A Generic RDF Transformation Software and its Application to an Online Translation Service for Common Languages of Linked Data

International audienceIn this article we present a generic template and software solution for developers to support the many cases where we need to transform RDF. It relies on the SPARQL Template Transformation Language (STTL) which enables Semantic Web developers to write specific yet compact RDF transformers toward other languages and formats. We first briefly recall the STTL principles and software features. We then demonstrate the support it provides to programmers by presenting a selection of STTL-based RDF transformers for common languages. The software is available online as a Web service and all the RDF transformers presented in this paper can be tested online

NLQxform: A Language Model-based Question to SPARQL Transformer

In recent years, scholarly data has grown dramatically in terms of both scale and complexity. It becomes increasingly challenging to retrieve information from scholarly knowledge graphs that include large-scale heterogeneous relationships, such as authorship, affiliation, and citation, between various types of entities, e.g., scholars, papers, and organizations. As part of the Scholarly QALD Challenge, this paper presents a question-answering (QA) system called NLQxform, which provides an easy-to-use natural language interface to facilitate accessing scholarly knowledge graphs. NLQxform allows users to express their complex query intentions in natural language questions. A transformer-based language model, i.e., BART, is employed to translate questions into standard SPARQL queries, which can be evaluated to retrieve the required information. According to the public leaderboard of the Scholarly QALD Challenge at ISWC 2023 (Task 1: DBLP-QUAD - Knowledge Graph Question Answering over DBLP), NLQxform achieved an F1 score of 0.85 and ranked first on the QA task, demonstrating the competitiveness of the system

Open Data Consumption Through the Generation of Disposable Web APIs

The ever-growing amount of information in today’s world has led to the publication of more and more open data, i.e., that which is available in a free and reusable manner, on the Web. Open data is considered highly valuable in situational scenarios, in which thematic data is required for a short life cycle by a small group of consumers with specific needs. In this context, data consumers (developers or data scientists) need mechanisms with which to easily assess whether the data is adequate for their purpose. SPARQL endpoints have become very useful for the consumption of open data, but we argue that its steep learning curve hampers open data reuse in situational scenarios. In order to overcome this pitfall, in this paper, we coin the term disposable Web APIs as an alternative mechanism for the consumption of open data in situational scenarios. Disposable Web APIs are created on-the-fly to be used temporarily by a user to consume open data. In this paper we specifically describe an approach with which to leverage semantic information from data sources so as to automatically generate easy-to-use disposable Web APIs that can be used to access open data in a situational scenario, thus avoiding the complexity and learning curve of SPARQL and the effort of manually processing the data. We have conducted several experiments to discover whether non-experienced users find it easier to use our disposable Web API or a SPARQL endpoint to access open data. The results of the experiments led us to conclude that, in a situational scenario, it is easier and faster to use the Web API than the corresponding SPARQL endpoint in order to consume open data.This work was supported in part by the Access@City coordinated Research Project through the Spanish Ministry of Science, Innovation and Universities under Grant TIN2016-78103-C2-1-R and Grant TIN2016-78103-C2-2-R; in part by the Plataforma intensiva en datos proveedora de servicios inteligentes de movilidad (MoviDA) Project through Rey Juan Carlos University; and in part by the Recolección y publicación de datos abiertos para la reactivación del sector turístico postCOVID-19 (UAPOSTCOVID19-10) Project through the Consejo Social of the University of Alicante. The work of César González-Mora was supported in part by the Generalitat Valenciana, and in part by the European Social Fund under Grant ACIF/2019/044

A dataflow platform for applications based on Linked Data

Modern software applications increasingly benefit from accessing the multifarious and heterogeneous Web of Data, thanks to the use of web APIs and Linked Data principles. In previous work, the authors proposed a platform to develop applications consuming Linked Data in a declarative and modular way. This paper describes in detail the functional language the platform gives access to, which is based on SPARQL (the standard query language for Linked Data) and on the dataflow paradigm. The language features interactive and meta-programming capabilities so that complex modules/applications can be developed. By adopting a declarative style, it favours the development of modules that can be reused in various specific execution context

Standards-based sensor web for wide area monitoring of power systems

The balance of supply and demand of energy is the key factor in the stability of power systems. A small disturbance in the supply demand relationship, if not properly handled, can cascade into a major outage, costing millions of dollars to the stakeholders. Proper monitoring and exchange of critical information in real time is the only solution to prevent the instability in this vulnerable system. But, the disparity in the protocols used by power utilities and the lack of infrastructure for information exchange are proving to be hindrance to obtaining a reliable de-regularized power industry. In this thesis, an emerging Sensor Web Enablement (SWE) has been adapted for the wide area monitoring of power systems. SWE and CIM provide a solution to both problems; the heterogeneity of data and the lack of central repository of the data for proper action. The sensor data from utilities that are published in CIM were modeled thorough a SensorML and exposed via a Sensor Observation Service (SOS). This provides a standard method for discovering and accessing the sensor data between utilities and facilitates rapid response functionality to handle contingences

Interface de visualisation innovante du Linked Data

Deux applications résultent de ce travail de Bachelor. La première est un outil utilisé pour extraire des données provenant du web sémantique. La deuxième application est capable de créer des visualisations en se basant sur des données au format JSON. L’outil d’administration est capable de récupérer des données issues de plusieurs points à la fois. Il permet à l’utilisateur de naviguer à l’intérieur de ces données et d’extraire les informations qu’il juge pertinentes. L’application de développement de visualisations importe des données avec lesquelles elle crée différentes visualisations. Par la suite, ces visualisations peuvent être déployées sur des sites internet et être consultées par les visiteurs. L’objectif principal de ces deux outils est de permettre d’utiliser les données appartenant au web sémantique d’une façon simple. Sans grande connaissance dans le domaine, l’utilisateur doit être en mesure de parcourir chacune des étapes jusqu’à la publication de visualisations

Fintan - Flexible, Integrated Transformation and Annotation eNgineering

We introduce the Flexible and Integrated Transformation and Annotation eNgeneering (Fintan) platform for converting heterogeneous linguistic resources to RDF. With its modular architecture, workflow management and visualization features, Fintan facilitates the development of complex transformation pipelines by integrating generic RDF converters and augmenting them with extended graph processing capabilities: Existing converters can be easily deployed to the system by means of an ontological data structure which renders their properties and the dependencies between transformation steps. Development of subsequent graph transformation steps for resource transformation, annotation engineering or entity linking is further facilitated by a novel visual rendering of SPARQL queries. A graphical workflow manager allows to easily manage the converter modules and combine them to new transformation pipelines. Employing the stream-based graph processing approach first implemented with CoNLL-RDF, we address common challenges and scalability issues when transforming resources and showcase the performance of Fintan by means of a purely graph-based transformation of the Universal Morphology data to RDF