NORA: Scalable OWL reasoner based on NoSQL databasesand Apache Spark

Reasoning is the process of inferring new knowledge and identifying inconsis-tencies within ontologies. Traditional techniques often prove inadequate whenreasoning over large Knowledge Bases containing millions or billions of facts.This article introduces NORA, a persistent and scalable OWL reasoner built ontop of Apache Spark, designed to address the challenges of reasoning over exten-sive and complex ontologies. NORA exploits the scalability of NoSQL databasesto effectively apply inference rules to Big Data ontologies with large ABoxes. Tofacilitatescalablereasoning,OWLdata,includingclassandpropertyhierarchiesand instances, are materialized in the Apache Cassandra database. Spark pro-grams are then evaluated iteratively, uncovering new implicit knowledge fromthe dataset and leading to enhanced performance and more efficient reasoningover large-scale ontologies. NORA has undergone a thorough evaluation withdifferent benchmarking ontologies of varying sizes to assess the scalability of thedeveloped solution.Funding for open access charge: Universidad de Málaga / CBUA This work has been partially funded by grant (funded by MCIN/AEI/10.13039/501100011033/) PID2020-112540RB-C41,AETHER-UMA (A smart data holistic approach for context-aware data analytics: semantics and context exploita-tion). Antonio Benítez-Hidalgo is supported by Grant PRE2018-084280 (Spanish Ministry of Science, Innovation andUniversities)

A Language for the Specification of the Schema of Spreadsheets for the Materialization of Ontologies

Ontology-based Data Access (OBDA) is concerned with providing end-users and applications with a way to query legacy databases through a high-level ontology that models both the business logic and the underlying data sources, accessed by mappings that de ne how to express records of the database as ontological assertions. In this research, we are concerned with providing with tools for performing OBDA with relational and non-relational data sources. We developed an OBDA tool that is able to access H2 databases and CSV les allowing the user to explicitly formulate mappings, and populating an ontology that can be saved for later querying. In this paper, we present an extension of our previous work as a language for specifying the schema of the data in a spreadsheet data application. This speci cation is then used to access the contents of a set of Excel books and express them as a relational database with the ultimate goal of materializing its data as an OWL/RDF ontology. We characterize the syntax and semantics of the language, present a prototypical implementation and report on the performance tests showing that our implementation can handle a workload of Excel tables of the order of ten thousand records.Workshop: WISS – Innovación en Sistemas de SoftwareRed de Universidades con Carreras en Informátic

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Ontop: answering SPARQL queries over relational databases

We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL2QL and RDFS ontologies), and its support for all major relational databases

Ontology Based Data Access in Statoil

Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connected’ to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background. Our modules have been integrated in one OBDA system, deployed at Statoil, integrated with Statoil’s infrastructure, and evaluated with Statoil’s engineers and data

Developing Ontology-based Data access techniques for temporal data

Η παρούσα πτυχιακή εργασία αφορά τη επέκταση του συστήματος Ontop-spatial για την υποστήριξη χρονικών δεδομένων (temporal data). Το Ontop-Spatial είναι ένα σύστημα το οποίο υποστηρίζει την επεξεργασία γεωχωρικών επερωτήσεων στη γλώσσα GeoSPARQL, επαναγράφοντάς τις στη γλώσσα SQL ώστε να αποττιμηθούν τελικά σε μια γεωχωρική βάση δεδομένων που είναι συνδεδεμένη με το Ontop-spatial. Με παρόμοια τεχνική, χρησιμοποιώντας οντολογίες και αντιστοιχήσεις δεδομένων από το σχεσιακό μοντέλο στο μοντέλο RDF γίνεται δυνατή η μετάφραση σε πραγματικό χρόνο και των χρονικών επερωτήσεων που εκφράζονται στη γλώσσα stSPARQL στα αντίστοιχα SQL ερωτήματα τα οποία μπορούν να αποτιμηθούν σε μια χρονική βάση δεδομένων. Η γλώσσα stSPARQL είναι μια επέκταση της γλώσσας SPARQL με χρονικά και γεωχωρικά χαρακτηριστικά. Στην παρούσα πτυχιακή περιγράφουμε την προσέγγισή μας και διεξάγουμε πειραματική μελέτη για να αξιολογήσουμε την απόδοση της υλοποίησης.We propose an additional enhancement on top of the already extended Ontop's SPARQL-to-SQL translation, which supports geospatial data, with the addition of stSPARQL-to-SQL translation regarding temporal data. Ontop is a mature, open-source Ontology-Based Data Access (OBDA) system that allows posing SPARQL queries on top of relational data sources through provided ontologies and mappings. The system Ontop-spatial is an extension of the system Ontop that performs on-the-fly GeoSPARQL-to-SQL translation on top of geospatial enabled databases. GeoSPARQL is a spatial extension of the SPARQL query language and has been standardized by OGC. In this thesis, we extend the system Ontop-spatial with the ability to execute temporal queries as well, on top of temporal enabled databases

Implementing OBDA for an end-user query answering service on an educational ontology

In the age where productivity of society is no longer defined by the amount of information generated, but from the quality and assertiveness that a set of data may potentially hold, the right questions to do depends on the semantic awareness capability that an information system could evolve into. To address this challenge, in the last decade, exhaustive research has been done in the Ontology Based Data Access (OBDA) paradigm. A conspectus of the most promising technologies with data integration capabilities and the foundations where they rely are documented in this memory as a point of reference for choosing tools that supports the incorporation of a conceptual model under a OBDA method. The present study provides a practical approach for implementing an ontology based data access service, to educational context users of a Learning Analytics initiative, by means of allowing them to formulate intuitive enquiries with a familiar domain terminology on top of a Learning Management System. The ontology used was completely transformed to semantic linked data standards and some data mappings for testing were included. Semantic Linked Data technologies exposed in this document may exert modernization to environments in which object oriented and relational paradigms may propagate heterogeneous and contradictory requirements. Finally, to validate the implementation, a set of queries were constructed emulating the most relevant dynamics of the model regarding the dataset nature