pave the way for enhanced business collaboration between business entities, and further enable the building of a data exchange service platform within the logistics industry.

The Animal Metabolite Database (AMDB, https://amdb.online) is a freely accessible database with built-in statistical analysis tools, allowing one to browse and compare quantitative metabolomics data and raw NMR and MS data, as well as sample metadata, with a focus on the metabolite concentrations rather than on the raw data itself. AMDB also functions as a platform for the metabolomics community, providing convenient deposition and exchange of quantitative metabolomic data. To date, the majority of the data in AMDB relate to the metabolite content of the eye lens and blood of vertebrates, primarily wild species from Siberia, Russia and laboratory rodents. However, data on other tissues (muscle, heart, liver, brain, and more) are also present, and the list of species and tissues is constantly growing. Typically, every sample in AMDB contains concentrations of 60–90 of the most abundant metabolites, provided in nanomoles per gram of wet tissue weight (nmol/g). We believe that AMDB will become a widely used tool in the community, as typical metabolite baseline concentrations in tissues of animal models will aid in a wide variety of fundamental and applied scientific fields, including, but not limited to, animal modeling of human diseases, assessment of medical formulations, and evolutionary and environmental studies. [ABSTRACT FROM AUTHOR]

The Common Information Model (CIM) defined in international electrotechnical commission technical committee 57 (IEC TC57) has been utilized for achieving interoperability by employing a canonical data model strategy for standardizing interfaces in the power industry. In adopting the CIM framework for data exchange, problems regarding identifiers (IDs) such as two different local IDs for the same object can occur, and local ID mapping tables are required for the object identification in advance of the data exchange. This paper proposes a new local ID mapping scheme using a topological fingerprint (TF) that represents a unique property of a power system resource. The concept of standard information, defined as common data that all systems considered for data exchange have in common, is introduced to make duplicated TFs separable. Case studies considering numerous power system resources in a distribution management system (DMS) are conducted and it can be seen from the simulation results that the proposed scheme can generate a unique TF for every resource in a system by the local ID mappings and automatically create an accurate mapping table of local IDs issued by each system differently. [ABSTRACT FROM AUTHOR]

This paper presents an analysis and the research results of system couplers in CAx systems that ensure the correct transfer of product data from the "supplier" system to the "recipient" system. This study presents the results of the compatibility tests between the systems based on the verification of geometric models and their attributes after importing/exporting 2D and 3D objects using neutral data exchange formats. The purpose of the research was to identify neutral formats that do not introduce errors after data transversion in certain types of geometry. Tests and analyses were carried out on selected formats depending on the type of object, such as 2D objects (DXF), solid objects (IGES, STEP, SAT, and PARASOLID), and surface objects (IGES, STEP, SAT, and X_T). One of the results of our research and analysis is the need for continuous development of CAD/CAE systems because current neutral formats are not 100% effective. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sharing land data from one department to the other is a continuous process. A solid structure and a set of guidelines on how to share them is to be put in place as a foundation for the development of a land administration data exchange and interoperability framework in support of data acquisition, land transactions and distribution of land data. In this research, the application of the ISO Framework for Enterprise Interoperability (FEI) as a standard is the starting point. Utilising the Land Administration Domain Model (LADM) profile for Kenya as a base, an interoperability framework in support of land administration in Kenya is developed that addresses concerns, removes barriers and selects the approach for implementation. Due to the critical nature of land, it fits into the United Nations 2030 sustainability agenda. During the development of the Kenyan profile, four country-specific issues in the context of people-to-land relationships have been identified and modeled. The mapping of those issues relevant to the sustainable development goals supports the achievement of those goals so that all related targets and indicators can be attained. Using GIS tools, the implementing and testing of the new LADM profile for Kenya is not a difficult task. By using existing land data combined with newly collected data in the LADM-compliant database, a complete and accurate workflow is assured. Integration with external databases is useful for improving efficiency and eliminating duplication. Data collection with all stakeholders and validation through public inspection are recommended.

A medical entity (hospital, nursing home, rest home, revalidation center, etc.) usually includes a multitude of information systems that allow for quick decision-making close to the medical sensors. The Internet of Medical Things (IoMT) is an area of IoT that generates a lot of data of different natures (radio, CT scan, medical reports, medical sensor data). However, these systems need to share and exchange medical information in a seamless, timely, and efficient manner with systems that are either within the same entity or other healthcare entities. The lack of inter- and intra-entity interoperability causes major problems in the analysis of patient records and leads to additional financial costs (e.g., redone examinations). To develop a medical data interoperability architecture model that will allow providers and different actors in the medical community to exchange patient summary information with other caregivers and partners to improve the quality of care, the level of data security, and the efficiency of care should take stock of the state of knowledge. This paper discusses the challenges faced by medical entities in sharing and exchanging medical information seamlessly and efficiently. It highlights the need for inter- and intra-entity interoperability to improve the analysis of patient records, reduce financial costs, and enhance the quality of care. The paper reviews existing solutions proposed by various researchers and identifies their limitations. The analysis of the literature has shown that the HL7 FHIR standard is particularly well adapted for exchanging and storing health data, while DICOM, CDA, and JSON can be converted in HL7 FHIR or HL7 FHIR to these formats for interoperability purposes. This approach covers almost all use cases. [ABSTRACT FROM AUTHOR]

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use.

A secured platform is a critical component of digital governance, as it helps to ensure the privacy, security, and reliability of the electronic platforms and systems used to manage and deliver public services. Interoperability and data exchange are essential for digital governance, as they enable different government agencies and departments to share data, information, and resources seamlessly, regardless of the platforms and technologies they use. In this paper, we build a secure platform to enhance the trustworthiness of digital governance interoperability and data exchange using blockchain and deep learning-based frameworks. Initially, an optimal blockchain leveraging approach is designed using the bonobo optimization algorithm to authenticate data generated from smart city environments. Furthermore, we introduce the integration of a lightweight Feistel structure with optimal operations to enhance privacy preservation. This integration provides two levels of security and ensures interoperability and double-secured data exchange in digital governance systems. In addition, we utilize a deep reinforcement learning (DRL) model to detect and prevent intrusions such as fraud/corruption in the smart city data. This approach enhances transparency and accountability in accessing the data and shows its predominance over other cutting-edge techniques on two benchmark datasets, BoT-IoT and ToN-IoT. Furthermore, the effectiveness of the framework in real-time scenarios has been demonstrated through two case studies. Overall, our proposed framework provides a trustworthy platform for digital governance, interoperability, and data exchange, addressing the challenges of privacy, security, and reliability in managing and delivering public services.

The interoperability concerns horizontal integration among IoT devices which form vendor- or protocol-specific silos. To answer, this brief presents an architectural design of an autonomic interoperability manager (AIM) that is capable of self-configuration, self-healing, self-optimization, and self-protection. With AIM, IoT devices having diverse protocols, syntax, and semantics can collaborate and interact, and its plugin-based autonomic, service-oriented architecture ensures scalability and extendability. We simulated a healthcare use-case with a range of virtual IoT devices to demonstrate that the AIM dramatically reduces the average response time in a highly dynamic environment, by proactively pruning the network traffic and optimizing the compute resources.

In order to adapt to the in-depth application of information management under the current normal disaster reduction and abnormal disaster relief scenarios, this paper proposes a design scheme of business platform for natural disaster emergency response process. Data exchange method was adopted to realize information sharing among multiple departments; the comprehensive natural disaster database was established to realize unified data source management and real-time update; intelligent mobile terminals was used to push natural disaster information to realize government society public multi-dimensional coordination; based on the network geographic information system, the natural disaster risk status was displayed in real time to realize the application of natural disaster risk monitoring and early warning, comprehensive research and judgment and emergency command. The platform effectively improves the management level of natural disaster risk control and the efficiency of emergency management, and truly achieve the goal of cross domain, multi-disaster and whole process closed-loop management and accurate control of natural disaster risk.

