Exchange Format Research Articles

Can the European EHR Exchange Format Support Shared Decision Making and Citizen-Driven Health Science?

The European Commission published in 2019 the Recommendation on the European Electronic Health Record exchange format (EHRxF) to support citizens and healthcare providers in securely accessing and sharing EHRs. The European EHRxF is expected to contribute to the digital transformation of health and care in the digital single market empowering citizens and building a healthier society. This paper presents areas of work that need to be resolved for the European EHRxF to advance shared decision-making for patients and citizen-centered science.

Design & development of customizable web API for interoperability of antimicrobial resistance data

Antimicrobial resistance (AMR) is a global health emergency. Complementary to developing new drugs, AMR can be monitored and controlled through cost-effective active surveillance of resistance. As an initiative to monitor resistance, countries all across the globe are collecting data using a variety of surveillance tools. Moreover, hospitals routinely collect the AMR data for treatment which is being stored in their Laboratory and Hospital Information systems (LIS-HIS). The generated clinical data is collected & stored in various formats, making it very difficult to analyze and generate national reports. To integrate the stored clinical data for predictive modeling and analysis, there is an immediate need for a one-stop data repository capable of importing and exporting data in simple data exchange formats (CSV/Excel). The paper highlights the design & development of i-DIA, a python-based web API to facilitate the interoperability of AMR data by automatically importing the bulk of medical data from CSV files into generic data management and analysis system. The i-DIA has been integrated and tested with the ICMR’s AMR surveillance network on in-house developed software, i-AMRSS. The i-AMRSS is presently collecting data from 31 laboratories across India and i-DIA has been used to import data generated from LIS & HIS of a few hospitals directly into the system. The paper also proposes the complete web-based framework (an extension of i-DIA) integrated with peer-to-peer system architecture.

METHODS AND MEANS OF ENSURING THE INTEROPERABILITY OF THE COMPONENTS OF THE NATIONAL GEOSPATIAL DATA INFRASTRUCTURE

Interoperability is one of the key characteristics of the national geospatial data infrastructure (NSDI), on which depends the effectiveness of the interaction of holders, producers and users of geospatial data in the network of geoportals. The article substantiates the methods and means of achieving a high level of interoperability of the components of the Ukraine NSDI on the basis of ensuring the consistency of geospatial data supplied by different data producers, standardization of metadata and interfaces of geoinformation services. It is established that the bases of the legislative and organizational level of interoperability are defined in the Law of Ukraine "On the national geospatial data infrastructure " and in the "Procedure for the operation of NSDI".
 To ensure the interoperability of the components of the Ukraine NSDI at the semantic and technical levels, it is necessary to develop a set of technical regulations that define common requirements for: composition and structure of metadata, interfaces and functions of geographic information services, compatibility of geospatial data sets, classification systems, coding and unique identification of geospatial objects, open data exchange formats. These technical regulations should be based on the consistent and comprehensive implementation of the methodology of the basic international standards of the ISO 19100 Geographic Information / Geomatics series, the effectiveness of which has been confirmed by the successful implementation of NSDI in many countries of the world.

