Time-varying JSON data are being used and exchanged in various today’s application frameworks like IoT platforms, Web services, cloud computing, online social networks, and mobile systems. However, ...in the state-of-the-art of JSON data management, there is neither a consensual nor a standard language for updating (i.e., inserting, modifying, and deleting) temporal JSON data, like the TSQL2 or SQL:2016 languages for temporal relational data. Moreover, existing JSON-based NoSQL DBMSs (e.g., MongoDB, Couchbase, CouchDB, OrientDB, and Riak) and both commercial relational DBMSs (e.g., IBM DB2 12, Oracle 19c, and MS SQL Server 2019) and open-source ones (e.g., PostgreSQL 15, and MySQL 8.0) supporting JSON documents do not provide any facility for maintaining temporal JSON data. Also in our previously proposed temporal JSON framework, called τJSchema, there was no feature for temporal JSON instance updates. For these reasons, we propose in this article a temporal update language, named τJUpdate (Temporal JUpdate), for JSON data in the τJSchema environment. We define it as a temporal extension of our previously introduced non-temporal JSON update language, named JUpdate (JSON Update). Both the syntax and the operational semantics of the data modification operations of JUpdate have been extended to support temporal aspects. τJUpdate allows to specify temporal JSON updates in an expressive and user-friendly manner, and to efficiently execute them in the τJSchema environment.
The ThermoML Archive is a subset of Thermodynamics Research Center (TRC) data holdings corresponding to cooperation between NIST TRC and five journals: Journal of Chemical Engineering and Data (ISSN: ...1520‐5134), The Journal of Chemical Thermodynamics (ISSN: 1096‐3626), Fluid Phase Equilibria (ISSN: 0378‐3812), Thermochimica Acta (ISSN: 0040‐6031), and International Journal of Thermophysics (ISSN: 1572‐9567). Data from initial cooperation (around 2003) through the 2019 calendar year are included. The archive has undergone a major update with the goal of improving the FAIRness and user experience of the data provided by the service. The web application provides comprehensive property browsing and searching capabilities; searching relies on a RESTful API provided by the Cordra software for managing digital objects. JSON files with a schema derived from ThermoML are provided as an additional serialization to lower the barrier to programmatic consumption of the information, for stakeholders who may have a preference of JSON over XML. The ThermoML and JSON files for all available entries can be downloaded from data.nist.gov (https://data.nist.gov/od/id/mds2-2422).
The NIST Thermodynamics Research Center critically evaluates experimental thermophysical and thermochemical property data. This work uses the ThermoML XSD established by IUPAC projects to transform a large slice (corresponding to five journals that cooperate with NIST TRC during the publication process) of highly‐structured database (SOURCE) information into XML and JSON files contained in a web application that makes the resource more Findable, Accessible, Interoperable, and Reusable. All json and xml files are available for download at https://data.nist.gov/od/id/mds2-2422.
Nowadays, ontologies, which are defined under the OWL 2 Web Ontology Language (OWL 2), are being used in several fields like artificial intelligence, knowledge engineering, and Semantic Web ...environments to access data, answer queries, or infer new knowledge. In particular, ontologies can be used to model the semantics of big data as an enabling factor for the deployment of intelligent analytics. Big data are being widely stored and exchanged in JavaScript Object Notation (JSON) format, in particular by Web applications. However, JSON data collections lack explicit semantics as they are in general schema-less, which does not allow to efficiently leverage the benefits of big data. Furthermore, several applications require bookkeeping of the entire history of big data changes, for which no support is provided by mainstream Big Data management systems, including Not only SQL (NoSQL) database systems. In this paper, we propose an approach, named τJOWL (temporal OWL 2 from temporal JSON), which allows users (i) to automatically build a temporal OWL 2 ontology of data, following the Closed World Assumption (CWA), from temporal JSON-based big data, and (ii) to manage its incremental maintenance accommodating the evolution of these data, in a temporal and multi-schema environment.
JSON parser, that has been developed, is made of two modules, each dedicated to process structure of either an object or an array. In both modules, building step of document model, that represents ...its structure, is combined with tokenization step. Design and development of algorithm is aimed at improving speed of parsing of documents.