The article continues the discussion of pilot study results concerning the specifics of university teachers' support for the idea of Open Science and is devoted to the main types of their engagement in data exchange. For this purpose, we described characteristics, subcharacteristics of engagement, and their indicators; classified the findings, conducted the step-by-step selection of engagement profiles with their further ranking according to the level of engagement, and grouped the types of engagement into common and distinctive ones. The determined types (intense, moderate, selective, and quasi) embrace all the identified relationships between various levels of engagement in empirical data exchange, namely: the shaped intention to share empirical data, the consistent application of its methods, and conscious assistance to it. The main types of engagement characterize teachers' intentions to disseminate empirical data and the possibility of such data reuse by other researchers. The findings can be valuable for the management of higher educational establishments, as it allows to evaluate teachers' readiness to disseminate the collected ED and to give permission for their reuse by other researchers. In general, the conducted research adds an important nuance to the implementation of institutional policies of research management with the purpose of promoting Open Science. [ABSTRACT FROM AUTHOR]

The interoperability of different virtual commissioning applications requires a lot of manual work, as they mainly use proprietary file formats. In this case, a generic virtual commissioning data model is highly demanded to realize interoperability among different virtual commissioning applications. Based on this model, the effort of exchanging data between different virtual commissioning applications is significantly reduced. A comprehensive generic virtual commissioning data model contains a variety of virtual commissioning-related information, such as geometry, physics, kinematics, sensors, actuators, and signal connections. For such an elaborate data model, no method is contemporarily indicated to evaluate its interoperability performance. Thus, in this paper, a case-based evaluation framework is introduced to fill in this gap. With this framework, the interoperability performance of a generic virtual commissioning data model can be evaluated by conducting data exchange of several emulation models developed in different virtual commissioning applications, and each of their specific virtual commissioning modeling functions is covered in at least one of these emulation models. As an example, a case study is presented by exchanging 10 carefully selected emulation models between Siemens NX and Visual Components software applications via AutomationML data format. Based on the case study, the applicability of this evaluation framework is analyzed and discussed. Finally, conclusion and outlook are illustrated in the end. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a methodology allowing any designer to be able to produce multi-material parts. Nowadays, the use of 3D printing is becoming a key process for on-demand and customized manufacturing. One of the most flexible 3D printing techniques is fused deposition modeling (FDM), where the combination of multiple materials was recently introduced. A quantum leap in part design is possible by integrating local variations between materials that allow for expanded functionality to be built into a single part. Therefore, the process of co-extrusion and material mixing is becoming more and more popular. The process of management and design of the engineered part are still complicated, and there are no commercially available tools that follow the process from design to production of these highly engineered products. This paper proposes a methodology to fill this gap and allow any designer to be able to produce multi-material parts by editing a G-code (computer numerical control programming language) with engineered gradients for FDM technology. More specifically, the proposed approach is based on the modification of the G-code according to a volumetric model describing the local combination of two or more materials. This original aspect allows for a wide extension of the current software capabilities. To explain and test the method, a simple test case was investigated, in which two components of an earphone are consolidated and developed gradually by combining polylactic acid and thermoplastic polyurethane. The results show the effectiveness of the proposed approach within the limits of the material coextrusion additive manufacturing process. [ABSTRACT FROM AUTHOR]

The food system is undergoing a digital transformation that connects local and global supply chains to address economic, environmental, and societal drivers. Digitalisation enables firms to meet sustainable development goals (SDGs), address climate change and the wider negative externalities of food production such as biodiversity loss, and diffuse pollution. Digitalising at the business and supply chain level through public–private mechanisms for data exchange affords the opportunity for greater collaboration, visualising, and measuring activities and their socio-environmental impact, demonstrating compliance with regulatory and market requirements and providing opportunity to capture current practice and future opportunities for process and product improvement. Herein we consider digitalisation as a tool to drive innovation and transition to a decarbonised food system. We consider that deep decarbonisation of the food system can only occur when trusted emissions data are exchanged across supply chains. This requires fusion of standardised emissions measurements within a supply chain data sharing framework. This framework, likely operating as a corporate entity, would provide the foci for measurement standards, data exchange, trusted, and certified data and as a multi-stakeholder body, including regulators, that would build trust and collaboration across supply chains. This approach provides a methodology for accurate and trusted emissions data to inform consumer choice and industrial response of individual firms within a supply chain.

