Towards a Conceptualization of Sociomaterial Entanglement

Abstract

In knowledge representation, socio-technical systems can be modeled as multiagent systems in which the local knowledge of each individual agent can be seen as a context. In this paper we propose formal ontologies as a means to describe the assumptions driving the construction of contexts as local theories and to enable interoperability among them. In particular, we present two alternative conceptualizations of the notion of sociomateriality (and entanglement), which is central in the recent debates on socio-technical systems in the social sciences, namely critical and agential realism. We thus start by providing a model of entanglement according to the critical realist view, representing it as a property of objects that are essentially dependent on different modules of an already given ontology. We refine then our treatment by proposing a taxonomy of sociomaterial entanglements that distinguishes between ontological and epistemological entanglement. In the final section, we discuss the second perspective, which is more challenging form the point of view of knowledge representation, and we show that the very distinction of information into modules can be at least in principle built out of the assumption of an entangled reality.

DOLCE: A descriptive ontology for linguistic and cognitive engineering1

“…We will also use the Artefact category, as introduced in [5] and two new subclasses of it introduced specifically for this scenario, i.e., Table and TableLeg. 10 In terms of relations we use: being subclass (IS_A), parthood (P), constitution (K) and being present (PRE). We also use the sum operator (+), and the order relation (<) for time.…”

“…Funct RL(x) → RL(x) (10) RL(x) → NASO(x) (11) The previous formulas state that a person is an agentive physical object, a functional role is a role and a role is a non-agentive social object.…”

“…These modules facilitate the application and coherent use of the ontology. Some extensions tackle knowledge representation's specific issues, like the modeling of roles [23], artifacts [30,3], and modules [10], others attempts an integration with machine learning and in particular computer vision [8]. Extensions to the modeling of social [6,28,26] and cognitive aspects [9,1] have also been proposed.…”

“…These modules facilitate the application and coherent use of the ontology. Some extensions tackle knowledge representation's specific issues, like the modeling of roles by Masolo et al (2004), of artifacts by Vieu et al (2008) and by Borgo et al (2014), and of modules by Ferrario and Porello (2015). Others showed a possible integration with machine learning and in particular computer vision (Conigliaro et al, 2017).…”