Resumo
Cultural Heritage is the source of much knowledge. Arguably, Cultural Heritage is one of the most complex objects of study, as it knots together cultural, psychological, material, historical, biological and environmental concerns. When we study Cultural Heritage, we encode what we learn in the form of information, and then as data. Reinterpreting these data and being able to generate relevant knowledge from them is quite a challenge, and often we struggle to integrate large amounts of heterogeneous information into meaningful insights. Sometimes we employ the so-called semantic technologies, such as the semantic web or ontology description languages to get computers to assist ourselves in the process, but the results are still disappointing.Often, data gets disconnected from knowledge. We hoard datasets, but we still struggle to generate meaningful knowledge from them. And, similarly, we struggle to encode our knowledge in the form of data that can be reused by others. There are four major reasons for this. First, the so-called “semantic” technologies are not really semantic, but heavily lexical, as they emphasize the symbols we use rather than their representational connections with the world. Second, we seem divided between standardized and custom approaches; we understand the value of sharing a common conceptualization and using the same mental models but, at the same time, are reluctant to part with our own specific approaches, fostering the fragmentation of data, information and knowledge. Third, we systematically fail to address “soft” issues such as subjectivity, temporality, vagueness or multilingualism when recording and processing information, thus stripping our understanding from critical elements. Fourth, we neglect human language as a key player in the construction and expression of Cultural Heritage, and try to understand it as a thing of itself rather than a language-mediated phenomenon.In this talk I will present a collection of technologies that tackle these issues. I will introduce ConML, a conceptual modelling language especially conceived for the humanities and social sciences, that is capable of capturing soft issues as well as hard evidence. I will also describe how our models can be gradually refined so that we share a common abstraction of the world while, at the same time, we describe our particular realm of interest using specific concepts and terminology. Finally, I will explain how discourse and argumentation analysis can help us introduce language as a key component in the knowledge generation processes related to Cultural Heritage. Hopefully, these will be seen as true semantic technologies that connect information to the world, and which eventually will help computers to assist humans to understand themselves a bit better.