Dataset on the PhD thesis "Heritage Beyond Singular Narratives: Embracing Diversity in Participatory Heritage Planning Empowered by Artificial Intelligence"

By comparing the different stakeholders’ perspectives, discovered using an AI approach from multiple unstructured data sources, this research develops an approach to reveal alignments and conflicts between academic experts, policymakers, and users to shed light on the conflicts and alignments embedded in the multi-stakeholder setting and as a step further towards inclusive data-supported heritage planning. To provide empirical evidence of such an approach, thisresearch explores various stakeholders’ perspectives on the cultural significance conveyed to a specific case study, the city of Yazd, Iran. The focus of research is on windcatchers which are key attributes conveying outstanding universal value, as inscribed on the UNESCO World Heritage List (UNESCO, 2017). This research discusses alignments and conflicts in the attributes and values, by comparing the perspectives of policy makers, users, and academic experts. Based on the analysis, a critical reflection on the changes expected in heritage planning is discussed. This study offers a comprehensive methodology with a customized AI-supported tool to detect alignments and conflicts in participation processes applied to heritage planning. Besides, this study reveals a critical gap that requires more reflection on the changes expected in heritage planning, by considering how different stakeholders may grow in their contribution to the definition of cultural significance in heritage planning, given the rising importance of public participation.These datasets contain the opinions of three main stakeholdr groups on the cultural significance of windcatchers in Yazd, Iran:experts (academic publications)users (social media: Instagram and Twitter/X)policy makers (local/national/international documents) <br>The analysis results have been published in journal papers, conference papers, and a book chapter. <br>There are three Excel files containing various sheets:general information: the publications' information namely, title, year of publication, authors, etc.sentences_values: titles, relevant sentences, and values addressed in the sentencessentences_attributes: titles, relevant sentences, and attributes addressed in the sentencesname entity recognition (NER): relevant sentences, relevant words, and the class of NER associated with the wordsentiment and emotion analysis: relevant sentences, sentiments, emotions<br>