JavaScript Object Notation Format Research Articles

Otargen: GraphQL-based R Package for Tidy Data Accessing and Processing From Open Targets Genetics.

Open Target Genetics is a comprehensive resource portal that offers variant-centric statistical evidence, enabling the prioritization of causal variants and the identification of potential drug targets. The portal uses GraphQL technology for efficient data query and provides endpoints for programmatic access for R and Python users. However, leveraging GraphQL for data retrieval can be challenging, time-consuming, and repetitive, requiring familiarity with the GraphQL query language and processing outputs in nested JSON(JavaScript Object Notation) format into tidy data tables. Therefore, developing open-source tools are required to simplify data retrieval processes to integrate valuable genetic information into data-driven target discovery pipelines seamlessly. otargen is an open-source R package designed to make data retrieval and analysis from the Open Target Genetics portal as simple as possible for R users. The package offers a suite of functions covering all query types, allowing streamlined data access in a tidy table format. By executing only a single line of code, theotargen users avoid the repetitive scripting of complex GraphQL queries, including the post-processing steps. In addition, otargen contains convenient plotting functions to visualize and gain insights from complex data tables returned by several key functions. otargen is available at https://amirfeizi.github.io/otargen/.

A decay database of coincident γ−γ and γ−X-ray branching ratios for in-field spectroscopy applications

Current fieldable spectroscopy techniques often use single detector systems heavily impacted by interferences from intense background radiation fields. These effects result in low-confidence measurements that can lead to misinterpretation of the collected spectrum. To help improve interpretation of the fission products and short-lived radionuclides produced in a composite sample, a coincidence-database is being developed in support of a robust portable and X-ray coincidence detector system concurrently under development at the Pacific Northwest National Laboratory for in-field deployment. Hitherto, no database exists containing coincident γ−γ and γ−X-ray branching-ratio intensities on an absolute scale that will greatly enhance isotopic identification for in-field applications. As part of this project, software has been developed to parse all radioactive-decay data sets from the Evaluated Nuclear Structure Data File (ENSDF) archive to enable translation into a more useful JavaScript Object Notation (JSON) formats that more readily supports query-based data manipulation. The coincident database described in this work is the first of its kind and contains coincidence γ−γ and γ−X-ray intensities and their corresponding uncertainties, together with auxiliary metadata associated with each decay data set. The new JSON format provides a convenient and portable means of data storage that can be imported into analysis frameworks with relatively low overhead allowing for meaningful comparison with measured data.

Auto JSON: An Automatic Transformation Model for Converting Relational Database to Non-relational Documents

In recent days, the demand for dealing large set of distributed data obsoletes the relational database and its structured query language (SQL) solutions in practice and paves the way for novel solutions in the name of non-relational database as not-only SQL (NoSQL). The NoSQL offers dynamic, flexible, scalable, highly available, greater performance and near real-time access to the distributed nature of voluminous data used for current industrial applications. Apart from these giant features of NoSQL, the SQL is still found to be in operation because of its popularity and standard. This paper projected an algorithm to convert the relational documents of MySQL into any document oriented NoSQL databases automatically without destructing the existing relational database setup and installing the NoSQL from scratch in the core machines. Java Script Object Notation (JSON) is a human readable data interchange format, being used in web development. The characteristics of JSON widened its use cases from web development to database storage. The Mongo DB, one of the most popular document oriented NoSQL adapts JSON format for its storage. The proposed algorithm is built based on its schema definition and the performance is captured through evaluating it against a sample database from hospital management system. The findings are discussed with great interest of addressing the challenges and revealing the scope for improvement.

