GpJSON: High-Performance JSON Data Processing on GPUs

JavaScript Object Notation (JSON) and its variants have gained great popularity in recent years. Unfortunately, the performance of their analytics is often dragged down by the expensive JSON parsing. To address this, recent work has shown that building bitwise indices on JSON data, called structural indices , can greatly accelerate querying. Despite its promise, the existing structural index construction does not scale well as records become larger and more complex, due to its (inherently) sequential construction process and the involvement of costly memory copies that grow as the nesting level increases. To address the above issues, this work introduces Pison - a more memory-efficient structural index constructor with supports of intra-record parallelism. First, Pison features a redesign of the bottleneck step in the existing solution. The new design is not only simpler but more memory-efficient. More importantly, Pison is able to build structural indices for a single bulky record in parallel, enabled by a group of customized parallelization techniques. Finally, Pison is also optimized for better data locality, which is especially critical in the scenario of bulky record processing. Our evaluation using real-world JSON datasets shows that Pison achieves 9.8X speedup (on average) over the existing structural index construction solution for bulky records and 4.6X speedup (on average) of end-to-end performance (indexing plus querying) over a state-of-the-art SIMD-based JSON parser on a 16-core machine.

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JSON (JavaScript Object Notation) is a lightweight data-interchange format for the Internet. JSON is built on two structures: (1) a collection of name/value pairs and (2) an ordered list of values (http://www.json.org/). Because of this simple approach, JSON is easy to use and it has the potential to be the data interchange format of choice for the Internet. Similar to XML, JSON schemas allow nested structures to model hierarchical data. As data interchange over the Internet increases exponentially due to cloud computing or otherwise, redundancy free JSON data are an attractive form of communication because they improve the quality of data communication through eliminating update anomaly. Nested Normal Form, a normal form for hierarchical data, is a precise characterization of redundancy. A nested table, or a hierarchical schema, is in Nested Normal Form if and only if it is free of redundancy caused by multivalued and functional dependencies. Using Nested Normal Form as a guide, this paper introduces a JSON schema design methodology that begins with UML use case diagrams, communication diagrams and class diagrams that model a system under study. Based on the use cases’ execution frequencies and the data passed between involved parties in the communication diagrams, the proposed methodology selects classes from the class diagrams to be the roots of JSON scheme trees and repeatedly adds classes from the class diagram to the scheme trees as long as the schemas satisfy Nested Normal Form. This process continues until all of the classes in the class diagram have been added to some JSON scheme trees.

We present a draft Minimum Information About Geospatial Information System (MIAGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The draft MIAGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. The associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data formats plus options for extraction from user-specified JSON formats. We also demonstrate their use in crafting two example depositions of ArcGIS generated maps. We hope this draft MIAGIS standard along with the supporting miagis Python package will assist in establishing a GIS standards group that will develop the draft into a full standard for the wider GIS community as well as a future public repository for GIS datasets.

External service integration and adherence to industry standards has become ever more important for collections data management platforms. External APIs (Application Programming Interfaces), allow for the development of bi-directional data flows critical to service integration. In contrast to service-oriented backend APIs, public APIs must have continually up-to-date, comprehensive documentation that covers common use cases, on-the-fly request validation, and meaningful error messages. OpenAPI (OpenAPI Initiative 2021), a machine-readable API documentation specification can help significantly with testing and maintenance, and libraries can be used to automate common maintenance tasks. Specify 7 is a biological collections data management platform developed by the Specify Collections Consortium (Specify Software Consortium 2021). This presentation summarizes the challenges and lessons learned with publishing the existing backend Specify 7 API to a public-facing external API. Each Specify 7 API is composed of 200 resources. A standard set of CRUD (Create, Read, Update, Delete) operations is provided for each resource for client interaction with a group of service-based endpoints for bulk operations such as file uploads, file-based data imports, and attachment manipulation. To support the migration, we developed a custom library to enhance request validation. Parameter validation is extended through a real-time comparison against the existing schema and data. The library is available to the community under a MIT license on GitHub (https://github.com/specify/open_api_tools/). In this presentation, we will close with an overview of the next steps for the Specify 7 public API. These include: An update to the latest OpenAPI specification, version 3.1. The latest version aims to increase compatibility with the Javascript Object Notation (JSON) Schema specification, and thus would allow us to use JSON Schema (IETF Trust 2021) validation frameworks. An in-depth evaluation of GraphQL for its ability to force all endpoints to be strongly typed and automatic validation of request parameters and response objects. An update to the latest OpenAPI specification, version 3.1. The latest version aims to increase compatibility with the Javascript Object Notation (JSON) Schema specification, and thus would allow us to use JSON Schema (IETF Trust 2021) validation frameworks. An in-depth evaluation of GraphQL for its ability to force all endpoints to be strongly typed and automatic validation of request parameters and response objects.

