Standard Exchange Format Research Articles

Modeling Enzyme Kinetics: Current Challenges and Future Perspectives for Biocatalysis.

Biocatalysis is becoming a data science. High-throughput experimentation generates a rapidly increasing stream of biocatalytic data, which is the raw material for mechanistic and novel data-driven modeling approaches for the predictive design of improved biocatalysts and novel bioprocesses. The holistic and molecular understanding of enzymatic reaction systems will enable us to identify and overcome kinetic bottlenecks and shift the thermodynamics of a reaction. The full characterization and modeling of reaction systems is a community effort; therefore, published methods and results should be findable, accessible, interoperable, and reusable (FAIR), which is achieved by developing standardized data exchange formats, by a complete and reproducible documentation of experimentation, by collaborative platforms for developing sustainable software and for analyzing data, and by repositories for publishing results together with raw data. The FAIRification of biocatalysis is a prerequisite to developing highly automated laboratory infrastructures that improve the reproducibility of scientific results and reduce the time and costs required to develop novel synthesis routes.

MeDaX: A Knowledge Graph on FHIR.

In Germany, the standard format for exchange of clinical care data for research is HL7 FHIR. Graph databases (GDBs), well suited for integrating complex and heterogeneous data from diverse sources, are currently gaining traction in the medical field. They provide a versatile framework for data analysis which is generally challenging for raw FHIR-formatted data. For generation of a knowledge graph (KG) for clinical research data, we tested different extract-transform-load (ETL) approaches to convert FHIR into graph format. We designed a generalised ETL process and implemented a prototypic pipeline for automated KG creation and ontological structuring. The MeDaX-KG prototype is built from synthetic patient data and currently serves internal testing purposes. The presented approach is easy to customise to expand to other data types and formats.

TPMS2STEP: Error-Controlled and [formula omitted] Continuity-Preserving Translation of TPMS Models to STEP Files Based on Constrained-PIA

Triply periodic minimal surface (TPMS) is emerging as an important way of designing microstructures. However, there has been limited use of commercial CAD/CAM/CAE software packages for TPMS design and manufacturing. This is mainly because TPMS is consistently described in the functional representation (F-rep) format, while modern CAD/CAM/CAE tools are built upon the boundary representation (B-rep) format. One possible solution to this gap is translating TPMS to STEP, which is the standard data exchange format of CAD/CAM/CAE. Following this direction, this paper proposes a new translation method with error-controlling and C2 continuity-preserving features. It is based on an approximation error-driven TPMS sampling algorithm and a constrained-PIA algorithm. The sampling algorithm controls the deviation between the original and translated models. With it, an error bound of 2ϵ on the deviation can be ensured if two conditions called ϵ-density and ϵ-approximation are satisfied. The constrained-PIA algorithm enforces C2 continuity constraints during TPMS approximation, and meanwhile attaining high efficiency. A theoretical convergence proof of this algorithm is also given. The effectiveness of the translation method has been demonstrated by a series of examples and comparisons. The code will be open-sourced upon publication.

Enhancing Interoperability: Exploring Data Exchange Standards in SaaS Laboratory Management Systems

In the ever-changing environment of health care, smooth information exchange among different systems is significant to ensure efficiency and high-quality patient care. This is also important in laboratory management, where time and accuracy are critical for patients' diagnosis and treatment choices. Nevertheless, interoperability is still a big issue, with SaaS laboratory systems being the primary concern. This study focuses on the importance of interoperability in contemporary healthcare systems, with particular emphasis on laboratory management. It shows the significance of an uninterrupted data flow between SaaS laboratory management systems and other healthcare I.T. systems, such as E.H.R.s and HIEs. Existing data exchange standards and frameworks for interoperability among SaaS laboratory management systems are discussed, including the challenges of achieving interoperability. A quantitative research approach-based questionnaire was deployed to assess the interoperability requirements and processes of the genetic testing laboratories in the survey. Investigations point to different levels of compatibility among SaaS lab management systems in terms of features offered as well as the challenges faced by the latter. Challenges include different data formats, communication protocol standards, and data model incompatibility. The study emphasizes the critical role of interoperability and data exchange in SaaS laboratory management systems and the entire healthcare industry. The methods of overcoming the interoperability problem are investing in education, creating collaborative partnerships, promoting integration frameworks, and establishing incentives for obedience to standardized data exchange format.

BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies

The main objective of this review is to summarize and thoroughly investigate the most popular and promising BIM (building information modeling) and BEM (building energy modeling) interoperability strategies employed in the last years (2004–2023), highlighting pros and cons of each strategy and trying to understand the reason for the still limited BIM–BEM interaction. This review summarizes the main countries, areas, modeling tools, and interoperability strategies, with the advantages and disadvantages of each one. The methodology is based on the PRISMA protocol, and two databases were used for the research: Scopus and Google Scholar. A total of 532 publications were selected and 100 papers were deemed useful for the purposes of this review. The main findings led to the identification of four different interoperability strategies between BIM and BEM tools: (1) real-time connection; (2) standardized exchange formats and middleware corrective tools; (3) adherence to model view definitions; (4) proprietary tool-chain. These strategies were found to be characterized by different degrees of complexity, time required for information exchange, proprietary or opensource software, ability to reduce information loss, and detailed energy results. The results of this study showed that, to date, there is no better interoperability strategy, and that further efforts are needed so that interoperability between the two tools can become commonplace.

FAIR and scalable management of small-angle X-ray scattering data.

A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small-angle X-ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS-tools library is a community-driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python-native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS-tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethyl-ammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry.

Verification Witnesses

Over the last years, witness-based validation of verification results has become an established practice in software verification: An independent validator re-establishes verification results of a software verifier using verification witnesses, which are stored in a standardized exchange format. In addition to validation, such exchangable information about proofs and alarms found by a verifier can be shared across verification tools, and users can apply independent third-party tools to visualize and explore witnesses to help them comprehend the causes of bugs or the reasons why a given program is correct. To achieve the goal of making verification results more accessible to engineers, it is necessary to consider witnesses as first-class exchangeable objects, stored independently from the source code and checked independently from the verifier that produced them, respecting the important principle of separation of concerns. We present the conceptual principles of verification witnesses, give a description of how to use them, provide a technical specification of the exchange format for witnesses, and perform an extensive experimental study on the application of witness-based result validation, using the validators CPAchecker , UAutomizer , CPA-witness2test , and FShell-witness2test .

EnzymeML-a data exchange format for biocatalysis and enzymology.

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.

The Impact of Organizational Structure and Technology Use on Collaborative Practices in Computer Emergency Response Teams: An Empirical Study

Besides the merits of increasing digitization and interconnectedness in private and professional spaces, critical infrastructures and societies are more and more exposed to cyberattacks. In order to enhance the preventative and reactive capabilities against cyberattacks, Computer Emergency Response Teams (CERTs) are deployed in many countries and organizations. In Germany, CERTs in the public sector operate on federal and state level to provide information security services for authorities, citizens, and enterprises. Their tasks of monitoring, analyzing, and communicating threats and incidents is getting more complex due to the increasing amount of information disseminated into public channels. By adopting the perspectives of Computer-Supported Cooperative Work (CSCW) and Crisis Informatics, we contribute to the study of organizational structures, technology use, and the impact on collaborative practices in and between state CERTs with empirical research based on expert interviews with representatives of German state CERTs (N=15) and supplementary document analyses (N=25). We derive design and policy implications from our findings, including the need for interoperable and modular architecture, a shift towards service level agreements, cross-platform monitoring and analysis of incident data, use of deduplication techniques and standardized threat exchange formats, a reduction of resource costs through process automation, and transparent reporting and tool structures for information exchange.

A pathway map of signaling events triggered upon SARS-CoV infection.

Severe acute respiratory syndrome coronaviruses (SARS-CoVs) caused worldwide epidemics over the past few decades. Extensive studies on various strains of coronaviruses provided a basic understanding of the pathogenesis of the disease. Presently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading a global pandemic with unprecedented challenges. This is the third coronavirus outbreak of this century. A signaling pathway map of signaling events induced by SARS-CoV infection is not yet available. In this study, we present a literature-annotated signaling pathway map of reactions induced by SARS-CoV infected cells. Multiple signaling modules were found to be orchestrated including PI3K-AKT, Ras-MAPK, JAK-STAT, Type 1 IFN and NFκB. The signaling pathway map of SARS-CoV consists of 110 molecules and 101 reactions mediated by SARS-CoV proteins. The pathway reaction data are available in various community standard data exchange formats including Systems Biology Graphical Notation (SBGN). The pathway map is publicly available through the GitHub repository and data in various formats can be freely downloadable.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12079-021-00642-2.

SPART: A versatile and standardized data exchange format for species partition information.