Rancangan Pembuatan API Website Data Tanaman Obat Dan Langka Kabupaten Kediri

The design of a website for information on medicinal and rare plants in Kediri Regency aims to provide convenience in obtaining information easily and quickly. The design of this website uses the Software Development Life Cycle (SLDC) Waterfall method with the stages of identification, analysis, design, implementation and testing. The web-based Application Programming Interface (API) uses Node.js as a runtime environment for the JavaScript programming language using the Express.js framework. The Application Programming Interface (API) is used as a liaison between the client and server, testing the endpoint Application Programming Interface (API) using Postman tools by displaying the results of the test in the form of data in JSON (JavaScript Object Notation) format which is used to store and transfer data

Bridging Data Pasien Rawat Inap Dengan INA-CBG’s (Indonesian Case Base Groups’s)

Abstract— Integration and acceleration of data transactions is a very important issue to be discussed in the era of integrated information technology development. This problem is the reason for making the system interact with each other quickly. Indonesian Case Base Groups (INA-CBG's) is an application used to process claims for National Health Insurance (JKN) participants from the Hospital. Every hospital is required to send patient data through INACBG's. However, current data claims for inpatients are still done manually. This manual process will make officers enter patient data into the main system and INACBG's. This results in the efficiency of work performed by hospital staff. In addition, the data entered is not automatic because there is a delay when entering data into the main system and INACBG's. Development of an Inpatient Information System that is integrated with INA-CBG's using JavaScript Object Notation (JSON). This format can send inpatient claim data to the INACBG's application in the form of an array. The JSON format does not have a standard format for writing, so it can be faster and more flexible in sending data. With an integrated system between the main system and INACBG's, it can increase the efficiency of processing data claims to INACBG's.

Adamant: a JSON schema-based metadata editor for research data management workflows.

The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant.

Adamant: a JSON schema-based metadata editor for research data management workflows

The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant.

Adamant: a JSON schema-based metadata editor for research data management workflows.

The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant.

Image‐based locating and guiding for unmanned aerial vehicles using scale invariant feature transform, speeded‐up robust features, and oriented fast and rotated brief algorithms

AbstractThis study provides a method for determining the location information from a photograph taken by an Unmanned Aerial Vehicle (UAV). In today's defense industry, the goal is to design a reliable navigation system that can operate even when the Internet and GPS systems are unavailable. In the proposed system, it is expected that there is an image database in which each image has its own metadata in JavaScript Object Notation format that defines the geolocation information for the corresponding image. In real‐time, UAV flies captures an image and uses a matching algorithm to compare it with each and every photo in the database. The image with the highest match rate in the database and its metadata is returned. The UAV extracts its own location information from the metadata. For image matching, Scale Invariant Feature Transform, Speeded‐Up Robust Features, and Oriented FAST and Rotated BRIEF algorithms are used. The proposed system is tested and evaluated by using a real‐world dataset obtained from Flickr's city images. The proposed approach is proved to work with a success rate of 97.14%.

Development of Bot for Microservices Server Monitoring Using Life Cycle Approach to Network Design Method

This study was conducted on the emergency response system that has been implemented in Demak, Kendal and Batang districts, namely Tanggapin. This system provides services in the form of reporting and actions, as well as information about the health sector, from the availability of hospital rooms to the availability of blood at PMI. Tanggapin uses a mobile-based and web-based platform, where the web is used as a medium for operators to input data and validate incoming reports. Due to complex system services with various supporting features, it requires a microservices architecture to operate independently and in a distributed manner. Because of this dynamic system, realtime monitoring support for server performance is needed via Telegram Bot. The monitoring system was built using the PPDIOO Lifecycle Approach to Network Design and Implementation method because it is reliable and the flow of a process never breaks. The format used to exchange data uses the JSON (Javascript Object Notation) format. This study shows that the monitoring system run well because every test carried out gives the expected results, namely the admin receives a warning message via the Telegram Bot.

