The interplay between models and observations

Abstract

We propose a formal framework to examine the relationship between models and observations. To make our analysis precise, models are reduced to first-order theories that represent both terminological knowledge -e.g., the laws that are supposed to regulate the domain under analysis and that allow for explanations, predictions, and simulations -and assertional knowledgee.g., information about specific entities in the domain of interest. Observations are introduced into the domain of quantification of a distinct first-order theory that describes their nature and their organization and takes track of the way they are experimentally acquired or intentionally elaborated. A model mainly represents the theoretical knowledge or hypotheses on a domain, while the theory of observations mainly represents the empirical knowledge and the given experimental practices. We propose a precise identity criterion for observations and we explore different links between models and observations by assuming a degree of independence between them. By exploiting some techniques developed in the field of social choice theory and judgment aggregation, we sketch some strategies to solve inconsistencies between a given set of observations and the assumed theoretical hypotheses. The solutions of these inconsistencies can impact both the observations -e.g., the theoretical knowledge and the analysis of the way observations are collected or produced may highlight some unreliable sources -and the models -e.g., empirical evidences may invalidate some theoretical laws.

Pluralities, Collectives, and Composites

“…First, it requires an additional kind of entity, namely, the rigid embodiments. The nature of rigid embodiments seems quite close to that of states in [36], but Fine, more recently, prefers to liken their ontological status to that of qua-entities [37]. Second, one could assume that variable embodiments are always constituted by rigid embodiments grounded on the same relation R. Even though this assumption seems in line with Rector and colleagues' approach, where composites are always composed by a determinate number of parts [33], it has been considered too restrictive by Jansen and Schulz [3], it does not apply to collectives that can lose or acquire members, and it is not endorsed by Fine himself.…”

Semantically Modeling Cyber Influence Campaigns (CICs): Ontology Model and Case Studies

“…Ontologies are able to logically and conceptually map information, making them versatile and valuable to numerous research fields [89]- [92]. Masolo, Benevides, and Porello [93] proposed a formal framework to examine the relationship between (scientific) models and empirical observations. The study [93] uses an ontological approach to address the problem of observational conclusions and the potential for inconsistencies that underline the knowledge gained from the observations.…”

A review and comparison of ontology-based approaches to robot autonomy

“…An upper-level ontology is an ontology that focuses on widely applicable concepts like object, event, state, quality, and high-level relations like part hood, constitution, participation, and dependence. Examples are SUMO (Suggested Upper Merged Ontology) (Niles & Pease, 2001), Cyc ontology (Lenat & Guha, 1990), Basic Formal Ontology (Arp et al , 2015), and DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering) (Masolo et al , 2003).…”

“…More generally, mental and social objects depend on material acts (like brain activities and communication acts) but they may be neither material (made of matter) nor physical (located in a region of space). A significant number of foundational ontologies make a distinction between and (Masolo et al , 2003; Niles and Pease 2001). Endurants (aka continuants or objects) are wholly present at any time, but may change over time.…”