Data security is an infrastructure designed to protect and secure data from unauthorized access, data manipulation, malfunction, destruction, and inappropriate data disclosure. Currently, organizations widely use data transfer to validate and verify data using different media particularly in host-to-host connections. This research focuses on data exchanged (end-to-end communication) using Multi Protocol Label Switching (MPLS), metro ethernet, and Software Defined Wide Area Network (SD-WAN) network architecture with third parties. This research aims to develop a design and analysis framework for verifying data transferred from one host to another in ABC organization by applicable security standards that are appropriate and follow its needs to help the organization. Furthermore, the analysis result is used as materials for drafting a cybersecurity framework through the three standards ISO/EIC 27001:2013, NIST SP800-161, and ITU-T X.805. The methodology used in this study is the comparative analysis of three frameworks, requirement analysis, and content analysis to develop a framework. The framework proposed of eight security dimensions, five threats, and providing mitigation is expected to enhance the security system of data exchange on host-to-host connections in ABC organization.

Environmental and technological design for climate adaptation in the urban built environment can no longer be separated from the generation, collection, or use of data (big data). ICT tools (Information and Communication Technologies), for the modelling and simulation of the built urban environment are identified as measuring devices and provide knowledge on the impacts of climate change in design practice based on an environmentally data-driven approach. This study aims to define a framework for the evaluation of environmental health and comfort parameters applicable to simulation tools, with a specific focus on thermal and environmental exchanges between indoor and outdoor spaces, to define those factors that affect the perception of user's well-being in thermal stress conditions (e.g., heatwaves), both indoor and outdoor. Through the definition of two study cases in the city of Naples, Italy, special attention was paid to investigating the interaction between outdoor and indoor performance when urban temperatures rise. A comparison between a daily survey for occupants and simulations was conducted to confirm the validity of the data obtainable from the perceived thermal sensations. The obtained results show that the designed framework can reliably simulate real outdoor and indoor conditions according to comfort indices such as the predicted mean vote and adaptive comfort model. The methodological framework developed can guarantee the interoperability of data to simulate indoor and outdoor environments responding to real conditions and determine a favourable condition for the development of urban redevelopment interventions through the application of climate adaptive design strategies. [ABSTRACT FROM AUTHOR]

There were examined the problems of passage of the regulated parts of a road. There were investigated the changes of a traffic movement intensity in Lutsk (Ukraine) during the spread of Covid-19 pandemic. The graphic dependences of the drivers’ actions estimation while passing the traffic lights objects on a chosen movement route at the beginning of quarantine measures, during the least movement intensity and at the increasing of movement intensity, were obtained. A method of increasing of a possibility of the traffic lights objects nonstop passage was offered.

The Animal Metabolite Database (AMDB, https://amdb.online) is a freely accessible database with built-in statistical analysis tools, allowing one to browse and compare quantitative metabolomics data and raw NMR and MS data, as well as sample metadata, with a focus on the metabolite concentrations rather than on the raw data itself. AMDB also functions as a platform for the metabolomics community, providing convenient deposition and exchange of quantitative metabolomic data. To date, the majority of the data in AMDB relate to the metabolite content of the eye lens and blood of vertebrates, primarily wild species from Siberia, Russia and laboratory rodents. However, data on other tissues (muscle, heart, liver, brain, and more) are also present, and the list of species and tissues is constantly growing. Typically, every sample in AMDB contains concentrations of 60–90 of the most abundant metabolites, provided in nanomoles per gram of wet tissue weight (nmol/g). We believe that AMDB will become a widely used tool in the community, as typical metabolite baseline concentrations in tissues of animal models will aid in a wide variety of fundamental and applied scientific fields, including, but not limited to, animal modeling of human diseases, assessment of medical formulations, and evolutionary and environmental studies.

The Common Information Model (CIM) defined in international electrotechnical commission technical committee 57 (IEC TC57) has been utilized for achieving interoperability by employing a canonical data model strategy for standardizing interfaces in the power industry. In adopting the CIM framework for data exchange, problems regarding identifiers (IDs) such as two different local IDs for the same object can occur, and local ID mapping tables are required for the object identification in advance of the data exchange. This paper proposes a new local ID mapping scheme using a topological fingerprint (TF) that represents a unique property of a power system resource. The concept of standard information, defined as common data that all systems considered for data exchange have in common, is introduced to make duplicated TFs separable. Case studies considering numerous power system resources in a distribution management system (DMS) are conducted and it can be seen from the simulation results that the proposed scheme can generate a unique TF for every resource in a system by the local ID mappings and automatically create an accurate mapping table of local IDs issued by each system differently.

