## 2 Theoretical Background  
More than two decades have passed since [PERSON] and his team envisioned the Semantic Web, a form of web content that would be readable and, thus, understandable and comprehensible by machines [1]. One of Semantic Web's most important properties is this ability to give more valuable information by automatically searching the meaning structure of web content [5]. In essence, it would provide structure to the anarchic structure of the Web in conjunction with the focus on human-centered computing as presented by [PERSON] [6], an early proponent of the Semantic Web. The Semantic Web, alongside other web paradigms such as the Social Web which involves the evolution of social media, the 3D Web which encompasses virtual reality experiences in the Web and the Media Centric Web which focuses on the transmediative nature of the Web, is a key consisting element of Web 3.0 [7]. Furthermore, new technologies such as Artificial Intelligence and the blockchain also enhance and improve aspects of the Web, aiming to achieve different goals such as decentralization, connectivity and ubiquity. Web 3.0 and especially the Semantic Web, which is the focus of this study, seem to find their way in multiple thematic fields in the Web, such as news outlets or art and culture-related websites. The rise of increasingly technologically advanced forms of journalism dispels any questions about the technical optimization of contemporary journalism [3]. Despite the fact that now there is more pluralism in terms of websites than ever and more opinions can be heard, the sheer reality is that the majority of this information is left unstructured [3]. Semantic Web solutions could be valuable for journalistic research. The Web offered journalists the plurality that was missing but as a result this led to a more time-consuming process where journalists need to navigate through all the available data and sources and filter the information they are accessing manually [4]. Semantic Web technologies could automatically read, comprehend and include or exclude the useful information and even improve it by reproducing it with added enhancements such as accessibility features [8], or even advanced user personalization features [9]. [PERSON] and [PERSON] [4] note that a combination of technologies will be necessary to provide a Social Semantic Journalism Framework. These technologies would undoubtedly collaborate with each other and serve as inputs and outputs for one another, establishing a procedure capable of addressing the issue that social media poses to journalists and editors as they attempt to determine what is noteworthy in user-generated content. Another field that could benefit from Semantic Web solutions is that of art and cultural heritage in general. Cultural heritage can be defined as a kind of inheritance to be preserved and passed down to future generations. It is also linked to group identity and is both a symbol of and an essential ingredient in the building of that group's identity [10]. Cultural heritage is vital to understanding earlier generations and the origins of humanity. The Web has enabled local, national and global publishing, explanation and debate. More and more museums, galleries and art-related institutions are transferring part or all of their collections into the digital space. The quality of a museum's Web presence on the Web can lead, not only to increased website visits, but also to increased physical visitors [11]. However, cultural heritage resources are vast and diverse. They comprise data or information that is highly structured, very unstructured or semi-structured and derived from both authorized and unauthorized sources, and also include multimedia data such as text, images, audio and video data [2]. In order to accommodate the users' needs, many usability-related features need to be implemented [12], but a usability-oriented approach is not the only approach that can help scientists, companies, and schools better understand cultural data.