EXPERIMENTAL RESEARCH OF THE ACCURACY OF NAVIGATION GNSS - RECEIVERS IN CONDITIONS OF THE CONSTRUCTED TERRITORY

Use of digital geodetic support technologies with the use of GNSS satellite systems in combination with electronic geodetic instruments, introduction of new methods of construction of geodetic networks, collection of information by ground and aerospace surveying, unification of exchange formats of measurement results based on computer technologies and their application conditions. Substantiation and development of remote methods of spatial information collection requires analysis and consideration of a number of errors in order to improve accuracy.
 Wikimapia is a map project for shared use with open content, which aims to identify all geographical objects with the introduction of useful information about them. It combines an interactive web map and a Wiki system.
 One of the features of the Wikimapia resource is that it is possible to determine geographical coordinates. To do this, you need to move the cross cursor on the object of interest and get its coordinates visually.
 The purpose of the study was to determine the accuracy of the coordinates of GPS receivers Garmin Oregon 450 in the built-up area, using as a basis for calibration, the resource "Wikimapia".
 In order to determine the accuracy of the location with the help of GARMIN Oregon 450 GPS receivers, GNSS measurements were performed at 30 marker points.
 Ellipsoidal coordinates were recalculated into spatial rectangles according to known formulas.
 In order to assess the accuracy of determining the location of marker points, the differences in the coordinates of their position were found and the root mean square error from a number of measurements was found.
 The average error of coordinate measurements was ± 4.79 m for the GPS receiver.
 Based on experimental research, the possibility of using the resource "Wikimapia" not only to quickly determine the coordinates of topographic objects, determine their categories, but also with sufficient accuracy to apply for the calibration of navigation GNSS receivers when there is no network of geodetic points.
 A promising direction in the process of scientific and practical research should be the creation of a general mathematical model for predicting the influence of the plurality on the location and improvement of navigation aids.

SWEA-Dataveg: A vegetation database for sub-Saharan Africa

SWEA-Dataveg is a vegetation-plot database collecting observations mainly in sub-Saharan Africa but also open to the rest of the African continent. To date this database contains more than 5,500 plot observations provided by 47 sources (projects, monographs, and articles). While the database is stored in PostgreSQL (including the PostGIS extension), the R-package “vegtable” implements a suitable exchange format. In this article we assess the current content of SWEA-Database and introduce its history and future as a repository of data for syntaxonomic assessments and macroecological research.

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ ОБМІНУ ДАНИМИ СУТНОСТЕЙ У РЕЛЯЦІЙНОМУ ПРЕДСТАВЛЕННІ ТА ЇХ ОБРОБКИ

Nowadays, the area of software development has become widespread among all areas of business, so it is important to ensure high efficiency of applications. Due to the fact that data operating is an integral part of any program, the question how to increase the efficiency of data transmission and processing appeared. Existing technologies for data exchange are designed primarily to meet the criteria of universality and clarity, but these technologies turn out to be redundant or insufficient for software products operating data in relational representation. Many domestic and foreign publications have been devoted to the study of data exchange formats, but all lack research on ways to improve the efficiency of software data processing. Also, the public domain doesn’t contain any latest publications solving the issue of reducing the amount of data being transmitted between software components. Improving the efficiency of exchange of data in relational representation, using a specially designed data serialization format and method of processing. The article is devoted to presenting own improved data serialization format for data exchange of entities in relational representation, as well as providing a method of software data processing, which can significantly increase productivity. This paper reveals the problem of exchanging data in relational representation and the disadvantages of using existing serialization formats for transferring relational objects in software systems. The explanation to the decision proposed here is given with the help of the description of the applied technique for problem solving, the graphic scheme of the data format designed and an example of program realization. The actual result of the study is the construction of the concept of own experimental data serialization format as a way to partially solve the problem described and a detailed description of its structure. The article also describes the .NET Core implementation of the proposed method of efficient processing of data retrieved as a result of deserialization from the format presented. The following tools to improve the efficiency of data exchange for entities with a relational representation were proposed in the article: a specially developed data serialization format and the method of its software processing.

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.

Методика картографування об’єктів історико-культурної спадщини засобами ГІС-технологій з використанням архівних картографічних та аероматеріалів

