Claudio Masolo

Sweetening Ontologies with DOLCE

In this paper we introduce the DOLCE upper level ontology, the first module of a Foundational Ontologies Library being developed within the WonderWeb project. DOLCE is presented here in an intuitive way; the reader should refer to the project deliverable for a detailed axiomatization. A comparison with WordNets top-level taxonomy of nouns is also provided, which shows how DOLCE, used in addition to the OntoClean methodology, helps isolating and understanding some major WordNet?s semantic limitations. We suggest that such analysis could hopefully lead to an ?ontologically sweetened? WordNet, meant to be conceptually more rigorous, cognitively transparent, and efficiently exploitable in several applications.

Foundational Choices in DOLCE

Foundational ontologies are ontologies that have a large scope, can be highly reusable in different modeling scenarios, are philosophically and conceptually well founded, and are semantically transparent.

Ontological Foundations of dolce

dolce, the Descriptive Ontology for Linguistic and Cognitive Engineering (Masolo et al., 2003), is a foundational ontology developed embracing a pluralist perspective: there cannot be a unique standard or universal ontology for knowledge representation. Once it is accepted that the so-called “monolithic approach” is unrealistic, it becomes clear that the different foundational ontologies must be mutually transparent by making explicit their ontological stands and formal constraints: this is necessary to make ontology interaction possible and reliable. Roughly, it is expected that an ontology is, on the one hand, philosophically well founded (by adopting a clear ontological perspective) and, on the other hand, that it provides the information for its correct application and use (for instance, by describing explicitly the basic assumptions and the formal constraints on which it relies). A consequence of this view is that, whenever a foundational ontology does not make an explicit commitment with respect to an ontological topic, it is assumed that the ontology is consistent with alternative ontological positions in that topic (in some cases, it may even allow coexistence of these via techniques like parametrization). This general view is quite demanding and requires a careful analysis of the ontology content and structure; dolce has been one of the first ontologies explicitly built to follow (and exemplify) this approach.

In defense of a trope-based ontology for conceptual modeling: an example with the foundations of attributes, weak entities and datatypes

In recent years, there has been a growing interest in approaches that employ foundational ontologies as theoretical tools for analyzing and improving conceptual modeling languages. However, some of these approaches do not always make explicit their ontological commitments. This leads to situations where criticisms resulting from the specific ontological choices made by a particular approach are generalized to the enterprise of ontology as a whole. In this paper we discuss an example of such a case involving the BWW approach. First, we make explicit the ontological commitments underlying that approach by relating it to other possible philosophical alternatives. Second, we construct an ontological theory which commits to a different philosophical position. Third, we show how the ontology proposed here can be used to provide real-world semantics and sound modeling guidelines for the modeling constructs of Attributes, Weak Entities and Datatypes. Finally, we compare the ontology proposed here with BWW, thus demonstrating its benefits.

Ontological Modularity and Spatial Diversity

ABSTRACT In this paper we propose that adequate treatments of space need to be multiperspectival and related to sound foundational ontologies. To support this, we show that natural spatial descriptions commonly appeal to diverse theories of space and these need to be formally combined to be fully interpreted. Our account draws particularly on the foundational ontology DOLCE and the algebraic specification language CASL. We show how the structuring mechanisms of CASL suggest mechanisms for both building and combining multiperspectival ontologies of space. We also suggest that these mechanisms provide a natural link both with currently emerging cognitive principles such as blending and with developments in ontology mediation and mapping.

A well-founded ontological framework for modeling personal income tax

In this paper we present an ontological framework for modeling the core concepts of personal income taxes, based on the Italian law. The ontological analysis focuses on an high-level conceptualization of the main principles of tax legislation, and is largely based on contributions from legal doctrine and the most relevant Italian Constitutional Courts decisions in tax law. As such, the model may serve as a framework to be specialized by further ontological modules. In addition to the core ontological concepts of tax domain, an emphasis is given to the norms application process, which we believe helps to explain the complicated way taxes are imposed. In our approach, the final result of this process is a tax position, which accounts for the relationship between the taxpayer and the treasury with respect to a particular tribute.

The interplay between models and observations

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 knowledge—e.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.