A wide range of data types can be used to delimit species and various computer-based tools dedicated to this task are now available. Although these formalized approaches have significantly contributed to increase the objectivity of species delimitation (SD) under different assumptions, they are not routinely used by alpha-taxonomists. One obvious shortcoming is the lack of interoperability among the various independently developed SD programs. Given the frequent incongruences between species partitions inferred by different SD approaches, researchers applying these methods often seek to compare these alternative species partitions to evaluate the robustness of the species boundaries. This procedure is excessively time consuming at present, and the lack of a standard format for species partitions is a major obstacle. Here, we propose a standardized format, SPART, to enable compatibility between different SD tools exporting or importing partitions. This format reports the partitions and describes, for each of them, the assignment of individuals to the "inferred species". The syntax also allows support values to be optionally reported, as well as original trees and the full command lines used in the respective SD analyses. Two variants of this format are proposed, overall using the same terminology but presenting the data either optimized for human readability (matricial SPART) or in a format in which each partition forms a separate block (SPART.XML). ABGD, DELINEATE, GMYC, PTP and TR2have already been adapted to output SPART files and a new version of LIMES has been developed to import, export, merge and split them.

Building Protein-Protein and Protein-Glycosaminoglycan Interaction Networks Using MatrixDB, the Extracellular Matrix Interaction Database.

The interaction database MatrixDB reports protein-protein and protein-glycosaminoglycan interactions in human, mammalian, and model organisms, involving at least one extracellular matrix (ECM) constituent, namely full-length proteins, ECM multimeric proteins considered as stable complexes, proteoglycans, glycosaminoglycans (GAGs), and bioactive fragments called matricryptins, which are released upon limited proteolysis of ECM proteins. The current version of MatrixDB (as of October 2020) contains 106,543 experimentally supported interactions, with all types of biomolecules combined. MatrixDB is the only database focusing on the curation of ECM protein and GAG interactions. The iNavigator integrated in MatrixDB allows users to build interaction networks online and to filter them according to expression data, quantitative proteomics data, or interaction detection methods. MatrixDB belongs to the International Molecular Exchange (IMEx) consortium, and uses its curation rules to capture interaction data, which are available in standardized exchange formats according to the Human Proteome Organization-Proteomics Standards Initiative (HUPO-PSI). © 2021 Wiley Periodicals LLC. Basic Protocol 1: Browse MatrixDB Basic Protocol 2: Create a list of biomolecules of interest to build interaction networks Basic Protocol 3: Build and export interaction networks of selected biomolecules using the iNavigator Basic Protocol 4: Build specific interaction networks using the iNavigator widgets Basic Protocol 5: Generate 3D models of glycosaminoglycan oligosaccharides using the GAG Builder tool.

ГЕОИНФОРМАЦИОННОЕ ОБЕСПЕЧЕНИЕ ПРОГНОЗИРОВАНИЯ ЗОН ЗАТОПЛЕНИЙ НА ЮГЕ САХАЛИНА

Modern systems of hydrometeorological monitoring, for the most part, widely use WEB and GIS technology tools. Territorial fragmentation divisions of the World Meteorological Organization (WMO), Roshydromet, Russian Academy of Sciences and other services and departments interested in obtaining data requires creation of unified information environment for exchange of heterogeneous information. Formation field for geospatial data has become possible with the availability of industrial design platforms with high performance, supporting standard data exchange formats suitable of system for building projectoin. The purpose of the study is to develop requirements for geoinformation sup-port of the system necessary for flood forecasting. Methods: GIS mapping, interpretation and analysis of remote sensing data of the Earth. When developing system for hydrological monitoring of rivers in the Southern Sakhalin, we used the experience of operating similar observational network in services of several European countries, as well as the geographically distributed GIS created by Roshydromet. Considering the vast experience of predecessors and requirements for geoinformation support neces-sary for predicting flood zones in the rivers of Southern Sakhalin have been developed. The initial da-ta for creating the correct flood model are satellite images, large-scale topographic maps, digital terrain models, data from long-term hydrometeorological observations, and engineering surveys.

Telemedicine System Based on Medical Consultation Assistance Integration

With the aging of the global population, how to provide effective telemedicine for the aging population has become a very important issue, especially for the elderly with limited mobility. If there is a complete telemedicine system, it will not only greatly improve medical efficiency. It can reduce the chance of contact between people and avoid the medical risks caused by severe special infectious pneumonia. This paper focuses on the development of a high-efficiency telemedicine system platform that conforms to international standard data exchange formats. This system platform can not only solve the problem of shortage of medical staff but also allow patients to be free from medical outpatient time constraints. Achieve the effect of telemedicine at any time, and digitize the medical process rules to establish a complete online telemedicine system platform.