Aim. The purpose of the work is to process archival cartographic materials and remote sensing data for the interpretation of objects of historical and cultural heritage (OHCH) of Cherkasy, including those that have not been preserved. Method. One of the possible technological schemes for research is offered. According to her, the first step was to analyze the input data of the study, among which were: a map of Cherkasy in 1895 at a scale of 1:42000; German aerial image of 1944; a fragment of a space image of Cherkasy obtained from the GeoEye-1 satellite in 2018. Geometric correction of the input materials was performed in the Mercator projection and the WGS84 coordinate system, in which the transformed image was obtained. The next step was to vectorize the objects of historical and cultural heritage of Cherkasy, according to the list obtained on the city’s website. There are two types of objects: point and polygonal. When vectorizing polygonal objects, the historical boundaries were specified with the help of archival maps and aerial images. Special symbols have been developed for each of the types of historical and cultural heritage sites, according to the proposed classification. In addition, an attributive database of these objects was created, which had the following structure: number of the passport of object, the name of the object, the address of the OHCH, the number of the decision to take under protection, information about the OHCH. Also, the obtained vector data was exported to the exchange format with the extension kmz and an online version of the thematic map was created on the basis of the free GISFile resource. Results. As a result of the conducted researches, the thematic GIS of the objects of historical and cultural heritage of Cherkasy was created, which are plotted on the space image of high spatial resolution, obtained in 2018. An on-line version of the GIS of Cherkasy historical and cultural heritage sites has been created on the basis of the free GISFile cartographic service, with the possibility of analyzing the location of these objects and building optimal tourist routes. Scientific novelty. Possible algorithms for creating offline and on-line versions of thematic GIS are proposed. Practical value. The obtained results of mapping the objects of historical and cultural heritage of Cherkasy can be used by the structures of protection of objects of historical and cultural heritage of Cherkasy at the Ministry of Culture.

TEC Response and Subsequent GPS Error Caused by the Most severe Geomagnetic Storm of Solar Cycle 24 at India

This paper presents the response of low-latitude and mid-latitude ionosphere to a severe geomagnetic storm that occurred on 17 March 2015 at 0445 UT, and the subsequent effect of this storm on GPS error in the East-West (E-W) and North-South (N-S) directions. The Vertical Total Electron Content (VTEC) data has been analysed from three dual frequency GPS receivers, which were installed under the framework of the International GNSS Service (IGS). For each day of the year, the data is downloadable as a single file in the Receiver Independent Exchange Format (RINEX) from the IGS data portal. The VTEC values from the IGS are obtained at one minute intervals. Results show the variations in GPS derived VTEC during the severe geomagnetic storm. Negative ionospheric storms caused by composition changes are observed at mid-latitude region of Lucknow, while positive ionospheric storms caused by magnetospheric convection and Equatorial Ionospheric Anomaly (EIA) are prominent at low-latitude regions of Bangalore and Hyderabad. The maximum depletion in VTEC peak at mid-latitude region of Lucknow when compared to the quiet day mean VTEC was 61 percent during a negative ionospheric storm that occurred on 18 March 2015, and maximum enhancement in VTEC peak at low-latitude region of Bangalore and Hyderabad when compared to the quiet day mean VTEC was 26 percent and 21 percent respectively during an early positive ionospheric storm on 18 March 2015. Positive ionospheric storms caused by enhanced EIA and Prompt Penetration Electric Fields (PPEF) are prominent at low-latitudes. The highest GPS error during storm time was +7.2 m and +11.3 m in E-W and N-S directions respectively at Lucknow. The average GPS error in E-W and N-S directions during storm time was higher at the mid-latitude station of Lucknow.

The Experimental Nuclear Reaction Data(EXFOR)

The EXchange FORmat (EXFOR) experimental nuclear reaction database and the retrieval system provide access to the wealth of low- and intermediate-energy nuclear reaction physics data, and become the most comprehensive compilation of experimental nuclear reaction data. Currently, there are 13 participants (nuclear data centers) of the International Network of Nuclear Reaction Data Centers(NRDC) which has been organized under the auspices of the International Atomic Energy Agency(IAEA) to coordinate the collection, compilation, and dissemination of nuclear data on an international scale. As the participant of NRDC, China Nuclear Data Center(CNDC) does its best for measurement of nuclear reaction quantities induced by neutron and charged-particle and research on the technique of database construction. The formation, development and current situation of EXFOR library, and its format, compilation and retrieval system were introduced. The work on compilation of experimental nuclear reaction data and study of the database construction technique in China was briefly summarized, such as scanning Chinese journals, compiling EXFOR entries, developing software, providing nuclear data service in China, collaborating with NRDC and so on.