BackgroundApplication Programming Interfaces (APIs) are now widely used to distribute biological data. And many popular biological APIs developed by many different research teams have adopted Javascript Object Notation (JSON) as their primary data format. While usage of a common data format offers significant advantages, that alone is not sufficient for rich integrative queries across APIs.ResultsHere, we have implemented JSON for Linking Data (JSON-LD) technology on the BioThings APIs that we have developed, MyGene.info, MyVariant.info and MyChem.info. JSON-LD provides a standard way to add semantic context to the existing JSON data structure, for the purpose of enhancing the interoperability between APIs. We demonstrated several use cases that were facilitated by semantic annotations using JSON-LD, including simpler and more precise query capabilities as well as API cross-linking.ConclusionsWe believe that this pattern offers a generalizable solution for interoperability of APIs in the life sciences.

One of main advantages of JSON (JavaScript Object Notation) is to represent structured as well as semi-structured data at the same time. Although the existing SQL/JSON standard specifies the way, how queries in relation to exact search can be preformed, it lacks the support for queries concerning full-text search. In this article we propose a set of design goals that full-text search extension of the SQL/JSON language should support. Additionally, the given set is valid for any full-text search language in relation to JSON documents. Also, we discuss full-text language extensions implemented in relational database systems concerning JSON documents and answer the question to what extent the extensions are supported by these systems.

The massive amounts of data processed in modern computational systems is becoming a problem of increasing importance. This data is commonly stored directly or indirectly through the use of data exchange languages, such as JavaScript Object Notation (JSON), for human-readable platform agnostic access. This paper focuses on describing and analyzing SJSON, a library that explores succinct representations of JSON documents as a means to achieve reduced memory usage of files in main memory, and to permit the compression of JSON files stored in disk. In SJSON we represent the document structure with succinct trees, as opposed to the usual pointer-based implementation. Furthermore, the remaining raw data are organized in arrays of attributes and values. Attributes are stripped of redundancies and stored in a simple contiguous array, while values are represented through a bit string indexed array. The scheme here proposed is then evaluated with respect to a number of metrics comparing its performance with popular libraries, anssd possible improvements to the representation are then presented.

Due to the popularity of the JavaScript Object Notation (JSON), a need has arisen for the creation of schema documents for the purpose of validating the content of other JSON documents. Existing automatic schema generation tools, however, have not adequately considered the scenario of an array of JSON objects with different types of structures. These tools work off the assumption that all objects have the same structure, and thus, only generate a single schema combining them together. To address this problem, this thesis looks to improve upon schema generation for heterogeneous JSON arrays. We develop an algorithm to determine a set of keys that identifies what type of structure each element has. These keys are then used as the basis for a schema decision tree. The objective of this tree is to help in the validation process by allowing each element to be compared against a single, more tailored, schema.

With the continuous development of information technology, the application market has also gradually innovated. Light applications are favored by people because of its small footprint, easy to use, and fast running. JSON (JavaScript Object Notation) is considered by developers to be an ideal data exchange language because of its simplicity and ease of use, and is widely used in Web development.Compared with XML, JSON has more advantages in Web data exchange processing. JSON is used to cache data, which is convenient for storing complex data, and is more conducive to client parsing and use.

I previously wrote about the JavaScript Object Notation (JSON) which has become a de facto standard for sharing data by web services. I personally still prefer something using the Resource Description Framework (RDF) because of its clear link to ontologies, but perhaps JSON-LD combines the best of both worlds. The Open PHACTS API support various formats and this JSON is the default format used by the ops.js library.

<p>Web data extraction is the process of extracting user required information from web page. The information consists of semi-structured data not in structured format. The extraction data involves the web documents in html format. Nowadays, most people uses web data extractors because the extraction involve large information which makes the process of manual information extraction takes time and complicated. We present in this paper WEIDJ approach to extract images from the web, whose goal is to harvest images as object from template-based html pages. The WEIDJ (Web Extraction Image using DOM (Document Object Model) and JSON (JavaScript Object Notation)) applies DOM theory in order to build the structure and JSON as environment of programming. The extraction process leverages both the input of web address and the structure of extraction. Then, WEIDJ splits DOM tree into small subtrees and applies searching algorithm by visual blocks for each web page to find images. Our approach focus on three level of extraction; single web page, multiple web page and the whole web page. Extensive experiments on several biodiversity web pages has been done to show the comparison time performance between image extraction using DOM, JSON and WEIDJ for single web page. The experimental results advocate via our model, WEIDJ image extraction can be done fast and effectively.</p>