Advanced and Rapid Tool in Control Room to Determine the Cause and Location of Events in Transmission Network

Operating personnel in control room act on SCADA alarm generated on data from station computer. Using new technologies and advanced technical solutions assistance tool can be designed. This tool provides quick help in busy situations for operator. For this new tool with three types of case studies insight will be given in this paper. Introduction part has short information about numbers of alarms and events in Control centre, and their distribution during one month period. Basic principles for alarm handling in SCADA system is given with all limitations. New tool, Intelligent Alarm Processing system is designed and implemented in control room. It has connection to SCADA system with standard data exchange format CIM/XML and run in real time, with only few seconds delay. This system based on Multilevel Flow Model has root cause analyses implemented for power system. Detail fault location algorithm description with block scheme for this Intelligent Alarm Processing system is part of third chapter. Special attention must be paid for modelling protection data in SCADA system which are sent to this new tool. Demonstration of Intelligent Alarm Processing system operation is reported in fourth chapter. Three characteristic disturbances in transmission network were elaborated. Most complex and challenging disturbances for operator in control room is cascading event. This case study is presented in detail in four sequences through graphical user interface. Second case study is also challenging for operators, heavy winter storm with numerous isolated events. In this case study very effective graphical presentation and alarm list with three types, primary event, consequences and detail list for this events were demonstrated. This list pointed out exactly and clearly what happened in the network. Last case study presents common disturbances which appears on daily basis, where this tool is of great assistance because it points on transmission elements very fast.

Sensor application of mobile nursing integrated workstation measurement system based on SOA architecture model in nursing information management

AbstractBased on the current status of the mobile medical market, combined with the specific needs of clinical care, this article analyzes the needs and business models of mobile nursing integrated workstations in detail, and combines the user's usage habits with the SOA architecture implemented by WebService. XML, as a standard format for data exchange between heterogeneous systems, and the data exchange method of ORACLE object technology, complete the interaction of data information; and use mobile intelligent devices to achieve the first‐time data collection at the bedside, and design mobile care integration workstation.

EleMA: A reference simulation model architecture and interface standard for modeling and testing of electric vehicles

Abstract In automotive development, simulation models are gaining significance, in particular in the early phases of verification and validation. According to the current state-of-the-art, there is no standardized simulation framework to achieve a seamless transition in the conception, implementation and integration of complex system simulations. In this paper, a reference simulation model architecture for electric vehicles is presented, which is proposed as a standard for real-time and non-real-time closed-loop simulations. The proposed Electric Modeling Architecture (EleMA) is intended as an extension of standardized model exchange formats by defining standardized, functional and signal-based interfaces of electric vehicle simulation models. It is designed independently of the utilized tool chain or exchange format of the simulation model components and enables their functional compatibility and exchangeability. Initially, an overview of standardized model exchange formats as well as the main design ideas of the proposed reference architecture are presented, followed by a short description of the applied specification methodology. EleMA provides all users a reference model including the contained components, a formalized description in the form of use case diagrams and a definition of the variant-independent component interfaces for each individual component. The implementation of simulation model components according to EleMA guarantees from an architectural point of view a functional compatibility of the elements on system level and thus improves reusability and exchangeability of simulation components. The last section demonstrates use cases to highlight the advantages of the reference architecture and quantifies the average effort reduction exemplary for one use case.

Simulation Foundry: Automated and F.A.I.R. Molecular Modeling.

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

The Development of Medical Markup Language Version 4 as a Clinical Document Exchange Format for Nationwide EHR Systems.

Medical Markup Language (MML) is a standard format for exchange of healthcare data among healthcare providers. Following the last major update (version 3), we developed new modules and discussed the requirements for the next major updates. Subsequently, in 2016 we released MML version 4 and used it to obtain clinical data from healthcare providers for a nationwide electronic health records (EHR) system. In this article we provide an overview of this major update of MML version 4 and discuss its interoperability for clinical data.

The Seagoing Scientist's Toolbox: Integrated Methods for Quality Control of Marine Geophysical Data at Sea

AbstractWe announce a new and integrated system for planning and executing marine geophysical surveys and for scrutinizing and visualizing incoming shipboard data. The system incorporates free software designed for use by scientists and shipboard operators and pertains to underway geophysics and multibeam sonar surveys. Regarding underway data, a crucial first step in the approach is to reduce and merge incoming center beam depth, gravity, and towed magnetic data with navigation, then reformat to the standard exchange format. We are then able to apply established quality control methods including along‐track and cross‐track analyses to identify error sources and to incrementally build the candidate archive file as new data are acquired. Regarding multibeam data, these are subjected to both an automated error removal scheme for quick visualization and to subsequent ping editing in detail. The candidate archive file and sonar data are automatically and periodically updated and adapted for display in Google Earth, wherein survey planning is also carried out. Data layers are also updated automatically in Google Earth, allowing scientists to focus on visual inspection and interpretation of incoming data. By visualizing underway and sonar data together with reference gravity, magnetic, and bathymetry grids in Google Earth, data familiarity is enhanced and the likelihood of noticing extreme errors increased. We hope scientists will embrace these techniques so that each data set being submitted to a data repository is vetted by the seagoing science party.