GPSeqClus: An R package for sequential clustering of animal location data for model building, model application and field site investigations

Abstract Evaluating the concentration of animal locations, in space and time, provides insight regarding animal activity and behaviour. Most commonly collected via global positioning system technology, these concentrations are identified using rule sets resulting in location ‘clusters’. Cluster algorithms provide a framework for modelling and predicting behavioural states when paired with field data to evaluate habitat characteristics and validate results. We provide a sequential clustering algorithm package (GPSeqClus) to process location datasets based on user‐defined parameters. GPSeqClus also calculates an array of movement attributes commonly applied as covariates to develop cluster‐based models. Our package maps locations and clusters, with additional functions to assess specific clusters for site investigations and to export GPS Exchange format (.gpx) files for navigation. We highlight the ability of GPSeqClus to modify existing cluster attributes or to append additional attributes, and the flexibility to accommodate archived or near real‐time (satellite‐driven) datasets. Although spatio‐temporal clustering is widely used in animal ecology, clustering routines are commonly applied to assess carnivore movement patterns to predict denning or feeding locations, evaluate prey composition and estimate kill rates and handling times. We demonstrate the applicability of GPSeqClus by constructing clusters using mountain lion Puma concolor location data. Our package provides an efficient data processing routine to build, characterize, visualize and navigate to clusters. Attributes provided within GPSeqClus can be used when developing predictive cluster models, or can be applied to other modelling procedures to advance understandings of animal behaviour.

Qiime Artifact eXtractor (qax): A Fast and Versatile Tool to Interact with Qiime2 Archives.

Qiime2 is one of the most popular software tools used for analysis of output from metabarcoding experiments (e.g., sequencing of 16S, 18S, or ITS amplicons). Qiime2 introduced a novel and innovative data exchange format: the ‘Qiime2 artifact’. Qiime2 artifacts are structured compressed archives containing a dataset and its associated metadata. Examples of datasets are FASTQ reads, representative sequences in FASTA format, a phylogenetic tree in Newick format, while examples of metadata are the command that generated the artifact, information on the execution environment, citations on the used software, and all the metadata of the artifacts used to produce it. While artifacts can improve the shareability and reproducibility of Qiime2 workflows, they are less easily integrated with general bioinformatics pipelines. Accessing metadata in the artifacts also requires full Qiime2 installation. Qiime Artifact eXtractor (qax) allows users to easily interface with Qiime2 artifacts from the command line, without needing the full Qiime2 environment installed (or activated).

Roundtable Review: Guilty Pleasures

This roundtable review of Arielle Zibrak's book Guilty Pleasures inaugurates what we hope to be a more dynamic, interactive format of exchange that works in tandem with traditional book reviews. In a (still not quite post–) COVID-19 pandemic world, new forms of cultural discourse have emerged, breaking down long-held, albeit already fluid, boundaries between public and private spaces; collective and individual identities; conventional and newly minted modes of interaction, communication, and scholarship. Guilty Pleasures brilliantly thematizes and embodies the need to revise the rigid boundaries of scholarly conversation. Hailing from the author's reflection on her own culture of reading femme fictions as a rite of passage into a world of “guilty pleasures”—such as romance novels, romantic comedies, and popular, female-centered television shows—Guilty Pleasures deftly weaves the nineteenth century with gender studies, cultural critique, and affect theory. With a candid, conversational style, the book bridges academic and popular writing in a way that engages the reader to do the same, broaching such important questions as the nature of pleasure, the experience of guilt, and structures of love, sex, and gender.In what follows, Sarah Danielle Allison (Loyola University), Rita Dashwood (Edge Hill University), and Melissa Gniadek (University of Toronto) join author Arielle Zibrak (University of Wyoming) in an incisive discussion of Guilty Pleasures.

