The SEALS Yardsticks for Ontology Management

This paper describes the rst SEALS evaluation campaign over ontology engineering tools (i.e., the SEALS Yardsticks for Ontology Management). It presents the dierent evaluation scenarios dened to evaluate the conformance, interoperability and scalability of these tools, and the test data used in these scenarios

IBSE: An OWL Interoperability Evaluation Infrastructure

The technology that supports the Semantic Web presents a great diversity and, whereas all the tools use different types of ontologies, not all of them share a common knowledge representation model, which may pose problems when they try to interoperate. The Knowledge Web European Network of Excellence is organizing a benchmarking of interoperability of ontology tools using OWL as interchange language with the goal of assessing and improving tool interoperability. This paper presents the development of IBSE, an evaluation infrastructure that allows executing automatically the benchmarking experiments and provides an easy way of analysing the results. Thus,including new tools into the evaluation infrastructure will be simple and straightforward

Benchmarking Semantic Web Technology

This paper summarises the research problem that the PhD thesis I am currently writing addresses. It presents an overview of the thesis, its goals taking into account the deciencies of the State of the Art, the approach followed, and the work performed for the thesis since its beginning in 2004

Defining a Benchmark Suite for Evaluating the Import of OWL Lite Ontologies

SemanticWeb tools should be able to correctly interchange ontologies and, therefore, to interoperate. This interchange is not always a straightforward task if tools have different underlying knowledge representation paradigms. This paper describes the process followed to define a benchmark suite for evaluating the OWL import capabilities of ontology development tools in a benchmarking activity in progress in the Knowledge Web European Network of Excellence

Benchmarking the RDF(S) interoperability of ontology tools

The number of ontology tools, such as ontology editors and repositories, is constantly rising. Ideally, one could use them all seamlessly and thus benefit from all the functionalities they offer. As shown in previous EON workshops, interoperability among different development tools is not straightforward since ontology editors rely on specific internal knowledge models which are translated into common formats such as RDF(S). This paper addresses the urgent need for interoperability by providing an exhaustive set of RDF(S) benchmarks and demonstrating in an extensive field study the state-of-the-art of interoperability among six ontology tools. From the field study we have compiled a comprehensive set of best practices which may serve as guidelines. Tool developers benefit from having guidelines to design their import and export functionalities and a concrete set of benchmarks against which they can evaluate their import and export functionalities. Ontology engineers benefit from our work by having an overview to which extend interoperability is ensured for combinations of specific tools

Towards the improvement of the Semantic Web technology

The Semantic Web technology needs to be thoroughly evalu- ated for providing objective results and to attain a massive improvement in their quality in order to be consolidated in the industrial and in the academic world. This paper presents software benchmarking as a process to carry out over the SemanticWeb technology in order to improve it and to search for best practices. It also describes a software benchmarking methodology and provides recommendations for performing evaluations in benchmarking activities

Benchmarking in the Semantic Web

The Semantic Web technology needs to be thoroughly evaluated for providing objective results and obtaining massive improvement in its quality; thus, the transfer of this technology from research to industry will speed up. This chapter presents software benchmarking, a process that aims to improve the Semantic Web technology and to find the best practices. The chapter also describes a specific software benchmarking methodology and shows how this methodology has been used to benchmark the interoperability of ontology development tools, employing RDF(S) as the interchange language

The state of semantic technology today - overview of the first SEALS evaluation campaigns

This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions

Infraestructura tecnológica de servicios semánticos para la Web Semántica

This project aims at creating a network of distributed interoperable semantic services for building more complex ones. These services will be available in semantic Web service libraries, so that they can be invoked by other systems (e.g., semantic portals, software agents, etc.). Thus, to accomplish this objective, the project proposes: a) To create specific technology for developing and composing Semantic Web Services. b) To migrate the WebODE ontology development workbench to this new distributed interoperable semantic service architecture. c) To develop new semantic services (ontology learning, ontology mappings, incremental ontology evaluation, and ontology evolution). d) To develop technological support that eases semantic portal interoperability, using Web services and Semantic Web Services. The project results will be open source, so as to improve their technological transfer. The quality of these results is ensured by a benchmarking process. Keywords: Ontologies and Semantic We

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems