arXiv subjects

Jose Emilio Labra Gayo

Publications and source records attributed to Jose Emilio Labra Gayo.

6 recordsLinked to original sources

arXiv2025

Shape Expressions with Inheritance

We formally introduce an inheritance mechanism for the Shape Expressions language (ShEx). It is inspired by inheritance in object-oriented programming languages, and provides similar advantages such as reuse, modularity, and more flexible data modelling. Using an example, we explain the main features of the inheritance mechanism. We present its syntax and formal semantics. The semantics is an extension of the semantics of ShEx 2.1. It also directly yields a validation algorithm as an extension of the previous ShEx validation algorithms, while maintaining the same algorithmic complexity.

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arXiv2023

A comparison between traditional and Serverless technologies in a microservices setting

Serverless technologies, also known as FaaS (Function as a Service), are promoted as solutions that provide dynamic scalability, speed of development, cost-per-consumption model, and the ability to focus on the code while taking attention away from the infrastructure that is managed by the vendor. A microservices architecture is defined by the interaction and management of the application state by several independent services, each with a well-defined domain. When implementing software architectures based on microservices, there are several decisions to take about the technologies and the possibility of adopting Serverless. In this study, we implement 9 prototypes of the same microservice application using different technologies. Some architectural decisions and their impact on the performance and cost of the result obtained are analysed. We use Amazon Web Services and start with an application that uses a more traditional deployment environment (Kubernetes) and migration to a serverless architecture is performed by combining and analysing the impact (both cost and performance) of the use of different technologies such as AWS ECS Fargate, AWS Lambda, DynamoDB or DocumentDB.

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arXiv2022

WShEx: A language to describe and validate Wikibase entities

Wikidata is one of the most successful Semantic Web projects. Its underlying Wikibase data model departs from RDF with the inclusion of several features like qualifiers and references, built-in datatypes, etc. Those features are serialized to RDF for content negotiation, RDF dumps and in the SPARQL endpoint. Wikidata adopted the entity schemas namespace using the ShEx language to describe and validate the RDF serialization of Wikidata entities. In this paper we propose WShEx, a language inspired by ShEx that directly supports the Wikibase data model and can be used to describe and validate Wikibase entities. The paper presents a the abstract syntax and semantic of the WShEx language.

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arXiv2021

Creating Knowledge Graphs Subsets using Shape Expressions

The initial adoption of knowledge graphs by Google and later by big companies has increased their adoption and popularity. In this paper we present a formal model for three different types of knowledge graphs which we call RDF-based graphs, property graphs and wikibase graphs. In order to increase the quality of Knowledge Graphs, several approaches have appeared to describe and validate their contents. Shape Expressions (ShEx) has been proposed as concise language for RDF validation. We give a brief introduction to ShEx and present two extensions that can also be used to describe and validate property graphs (PShEx) and wikibase graphs (WShEx). One problem of knowledge graphs is the large amount of data they contain, which jeopardizes their practical application. In order to palliate this problem, one approach is to create subsets of those knowledge graphs for some domains. We propose the following approaches to generate those subsets: Entity-matching, simple matching, ShEx matching, ShEx plus Slurp and ShEx plus Pregel which are based on declaratively defining the subsets by either matching some content or by Shape Expressions. The last approach is based on a novel validation algorithm for ShEx based on the Pregel algorithm that can handle big data graphs and has been implemented on Apache Spark GraphX.

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arXiv2019

Semi Automatic Construction of ShEx and SHACL Schemas

We present a method for the construction of SHACL or ShEx constraints for an existing RDF dataset. It has two components that are used conjointly: an algorithm for automatic schema construction, and an interactive workflow for editing the schema. The schema construction algorithm takes as input sets of sample nodes and constructs a shape constraint for every sample set. It can be parametrized by a schema pattern that defines structural requirements for the schema to be constructed. Schema patterns are also used to feed the algorithm with relevant information about the dataset coming from a domain expert or from some ontology. The interactive workflow provides useful information about the dataset, shows validation results w.r.t. the schema under construction, and offers schema editing operations that combined with the schema construction algorithm allow to build a complex ShEx or SHACL schema.

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arXiv2017

Semantics and Validation of Shapes Schemas for RDF

We present a formal semantics and proof of soundness for shapes schemas, an expressive schema language for RDF graphs that is the foundation of Shape Expressions Language 2.0. It can be used to describe the vocabulary and the structure of an RDF graph, and to constrain the admissible properties and values for nodes in that graph. The language defines a typing mechanism called shapes against which nodes of the graph can be checked. It includes an algebraic grouping operator, a choice operator and cardinality constraints for the number of allowed occurrences of a property. Shapes can be combined using Boolean operators, and can use possibly recursive references to other shapes. We describe the syntax of the language and define its semantics. The semantics is proven to be well-defined for schemas that satisfy a reasonable syntactic restriction, namely stratified use of negation and recursion. We present two algorithms for the validation of an RDF graph against a shapes schema. The first algorithm is a direct implementation of the semantics, whereas the second is a non-trivial improvement. We also briefly give implementation guidelines.

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