Large language models and AI-based audio-visual production technologies are currently attracting a great deal of public attention. However, from the perspective of Humanities and Social Sciences (HSS) research, it is important to remember the significance of knowledge graphs and linked open data (LOD), revolutionising the way information is analysed and shared at scale. Google's Knowledge Graph, defined by the company as a "giant virtual encyclopaedia of facts" has grown, as of March 2023, “to 800 billion facts on 8 billion entities” (Wikipedia). In this context, it is worth considering whether HSS researchers will be able to share the information they produce on a daily basis, using the same semantic technologies, and link their data with the metadata of libraries, archives and museums, in order to create a giant graph of high-quality information about historical objects? And thus enable a renewed knowledge of the societies of the past, and a better understanding of the issues of the present? This talk will first address the question of how to define information in the context of HSS research, and under what conditions and for what purposes the sharing of large amounts of information can be useful for fostering disciplinary innovation. Then there will be presentation of the semantic methodology underpinning the Semantic Data for Humanities and Social Sciences (SDHSS) project, which enables the creation of an open and refinable transdisciplinary ontology ecosystem that unambiguously documents the meaning of the shared information and facilitates reuse for new research. Finally, the speaker will outline the principles that allow the modelling of different aspects of social and legal life, and apply them to some examples. The aim is to challenge these principles from the perspective of legal history, in order to refine and enrich the shared conceptualisation.