Abstract. In this paper we investigate the benefits of binary data serialization as a means of storing and sharing large amounts of geospatial data in an interoperable way. De-facto text-based exchange encodings typically exposed by modern Application Programming Interfaces (APIs), including eXtensible Markup Language (XML) and JavaScript Object Notation (JSON), are generally inefficient for an increasingly higher number of applications due to their inflated volumes of data, low speed and the high computational cost for parsing and processing. In this work we consider comparisons of JSON/Geospatial JSON (GeoJSON) and two popular binary data encodings (Protocol Buffers and Apache Avro) for storing and sharing geospatial data. Using a number of experiments, we illustrate the advantages and disadvantages of both approaches for common workflows that make use of geospatial data encodings such as GeoPackage and GeoJSON. The paper contributes a number of practical recommendations around the potential for binary data serialization for interoperable (geospatial) data storage and sharing in the future.

JavaScript Object Notation (JSON) has evolved to the de-facto standard file format in the web used for application configuration, cross- and same-origin data exchange, as well as in Single Sign-On (SSO) protocols such as OpenID Connect. To protect integrity, authenticity, and confidentiality of sensitive data, JavaScript Object Signing and Encryption (JOSE) was created to apply cryptographic mechanisms directly in JSON messages.We investigate the security of JOSE and present different applicable attacks on several popular libraries. We introduce JOSEPH (JavaScript Object Signing and Encryption Pentesting Helper) -- our newly developed Burp Suite extension, which automatically performs security analysis on targeted applications. JOSEPH's automatic vulnerability detection ranges from executing simple signature exclusion or signature faking techniques, which neglect JSON message integrity, up to highly complex cryptographic Bleichenbacher attacks, breaking the confidentiality of encrypted JSON messages. We found severe vulnerabilities in six popular JOSE libraries. We responsibly disclosed all weaknesses to the developers and helped them to provide fixes.

Application Programming Interface (API) merupakan antarmuka yang dibangun
\noleh pengembang sistem supaya sebagian atau keseluruhan fungsi sistem dapat
\ndiakses secara programmatis. Sementara Representational State Transfer (REST)
\nmerupakan salah satu gaya arsitektur dari pengembangan API yang menggunakan
\nHypertext Transfer Protocol (HTTP) dalam melakukan komunikasi data. Penelitian
\nini mengimplementasikan gaya arsitektur REST dalam pengembangan API sebagai
\nback-end sistem informasi administrasi pasien klinik perawatan kulit. API yang
\ndikembangkan menggunakan Javascript Object Notation (JSON) sebagai standar
\nformat dalam komunikasi data serta JSON Web Token (JWT) sebagai kode
\notentikasi pengguna pengguna. Penelitian ini menunjukkan bahwa pengembangan
\nAPI berhasil dilakukan pada administrasi pasien klinik perawatan kulit dan REST
\nyang diterapkan mempermudah pengembangan struktur API. Penelitian ini
\nmenghasilkan back-end sistem informasi administrasi pasien klinik perawatan kulit
\nberbasis REST API. API diuji dalam tiga tahap yakni pengujian JWT pada backend
\nserver berjumlah banyak, pengujian API dengan metode Equivalence
\nPartitioning dan pengujian fungsional sistem.
\nKata kunci: application programming interface (api), representational state
\ntransfer (rest), hypertext transfer protocol (http), javascript object
\nnotation (json), json web token (jwt).
\n
\n
\nABSTRACT
\n
\nApplication Programming Interface (API) is an interface built by system developer
\nso some or entire functions of the system can programmatically be accessed.
\nRepresentational State Transfer (REST) is one of API development architectural
\nstyle that uses Hypertext Transfer Protocol (HTTP) for data communication. This
\nresearch implemented REST in developing API as the back-end of the skincare
\nclinic patient information system. API was developed using Javascript Object
\nNotation (JSON) as the standard format for data communication and JSON Web
\nToken (JWT) as user authentication code. This research indicates that the
\ndevelopment of API successfully performed on the patient administration of skin
\ncare clinic and implementation of REST makes it easy to develop API structures.
\nThis research produced REST API-based back-end for the patient administration
\ninformation system of skin care clinic. API was tested in three stages: JWT testing
\non multiple back-end servers, API testing with Equivalence Partitioning and system
\nfunctional testing.
\nKeywords : application programming interface (api), representational state transfer
\n(rest), hypertext transfer protocol (http), javascript object notation
\n(json), json web token (jwt).