This paper presents an analysis and the research results of system couplers in CAx systems that ensure the correct transfer of product data from the “supplier” system to the “recipient” system. This study presents the results of the compatibility tests between the systems based on the verification of geometric models and their attributes after importing/exporting 2D and 3D objects using neutral data exchange formats. The purpose of the research was to identify neutral formats that do not introduce errors after data transversion in certain types of geometry. Tests and analyses were carried out on selected formats depending on the type of object, such as 2D objects (DXF), solid objects (IGES, STEP, SAT, and PARASOLID), and surface objects (IGES, STEP, SAT, and X_T). One of the results of our research and analysis is the need for continuous development of CAD/CAE systems because current neutral formats are not 100% effective.

In a cyber-physical system, enterprise applications, control functions, and physical manufacturing assets are interconnected to seamlessly exchange information. However, the software and hardware often differ in terms of their data interfaces, data formats and semantics. Conventional enterprise applications usually employ file-based interfaces (e.g., Excel); control applications always support Ethernet-based protocols (e.g., OPC UA). Thus, data interoperability is currently lacking. The asset administration shell (AAS) is a new approach for achieving data interoperability across the automation pyramid as the AASX data format represents AAS information and supports data communication via OPC UA. In this study, we first provide insights into the AASX format and give exemplary applications on AASX; we then present an AASX-based solution for bidirectional data exchange between enterprise and control applications. In this solution, the conversion between AASX and Excel spreadsheets is completed to enable interoperable data exchange. Finally, a data exchange scenario for motor control is constructed to validate the effectiveness of the solution. The result shows no data were lost during the two-way conversions.

The exchange of information between transmission system operators (TSOs) and distribution system operators (DSOs) is a common practice. However, the evolution of the regulatory frameworks in Europe has increased the need for enhancing TSO-DSO data exchange and interoperability. This paper provides an overview of the TSO-DSO data exchanges and demonstrates the best practices using International Electrotechnical Commission (IEC) common information model (CIM), including the implementation of IEC common grid model exchange standard (CGMES), and discussion of the corresponding advantages, disadvantages, and challenges. Furthermore, this paper evaluates and reports the activities already carried out within European projects, with particular focus on TSODSO interoperability. Finally, this paper concludes the need for TSOs and DSOs to rely on standard-based solutions when performing TSO-DSO data exchange, which enables the efficient operation and development of the future power systems.

Data marketplaces are expected to play a crucial role in tomorrow’s data economy, but such marketplaces are seldom commercially viable. Currently, there is no clear understanding of the knowledge gaps in data marketplace research, especially not of neglected research topics that may advance such marketplaces toward commercialization. This study provides an overview of the state-of-the-art of data marketplace research. We employ a Systematic Literature Review (SLR) approach to examine 133 academic articles and structure our analysis using the Service-Technology-Organization-Finance (STOF) model. We find that the extant data marketplace literature is primarily dominated by technical research, such as discussions about computational pricing and architecture. To move past the first stage of the platform’s lifecycle (i.e., platform design) to the second stage (i.e., platform adoption), we call for empirical research in non-technological areas, such as customer expected value and market segmentation.

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/). [ABSTRACT FROM AUTHOR]

EnzymeML is an XML‐based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO‐RK. [ABSTRACT FROM AUTHOR]

The digital twin has emerged as a crucial technology for smart production. The Asset Administration Shell (AAS) is a standard tool that can support the digital representation of a process plant. We present a method to use AAS coupled with ISO 15926 to facilitate the exchange of maintenance data in process plants. To accomplish this, the operation and maintenance (O&M) system framework employed in process plants is defined. Information requirements are derived based on this framework, and a maintenance data structure is designed. Along with this, reference data are applied to identify the types of equipment and properties of each equipment type using ISO 15926. According to the pre-designed data structure, a neutral format based on AAS is developed to exchange maintenance data among software systems in O&M. The neutral format is verified through a test case of exchanging maintenance data (equipment condition and health status data) in terms of applicability to O&M systems in the field and compliance with the AAS meta-data model. [ABSTRACT FROM AUTHOR]