Papers

• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• JSONoid: Distributed JSON Schema Discovery - A tool for distributed JSON schema discovery including many properties of the data.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• TILT: A GDPR-Aligned Transparency Information Language and Toolkit for Practical Privacy Engineering - We present TILT, a transparency information language and toolkit explicitly designed to represent and process transparency information in line with the requirements of the GDPR and allowing for a more automated and adaptive use of such information than established, legalese data protection policies do.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Foundations of JSON Schema - In this paper we provide the first formal definition of syntax and semantics for JSON Schema and use it to show that implementing this layer on top of JSON is feasible in practice.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Jsongen: a quickcheck based library for testing JSON web services - This article describes a systematic approach to testing behavioural aspects of Web Services that communicate using the JSON data format. To generate random JSON data for populating tests we have developed a new library, jsongen, which given a characterisation of the JSON data as a JSON schema, (i) automatically derives a QuickCheck generator which can generate an infinite number of JSON values that validate against the schema, and (ii) provides a generic QuickCheck state machine which is capable of following the (hyper)links documented in the JSON schema, to automatically explore the web service.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Validation of Modern JSON Schema: Formalization and Complexity - In this paper, we give the first formal description of Modern JSON Schema, which we consider a central contribution of the work that we present here. We then prove that its data validation problem is PSPACE-complete. We prove that the origin of the problem lies in dynamic references, and not in annotation-dependent validation. We study the schema and data complexities, showing that the problem is PSPACE-complete with respect to the schema size even with a fixed instance, but is in PTIME when the schema is fixed and only the instance size is allowed to vary. Finally, we run experiments that show that there are families of schemas where the difference in asymptotic complexity between dynamic and static references is extremely visible, even with small schemas..
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• User profile integration made easy: model-driven extraction and transformation of social network schemas - This paper presents, firstly, a semi-automatic approach to extract schema information from instance data. Secondly, transformations of the derived schemas to different technical spaces are utilized, thereby allowing, amongst other benefits, the application of established integration tools and methods. Finally, as a case study, schemas are derived for Facebook, Google+, and LinkedIn.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.
• τJSchema: A Framework for Managing Temporal JSON-Based NoSQL Databases - This paper proposes a framework called Temporal JSON Schema (τJSchema), inspired by the τXSchema framework defined for XML data. τJSchema allows defining a temporal JSON schema from a conventional JSON schema and a set of temporal logical and physical characteristics. Our framework guarantees logical and physical data independence for temporal schemas and provides a low-impact solution since it requires neither modifications of existing JSON documents, nor extensions to the JSON format, the JSON Schema language, and all related tools and languages.
• Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework - This paper proposes an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.
• JSON Schema Inference Approaches - In the context of document NoSQL databases, namely those assuming the JSON data format, this paper focuses on several representatives of the existing inference approaches and provide their thorough comparison.
• Challenges in Checking JSON Schema Containment over Evolving Real-World Schemas - This paper presents the results of an empirical study of the first generation of tools for checking JSON Schema containment which is applied to a diverse collection of over 230 real-world schemas and their altogether 1k historic versions.
• What Are Real JSON Schemas Like? - A first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.
• Example-Driven Web API Specification Discovery - In this paper we present an example-driven discovery process that generates model-based OpenAPI specifications for REST Web APIs by using API call examples. A tool implementing our approach and a community-driven repository for the discovered APIs are also presented.