Ontologies as bridges between data sources and user queries: the KNOWMAK project experience

This paper describes ongoing work in the KNOWMAK project, which aims to develop a webbased tool providing interactive visualisations and state-of-the-art indicators on knowledge cocreation in the European research area. One of the main novel developments in this work is the use of ontologies to act as a bridge between the data sources (research projects, patents and publications) and user queries, in order to address the problems of mapping between heterogenous data sources with different vocabularies while still maintaining a level of standardization necessary for summarising the information required to provide informative views about the highly dynamic S&T landscape

Big Data Analytics National Educational System Monitoring and Decision Making

This paper reviews the applications of big data in supporting monitoring and decision making in the National Educational System. It describes different types of monitoring methodologies and explores the opportunities, challenges and benefits of incorporating big data applications in order to study the National Educational System. This approach allows to analyze schools as entities, which included in a local context with specific social, economic, and cultural development features. In addition, the paper attempts to identify the prerequisites that support the implementation of data analysis in the national educational system. This review reveals that there are several opportunities for using big data (structured and unstructured information) in the educational system, in order to improve strategic multidimensional knowledge for decision making and developing educational policies; however, there are still many issues and challenges that need to be addressed so as to achieve a better use of this technology

THE USE OF AI IN LANGUAGE LEARNING: WHAT YOU NEED TO KNOW

Kecerdasan Buatan adalah kekuatan transformasional dalam pendidikan, terutama dalam pembelajaran bahasa. Studi ini membahas berbagai alat AI yang digunakan untuk pembelajaran bahasa, seperti terjemahan mesin, teknologi ucapan, chatbot, dan konten yang dihasilkan oleh kecerdasan buatan. Studi ini secara komprehensif menjelajahi potensi dan tantangan yang terkait dengan peran kecerdasan buatan dalam pendidikan bahasa. Di satu sisi, kecerdasan buatan menawarkan manfaat seperti panduan personal, keterlibatan interaktif, dan pelacakan kemajuan. Namun, juga menimbulkan kekhawatiran tentang interaksi manusia yang berkurang, dampak potensial pada otonomi pembelajar, dan peran yang berkembang dari guru bahasa. Oleh karena itu, studi ini menekankan pentingnya menggabungkan prinsip-prinsip etika, transparansi, dan inklusivitas untuk memandu integrasi kecerdasan buatan dalam pendidikan secara bertanggung jawab. Penelitian ini menggunakan metodologi penelitian perpustakaan untuk membangun landasan teoritis yang kuat, menekankan peran penting integrasi kecerdasan buatan yang bertanggung jawab dalam meningkatkan pendidikan bahasa sambil menjaga standar etika yang tinggi

Tacit knowledge elicitation process for industry 4.0

Manufacturers migrate their processes to Industry 4.0, which includes new technologies for improving productivity and efficiency of operations. One of the issues is capturing, recreating, and documenting the tacit knowledge of the aging workers. However, there are no systematic procedures to incorporate this knowledge into Enterprise Resource Planning systems and maintain a competitive advantage. This paper describes a solution proposal for a tacit knowledge elicitation process for capturing operational best practices of experienced workers in industrial domains based on a mix of algorithmic techniques and a cooperative game. We use domain ontologies for Industry 4.0 and reasoning techniques to discover and integrate new facts from textual sources into an Operational Knowledge Graph. We describe a concepts formation iterative process in a role game played by human and virtual agents through socialization and externalization for knowledge graph refinement. Ethical and societal concerns are discussed as well

Rebuilding 'ethics' to govern AI: How to re-set the boundaries for the legal sector?

© 2023 Copyright held by the owner/author(s). This is an open access conference contribution distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Artificial intelligence (AI) has been transforming the legal sector and profession given every day enhancing AI-driven legal tech tools. Considering the far-reaching ethical implications of such tools and the disparate functionalities of 'AI ethics' and 'legal ethics', this paper puts into question the interplay between these ethical domains and their underlying rules. After fleshing out the governance of ethics under each domain, e.g. respectively professional conduct rules and self-regulatory principles, and signposting the unresolved ethical challenges of status quo, e.g. particularly concerning cross-domain issues, the paper discusses how they need to interact, based on the three policy options: 'revision of the conduct rules', 'individual (company level) collaboration' and 'higher-level collaboration'. It is concluded that 'higher-level collaboration' between the stakeholders is found to be the most sustainable and long-term option given the need to mitigate the ethical challenges concerning the legal sector from a holistic point of view