A Digital Perspective on Machine Tool Calibration

Machine tool calibration and subsequent controller-based compensation are industrially established and research-intensive techniques used to monitor and increase the volumetric performance in high-precision manufacturing. Moreover, a variety of interim performance checks and integrated sensor approaches have been developed to predict volumetric performance degradation and avoid an economically undesirable downtime. However, the fragmentation of data acquisition and management limits the potential for additional insights with respect to the value creation based on existing methods in the field of machine tool calibration. The authors reviewed the former from the perspective of data sources according to the frequency of their contribution to the digital twin of a machine tool, adopting a digital view regarding machine tool calibration within theInternet of Productionconcept. The latter proposes a semantic separation of cyber physical production systems into four layers: data sources, data access and provisioning, storage and analytics, and user respective agent feedback. To achieve a common representation across different layers, devices, and industrial Internet protocols, a model-based abstraction layer is required, which must be compatible with existing standards within the field, e.g., the ISO 230 series. Utilizing different Internet of Production architectures and platforms, a multitude of parallel analytic applications and an evaluation of complex models are enabled owing to the availability of ample computing resources, among which the machine tool’s numerical controller takes the role of an edge-device injecting the feedback into the production process. A proof-of-concept of a digital approach to machine tool calibration data storage and processing was established based on the software prototypeVoluSoft, which implements an ISO 230-1:2012 based abstraction layer in JavaScript Object Notation format, and an evaluation of the kinematic models to estimate the volumetric performance at the functional point. Apart from generating compensation tables, the results are used to project the expected deviation at the tool tip to the computer-aided design-model of a work piece, correlate the error motions using the temperature data acquired by integrated sensors, and estimate the contribution of the volumetric performance limitation to the uncertainty budget of on-machine measurements.

An effective biomedical data migration tool from resource description framework to JSON.

Resource Description Framework (RDF) is widely used for representing biomedical data in practical applications. With the increases of RDF-based applications, there is an emerging requirement of novel architectures to provide effective supports for the future RDF data explosion. Inspired by the success of the new designs in National Center for Biotechnology Information dbSNP (The Single Nucleotide Polymorphism Database) for managing the increasing data volumes using JSON (JavaScript Object Notation), in this paper we present an effective mapping tool that allows data migrations from RDF to JSON for supporting future massive data explosions and releases. We firstly introduce a set of mapping rules, which transform an RDF format into the JSON format, and then present the corresponding transformation algorithm. On this basis, we develop an effective and user-friendly tool called RDF2JSON, which enables automating the process of RDF data extractions and the corresponding JSON data generations.

Tamper-Resistant Mobile Health Using Blockchain Technology.

BackgroundDigital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials.ObjectiveThe aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network.MethodsWe developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults.ResultsElectronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network.ConclusionsBlockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may provide a novel solution that enables both accessibility and data transparency without a third party such as a contract research organization.

JavaScript Object Notation (JSON) data serialization for IFC schema in web-based BIM data exchange

Abstract In the building industry, building data such as objects and processes are described in Industry Foundation Classes (IFC) data model schema to support a neutral data exchange format for BIM tools interoperability. While IFC specification has been encoded in ifcXML format by buildingSMART to support XML-based data transmission, there is a lack of studies on the implementation of IFC specification using JavaScript Object Notation (JSON) serialization. JSON is a key-value style lightweight data exchange format that has higher parsing efficiency than XML and due to the inadequacies of XML, JSON has been widely used in Web applications, specifically in Asynchronous JavaScript and XML (AJAX) Web services. This paper highlights the need for JSON implementation of IFC specification and introduces ifcJSON Schema and its data content. The main objective of this study is to outline how IFC specification can be represented in JSON format. Therefore, the study explains the implementation of the IFC standard as a JSON schema to guide the creation of JSON documents. The ifcJSON documents can be used for web-based data transfer as an alternative to XML documents. Since current IFC specification release is IFC4 Add1, the implementation of ifcJSON4 schema is specified and guidelines for generating and validating ifcJSON documents are described. Additionally, this paper implements ifcJSON4 schema in a use case within the precast concrete domain by indicating the data content for a precast building element with its corresponding geometry representation, product placement, and owner history data. The analysis of results indicates that ifcJSON4 schema developed in this paper is a valid JSON schema that can guide the creation of valid ifcJSON documents to be used for web-based data transfer and to improve interoperability of Cloud-based BIM applications.