19 research outputs found
JUpdate: A JSON Update Language
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
Highway increases concentrations of toxic metals in giant panda habitat
The Qinling panda subspecies (Ailuropoda melanoleuca qinlingensis) is highly endangered with fewer than 350 individuals inhabiting the Qinling Mountains. Previous studies have indicated that giant pandas are exposed to heavy metals, and a possible source is vehicle emission. The concentrations of Cu, Zn, Mn, Pb, Cr, Ni, Cd, Hg, and As in soil samples collected from sites along a major highway bisecting the panda's habitat were analyzed to investigate whether the highway was an important source of metal contamination. There were 11 sites along a 30-km stretch of the 108th National Highway, and at each site, soil samples were taken at four distances from the highway (0, 50, 100, and 300 m) and at three soil depths (0, 5, 10 cm). Concentrations of all metals except As exceeded background levels, and concentrations of Cu, Zn, Mn, Pb, and Cd decreased significantly with increasing distance from the highway. Geo-accumulation index indicated that topsoil next to the highway was moderately contaminated with Pb and Zn, whereas topsoil up to 300 m away from the highway was extremely contaminated with Cd. The potential ecological risk index demonstrated that this area was in a high degree of ecological hazards, which were also due to serious Cd contamination. And, the hazard quotient indicated that Cd, Pb, and Mn especially Cd could pose the health risk to giant pandas. Multivariate analyses demonstrated that the highway was the main source of Cd, Pb, and Zn and also put some influence on Mn. The study has confirmed that traffic does contaminate roadside soils and poses a potential threat to the health of pandas. This should not be ignored when the conservation and management of pandas is considered
Normalization of XML Schema Definitions
An XML schema definition can be organized according to one of the following design styles: \u201cRussian Doll\u201d, \u201cSalami Slice\u201d, \u201cVenetian Blind\u201d, or \u201cGarden of Eden\u201d; otherwise, it is said to be in \u201cBologna\u201d style, which actually means free format. Converting a complex XML schema from a style to another without automated support is not a trivial task. The \u201cGarden of Eden\u201d style can be considered as a normalized format since the definitions of all components (i.e., elements, attributes and types) are global and, thus, can be re-used in the definition of other XML schema constructs (e.g., when expanding the schema or importing it into another schema or using it to define an XML namespace). In this work, we present a Normalize procedure, which can be used to convert any given XML schema to the \u201cGarden of Eden\u201d style, by automatically transforming and rearranging all declarations and definitions it contains
A disciplined approach to temporal evolution and versioning support in JSON data stores
The JSON Schema language lacks explicit support for defining time-varying schemas of JSON documents. Moreover, existing JSON NoSQL databases (e.g., MongoDB, CouchDB) do not provide any support for managing temporal data. Hence, administrators of JSON NoSQL databases have to use ad hoc techniques in order to specify JSON schema for time-varying instances. In this chapter, the authors propose a disciplined approach, named Temporal JSON Schema (tauJSchema), for the temporal management of JSON documents. tauJSchema allows creating a temporal JSON schema from (1) a conventional JSON schema, (2) a set of temporal logical characteristics, for specifying which components of a JSON document can vary over time, and (3) a set of temporal physical characteristics, for specifying how the time-varying aspects are represented in the document. By using such characteristics to describe temporal aspects of JSON data, tauJSchema guarantees logical and physical data independence and provides a low-impact solution since it requires neither updates to existing JSON documents nor extensions to related JSON technologies
Implicit JSON Schema Versioning Driven by Big Data Evolution in the \u3c4JSchema Framework
In JSON-based NoSQL data stores, Big Data instance documents and their JSON schemas must evolve over time to reflect changes in the real world. When a JSON instance document, valid with respect to a JSON schema, is updated giving rise to a new document no longer valid with respect to the schema, the update is usually rejected also resulting in user frustration. In such a case, the JSON schema has to be explicitly changed by an administrator in order to become compliant with the new Big Data format before the update can be effected by the user. The different approach we propose in this work is to privilege the user actions and accept in a transparent way any update he/she wants to apply to the instance documents: violation of the validity of an updated instance document with respect to its JSON schema is automatically detected and schema changes necessary to produce a new schema version compliant with the new Big Data format are automatically applied by the system, producing a new JSON schema version. Hence, in this work, we deal with implicit JSON schema versioning driven by updates to JSON-based Big Data instance documents. Our proposed solution consists in an extension of the \u3c4JSchema (Temporal JSON Schema) framework we previously introduced to create and validate temporal JSON documents and to allow classical temporal JSON schema versioning, to also support implicit JSON schema versioning
Conversion of XML schema design styles with StyleVolution