Interoperability between Building Information Modelling (BIM) and Building Energy Model (BEM)

Building information modelling (BIM) is the first step towards the implementation of the industrial revolution 4.0, in which virtual reality and digital twins are key elements. At present, buildings are responsible for 40% of the energy consumption in Europe and, so, there is a growing interest in reducing their energy use. In this context, proper interoperability between BIM and building energy model (BEM) is paramount for integrating the digital world into the construction sector and, therefore, increasing competitiveness by saving costs. This paper evaluates whether there is an automated or semi-automated BIM to BEM workflow that could improve the building design process. For this purpose, a residential building and a warehouse are constructed using the same BIM authoring tool (Revit), where two open schemas were used: green building extensible markup language (gbXML) and industry foundation classes (IFC). These transfer files were imported into software compatible with the EnergyPlus engine—Design Builder, Open Studio, and CYPETHERM HE—in which simulations were performed. Our results showed that the energy models were built up to 7.50% smaller than in the BIM and with missing elements in their thermal envelope. Nevertheless, the materials were properly transferred to gbXML and IFC formats. Moreover, the simulation results revealed a huge difference in values between the models generated by the open schemas, in the range of 6 to 900 times. Overall, we conclude that there exists a semi-automated workflow from BIM to BEM which does not work well for big and complex buildings, as they present major problems when creating the energy model. Furthermore, most of the issues encountered in BEM were errors in the transfer of BIM data to gbXML and IFC files. Therefore, we emphasise the need to improve compatibility between BIM and model exchange formats by their developers, in order to promote BIM–BEM interoperability.

Support NNEF execution model for NNAPI

With growing applications such as image recognition, speech recognition, ADAS, and AIoT, artificial intelligence (AI) frameworks are becoming popular in various industries. Currently, many choices for neural network frameworks exist for executing AI models in applications, especially for training/inference purposes, including TensorFlow, Caffe, MXNet, PyTorch, Core ML, TensorFlow Lite, and NNAPI. With so many different emerging frameworks, exchange formats are needed for different AI frameworks. Given this requirement, the Khronos group created a standard draft known as the Neural Network Exchange Format (NNEF). However, because NNEF is new, conversion tools for various AI frameworks that would allow the exchange of various AI frameworks remain missing. In this work, we fill this gap by devising NNAPI conversion tools for NNEF. Our work allows NNEF to execute inference tasks on host and Android platforms and flexibly invokes Android neural networks through the API (NNAPI) on the Android platform to speed up inference operations. We invoke NNAPI by dividing the input NNEF model into multiple submodels and let NNAPI execute these submodels. We develop an algorithm named BFSelector that is based on a classic breadth-first search and includes cost constraints to determine how to divide the input model. Our preliminary experimental results show that our support of NNEF on NNAPI can obtain a speedup of 1.32 to 22.52 times over the baseline for API 27 and of 4.56 to 211 times over the baseline for API 28, where the baseline is the NNEF-to-Android platform conversion without invoking NNAPI. The experiment includes AI models such as LeNet, AlexNet, MobileNet_V1, MobileNet_V2, VGG-16, and VGG-19.

The glycoconjugate ontology (GlycoCoO) for standardizing the annotation of glycoconjugate data and its application.

Recent years have seen great advances in the development of glycoproteomics protocols and methods resulting in a sustainable increase in the reporting proteins, their attached glycans and glycosylation sites. However, only very few of these reports find their way into databases or data repositories. One of the major reasons is the absence of digital standard to represent glycoproteins and the challenging annotations with glycans. Depending on the experimental method, such a standard must be able to represent glycans as complete structures or as compositions, store not just single glycans but also represent glycoforms on a specific glycosylation side, deal with partially missing site information if no site mapping was performed, and store abundances or ratios of glycans within a glycoform of a specific site. To support the above, we have developed the GlycoConjugate Ontology (GlycoCoO) as a standard semantic framework to describe and represent glycoproteomics data. GlycoCoO can be used to represent glycoproteomics data in triplestores and can serve as a basis for data exchange formats. The ontology, database providers and supporting documentation are available online (https://github.com/glycoinfo/GlycoCoO).

Erfahrungen bei der Anwendung einer interprofessionellen Anamnese im Krankenhaus.