Model-based phylogenetic reconstructions increasingly consider spatial or phenotypic traits in conjunction with sequence data to study evolutionary processes. Alongside parameter estimation, ...visualization of ancestral reconstructions represents an integral part of these analyses. Here, we present a complete overhaul of the spatial phylogenetic reconstruction of evolutionary dynamics software, now called SpreaD3 to emphasize the use of data-driven documents, as an analysis and visualization package that primarily complements Bayesian inference in BEAST (http://beast.bio.ed.ac.uk, last accessed 9 May 2016). The integration of JavaScript D3 libraries (www.d3.org, last accessed 9 May 2016) offers novel interactive web-based visualization capacities that are not restricted to spatial traits and extend to any discrete or continuously valued trait for any organism of interest.
The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties ...searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.
JUpdate: A JSON Update Language Brahmia, Zouhaier; Brahmia, Safa; Grandi, Fabio ...
Electronics,
02/2022, Letnik:
11, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Although JSON documents are being used in several emerging applications (e.g., Big Data applications, IoT, mobile computing, smart cities, and online social networks), there is no consensual or ...standard language for updating JSON documents (i.e., creating, deleting or changing such documents, where changing means inserting, deleting, replacing, copying, moving, etc., portions of data in such documents). To fill this gap, we propose in this paper an SQL-like language, named JUpdate, for updating JSON documents. JUpdate is based on a set of six primitive update operations, which is proven complete and minimal, and it provides a set of fourteen user-friendly high-level operations with a well-founded semantics defined on the basis of the primitive update operations.
The current trend of solutions in storing large amounts of data is using the NoSQL Database. A document stored is one type of NoSQL database that uses the JavaScript Object Notation (JSON) and ...eXtensible Markup Language (XML) data formats in data storage. High Availability database is significant to support cloud-based applications and services. Replication is one solution to maintain the consistency of source data and target data. This study aims to determine the performance of JSON and XML data formats in the document stored NoSQL Database replication process. In this study, ArangoDB, RethinkDB, and MongoDB were chosen for use in the trial process of replication from master-server to slave-server with two different data formats, JSON and XML. Data transfer, CPU usage, memory usage, and execution time are measured in each trial. Based on research and experiments that have been carried out, the JSON data format consumes bandwidth with an average value smaller than the XML data format; this occurs in MongoDB, CouchDB, and RethinkDB. In CPU usage, JSON data format, on average, consumes less CPU compared to the XML data format. This is the case with MongoDB. While on CouchDB and RethinkDB, the average CPU usage for XML and JSON data formats does not show a significant difference. The average memory usage for the JSON data format is smaller than the XML data format. The average execution time of the XML data format a little faster than the JSON data format.
•The Allotrope Simple Model enables rapid standardization of the digital laboratory.•Multiple companies are currently rolling out Allotrope based technologies.•The Allotrope Foundation persisted ...throughout the COVID-19 pandemic and penetrates vertical industries.•A How-To guide to develop Allotrope Simple Models is provided.
The Allotrope Foundation (AF) started as a group of pharmaceutical companies, instrument, and software vendors that set out to simplify the exchange of data in the laboratory. After a decade of work, they released products that have found adoption in various companies. Most recently, the Allotrope Simple Model (ASM) was developed to speed up and widen the adoption. As a result, the Foundation has recently added chemical companies and, importantly, is reworking its business model to lower the entry barrier for smaller companies. Here, we present the proceedings from the Allotrope Connect Fall 2023 conference and summarize the technical and organizational developments at the Foundation since 2020.
Encoding JSON by using Base64 Shaamood, Mohammed
Iraqi journal for electrical and electronic engineering,
6/2021, Letnik:
17, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Transmitting binary data across a network should generally avoid transmitting raw binary data over the medium for several reasons, one would be that the medium may be a textual one and may not accept ...or correctly handle raw bitstream, another would be that some protocols may misinterpret the meaning of the bits and causes a problem or even loss of the data. To make the data more readable and would avoid misinterpretation by different systems and environments, this paper introduces encoding two of the most broadly used data interchange formats, XML and JSON, into the Base64 which is an encoding scheme that converts binary data to an ASCII string format by using a radix-64 representation. This process, will, make the data more readable and would avoid misinterpretation by different systems and environments.
The results reflect that encoding data in Base64 before the transmission will present many advantages including readability and integrity, it will also enable us to transmit binary data over textual mediums, 7 Bit protocols such as SMTP, and different network hardware without risking misinterpretation.
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