Purpose \u2013 Any XML schema definition can be organized according to one of the following design styles: \u201cRussian Doll\u201d, \u201cSalami Slice\u201d, \u201cVenetian Blind\u201d and \u201cGarden of Eden\u201d (with the additional \u201cBologna\u201d style actually representing absence of style). Conversion from a design style to another can facilitate the reuse and exchange of schema specifications encoded using the XML schema language. Without any computer-aided engineering support, style conversions must be performed very carefully as they are difficult and error-prone operations. The purpose of this paper is to efficiently deal with such XML schema design style conversions. Design/methodology/approach \u2013 A general approach, named StyleVolution, for automatic management of XML schema design style conversions, is proposed. StyleVolution is equipped with a suite of seven procedures: four for converting a valid XML schema from any other design style to the \u201cGarden of Eden\u201d style, which has been chosen as a normalized XML schema format, and three for converting from the \u201cGarden of Eden\u201d style to any of the other desired design styles. Findings \u2013 Procedures, algorithms and methods for XML schema design style conversions are presented. The feasibility of the approach has been shown through the encoding (using the XQuery language) and the testing (with the Altova XMLSpy 2019 tool) of a suite of seven ready-to-use procedures. Moreover, four test procedures are provided for checking the conformance of a given inputXML schema to a schema design style. Originality/value \u2013 The proposed approach implements a new technique for efficiently managing XML schema design style conversions, which can be used to make any given XML schema file to conform to a desired design style
Schema versioning in tauXSchema-based multitemporal XML repositories
tauXSchema [7] is a framework (a language and a suite of tools) for the creation and validation of time-varying XML documents. A tauXSchema schema is composed of a conventional XML Schema document annotated with physical and logical annotations. All components of a tauXSchema schema (i.e., conventional schema, logical annotations, and physical annotations) can change over time to reflect changes in user requirements or in reference world of the database. Since many applications need to keep track of both data and schema evolution, schema versioning has been long advocated to be the best solution to do this. In this paper, we deal with schema versioning in the tauXSchema framework. More precisely, we propose a set of schema change primitives for the maintenance of logical and physical annotations and define their operational semantics
High-level Operations for Creation and Maintenance of Temporal and Conventional Schema in the \u3c4XSchema Framework
Tauxschema is a framework for constructing and validating time-varying XML documents through the use of a temporal schema. This latter ties together a conventional schema (i.e., A standard XML Schema document) and its corresponding logical and physical annotations, which are stored in an annotation document. Conventional schema and logical and physical annotations undergo changes to respond to changes in user requirements or in the real-world. Consequently, the corresponding temporal schema is also evolving over time. In this paper, we study operations which help designers for changing such schema components. Indeed, we propose three sets of high-level operations for changing temporal schema, conventional schema, and annotations. These high-level operations are based on the low-level operations proposed in our previous work. They are also consistency preserving and more user-friendly than the low-level operations. Besides, we have divided the proposed operations into basic high-level operations (i.e., High-level operations that cannot be defined by using other basic high-level operations) and complex ones
Versioning of conventional schema in the \u3c4xSchema framework
Schema versioning is an indispensable feature for applications using temporal databases and requiring an entire history of data and schema. \u3c4XSchema is an infrastructure for constructing and validating temporal XML documents; but any explicit support for XML schema versioning is offered. A \u3c4XSchema schema is composed of a conventional XML Schema document annotated with physical and logical annotations. All components of a \u3c4XSchema schema can change over time to reflect changes in user requirements or in reference world of the database. In this work, we study versioning of \u3c4XSchema conventional schema: we propose a complete set of low-level primitives for changing such a schema and define their operational semantics
Schema Change Operations for Full Support of Schema Versioning in the \u3c4XSchema Framework
\u3c4XSchema is a framework (a language and a suite of tools) for the creation and validation of time-varying XML documents. A \u3c4XSchema schema is composed of a conventional XML Schema annotated with physical and logical annotations. All components of a \u3c4XSchema schema can evolve over time to reflect changes in the real-world. Since many applications need to keep track of both data and schema evolution, schema versioning has been long advocated to be the best solution to do this. In this paper, we complete the \u3c4XSchema framework, which is predisposed from the origin to support schema versioning, with the definition of the operations which are necessary to exploit such feature and make schema versioning functionalities available to final users. Moreover, we propose a new technique for schema versioning in \u3c4XSchema, allowing a complete and safe management of schema changes. It supports both versioning of conventional schema and versioning of annotations, in an integrated manner. For each component of a \u3c4XSchema schema, our approach provides a complete and sound set of change primitives and a set of high-level change operations, for the maintenance of such a component and defines their operational semantics