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Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).

Considering the lack of integration of sustainable development goals (SDGs) within architectural engineering education, the purpose of this study is to develop a framework that incorporates the SDGs into a programme through extracurricular research activities.

A framework based on case studies was examined. The framework uses extracurricular activities, including an integrated design process and analytical mapping tool. These were accompanied by a comprehensive list of the 17 SDGs and their interpretations.

The framework enabled students to develop a systematic understanding of sustainability early on in their design process, leading to a more comprehensive consideration of architectural design issues and increased motivation to prioritise sustainability in architecture.

The focus was on extracurricular activities rather than integrating the framework into the main programme. Therefore, further research is needed to explore this integration within the core curriculum.

The implications of research initiatives and extracurricular activities in promoting understanding of the SDGs among undergraduates were highlighted. The recommendations may be valuable for academic institutions aiming to align their planning in higher education with the necessary skills and global requirements as outlined in Agenda 2030.

The originality of this study lies in its contribution from the field of architectural engineering and its endeavour to incorporate the SDGs into a programme in the Middle East through a research-based approach.