This article describes the experiences of 19 nurses and physicians in an acute care hospital before and after the introduction of an interprofessional anamnesis. The aim was to show whether and how interprofessional cooperation changed during the ten months study period. The data are based on three group discussions at three different times with six to seven newly recruited participants in an interprofessional composition. The data analysis was carried out using the documentary method after Bohnsack. The group discussions document different phases of a developing interprofessional cooperation. By recognizing different professional perspectives and process structures, areas of responsibility could be clarified and trust could be built. This enabled the participants to benefit from the new cooperation and to introduce further common improvement requests. An interprofessionally developed working tool, such as shared instruments for taking and recording the anamnesis, can have a positive influence on interprofessional cooperation. Interprofessional exchange formats appear to have a beneficial effect on this development process.

Utilizing cloud FPGAs towards the open neural network standard

Accurate and efficient Machine Learning algorithms are of vital importance to many problems, especially on classification or clustering tasks but need a universal AI model standard. Unifying machine learning models into a common ecosystem can lead to less development time and better framework interoperability. ONNX (Open Neural Network Exchange Format) is a popular open format to represent deep learning models so that AI developers can more easily move models between state-of-the-art tools. On top of that, hardware companies such as Nvidia or Intel try to keep up with this trend and produce hardware-optimized runtimes (i.e. for CPUs, GPUs, FPGAs) that can handle these open format AI models like ONNX. That enables developers to leverage an heterogeneous mix of hardware and use whichever AI framework they prefer. However, FPGAs have a more challenging solution strategy which as a platform it is also proven to address these kind of problems very efficiently in terms of performance and power. This work is based on an early development stage project which is called HLS4ML originally created for particle physics applications via the automatic generation of neural networks (NNs) for embedded Xilinx FPGAs. Our work involves a hardware-aware NN training and a generalized optimization scheme on top of HLS4ML that boosts the performance and power efficiency of this package and adds functionality for cloud FPGA firmware from any NN model. We start from the FPGA-oriented training of a model in Keras for image recognition, converting into the ONNX open format then porting and optimizing it for cloud FPGAs using a novel scheme with optimizations in host, memory and kernels while using multiple levels of network precision. To the best of our knowledge this is a novel approach that also achieves a speed-up of up to 102× over single CPU in performance and up to 5.5× over GPU in performance/watt.

Prototypical Clinical Trial Registry Based on Fast Healthcare Interoperability Resources (FHIR): Design and Implementation Study.

BackgroundClinical trial registries increase transparency in medical research by making information and results of planned, ongoing, and completed studies publicly available. However, the registration of clinical trials remains a time-consuming manual task complicated by the fact that the same studies often need to be registered in different registries with different data entry requirements and interfaces.ObjectiveThis study investigates how Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) may be used as a standardized format for exchanging and storing clinical trial records.MethodsWe designed and prototypically implemented an open-source central trial registry containing records from university hospitals, which are automatically exported and updated by local study management systems.ResultsWe provided an architecture and implementation of a multisite clinical trials registry based on HL7 FHIR as a data storage and exchange format.ConclusionsThe results show that FHIR resources establish a harmonized view of study information from heterogeneous sources by enabling automated data exchange between trial centers and central study registries.

Recent Trends in JSON Filters

JavaScript Object Notation is a text-based data exchange format for structuring data between a server and web application on the client-side. It is basically a data format, so it is not limited to Ajax-style web applications and can be used with API’s to exchange or store information. However, the whole data never to be used by the system or application, It needs some extract of a piece of requirement that may vary person to person and with the changing of time. The searching and filtration from the JSON string are very typical so most of the studies give only basics operation to query the data from the JSON object. The aim of this paper to find out all the methods with different technology to search and filter with JSON data. It explains the extensive results of previous research on the JSONiq Flwor expression and compares it with the json-query module of npm to extract information from JSON. This research has the intention of achieving the data from JSON with some advanced operators with the help of a prototype in json-query package of NodeJS. Thus, the data can be filtered out more efficiently and accurately without the need for any other programming language dependency. The main objective is to filter the JSON data the same as the SQL language query.