Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.

The ontology translation problem (aka ontology interoperability problem) appears when we decide to reuse an ontology (or part of an ontology) with a tool or language that is different from those ones in which the ontology is available. If we force each ontology-based system developer, individually, to commit to the task of translating and incorporating to their systems the ontologies that they need, they will require a lot of effort and time to achieve their objective. This book presents two contributions to the current state of the art on ontology translation among languages and/or tools. The first contribution is a proposal for a new model for building and maintaining ontology translation systems. The second contribution characterises existing ontology translation approaches from the perspectives of semantic and pragmatic preservation, that is, consequence and intended meaning preservation respectively.

This is a comprehensive survey of ontologies with practical guidance on selection and applications in Knowledge Management and e-commerce. Ontologies provide a common vocabulary of an area and define, with different levels of formality, the meaning of the terms and the relationships between them. The book presents the major issues of ontological engineering and describes the most outstanding ontologies currently available. It covers the practical aspects of selecting and applying methodologies, languages, and tools for building ontologies. Ontological Engineering will be of great value to students and researchers, and to developers who want to integrate ontologies in their information systems.

Previous research performed in the context of the former European Data Portal explored concepts, methods and architectures to make (open) data portals sustainable. They helped bring about a paradigm shift in the open data community, namely a shift away from understanding portals primarily as a means to publish and discover data and towards rethinking of portals as sources of added-value content and resources that facilitate data reuse and foster data communities. This report is the first in a series. The series will build on this previous work and focus both on the value of the data and metadata that the data.europa.eu portal holds and on the value of other resources available on the portal (e.g. documentation in the form of reports and publications, tools and data stories). To provide such an analysis, we are developing methods (including computational methods, also known as software prototypes) to: • assess the value of datasets and their related resources by studying their presence on other digital platforms, tools and applications that are commonly used by data communities; • add value to datasets and resources by recommending other related datasets and resources and enriching their content to make it easier to use in downstream applications (e.g. in machine learning).

Data spaces are central to the European strategy for data. The strategy envisages 'a European data space as a genuine single market for data where personal and non-personal data, including sensitive business data, are secure and businesses have easy access to high-quality industrial data, boosting growth and creating value'. This report explores existing and emerging developments and initiatives around data sharing using data spaces (from the International Data Spaces Association, Gaia-X and Open DEI). Our aim is twofold: to identify holders of open data who are involved in ongoing data space implementation and to reflect on the role that open data portals (with a special focus on data.europa.eu) could play in this implementation.

This document has been developed by the Interoperability Task Force of the EOSC Executive Board FAIR Working Group, with participation from the Architecture WG. Achieving interoperability within EOSC is essential in order for the federation of services that will compose EOSC to provide added value for service users. In the context of the FAIR principles, interoperability is discussed in relation to the fact that "research data usually need to be integrated with other data; in addition, the data need to interoperate with applications or workflows for analysis, storage, and processing". Our view on interoperability does not only consider data but also the many other research artefacts that may be used in the context of research activity, such as software code, scientific workflows, laboratory protocols, open hardware designs, etc. It also considers the need to make services and e-infrastructures as interoperable as possible. This document identifies the general principles that should drive the creation of the EOSC Interoperability Framework (EOSC IF), and organises them into the four layers that are commonly considered in other interoperability frameworks (e.g., the European Interoperability Framework - EIF): technical, semantic, organisational and legal interoperability. For each of these layers, a catalogue of problems and needs, as well as challenges and high-level recommendations have been proposed, which should be considered in the further development and implementation of the EOSC IF components. Such requirements and recommendations have been developed after an extensive review of related literature as well as by running interviews with stakeholders from ERICs (European Research Infrastructure Consortia), ESFRI (European Strategy Forum on Research Infrastructures) projects, service providers and research communities. Some examples of such requirements are: "every semantic artefact that is being maintained in EOSC must have sufficient associated documentation, with clear examples of usage and conceptual diagrams", or "Coarse-grained and fine-grained dataset (and other research object) search tools need to be made available", etc. The document finally contains a proposal for the management of FAIR Digital Objects in the context of EOSC and a reference architecture for the EOSC Interoperability Framework that is inspired by and extends the European Interoperability Reference Architecture (EIRA), identifying the main building blocks required.

This report is the first in a series of four that aims to establish a standard methodology for open data impact assessments that can be used across Europe. This exercise is key because a consistent definition of the impact of open data does not exist. The lack of a robust, conceptual foundation has made it more difficult for data portals to demonstrate their value through empirical evidence. It also challenges the EU's ability to understand and compare performance across Member States. Most academic articles that look to explore the impact of data refer to existing open data frameworks, with the open data maturity (ODM) and open data barometer (ODB) ones most frequently represented. These two frameworks distinguish between different kinds of impact, and both mention social, political and economic impacts in particular. The ODM also includes the environmental impact in its framework. Sometimes, these frameworks diverge from the European Commission's own recommendations of how best to measure impact, as explained in specific sections of the better regulation guidelines and the better regulation toolbox. They help to answer a critical question for policymakers: do the benefits provided outweigh the costs of assembling and distributing (open) data? Future reports in this series will further explore how to better align existing frameworks, such as the ODM, with these critically important guidelines.

This report summarises the work done so far on thought leadership regarding the mid- and long-term sustainability of (open) data portal infrastructures. The main research questions we are addressing in this work, which spans from 2021 to 2025, are the following. What is the role of data intermediaries (such as data.europa.eu) in the broader data economy? How can open data portals evolve towards mid- and long-term self-sustainability? How can we design software tools and platforms to support data intermediaries?

The main objective of this report is to provide some insight about citizen-generated data (CGD) that may be part of open data portals, allowing public administrations to better understand whether and how CGD may be made available as part of their open data offering. The report provides a categorisation of different types and dimensions of CGD that may be offered in open data portals (and that is already offered in some of them), together with a discussion on the opportunities and challenges that their inclusion in data.europa.eu may bring in.