On the role of domain ontologies in the design of domain-specific visual modeling langages

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user’s perspective, the language’s modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community

Towards semantic software engineering environments

Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based approach to tool integration and present ODE, an ontology-based SEE

O4OA Specification

This document is the reference ontology specification for the Ontology for Ontological Analysis (O4OA) version 2.6.This work has been developed under the project Digital Knowledge Graph – Adaptable Analytics API with the financial support of Accenture LTD, the Generalitat Valenciana through the CoMoDiD project (CIPROM/2021/023), the Spanish State Research Agency through the DELFOS (PDC2021-121243-I00) and SREC (PID2021-123824OB-I00) projects, MICIN/AEI/10.13039/501 100011033 and co-financed with ERDF and the European Union Next Generation EU/PRTR.Franco Martins Souza, B.; Guizzardi, R.; Pastor López, O. (2023). O4OA Specification. http://hdl.handle.net/10251/19672

Enriching Ontologies with Multilingual Information

Multilinguality in ontologies has become an impending need for institutions worldwide that have to deal with data and linguistic resources in different natural languages. Since most ontologies are developed in one language, obtaining multilingual ontologies implies to localize or adapt them to a concrete language and culture community. As the adaptation of the ontology conceptualization demands considerable efforts, we propose to modify the ontology terminological layer by associating an external repository of linguistic data to the ontology. With this aim we provide a model called Linguistic Information Repository (LIR) that associated to the ontology meta-model allows terminological layer localization

Developing Ontological Theories for Conceptual Models using Qualitative Research

Conceptual modelling is believed to be at the core of the IS discipline. There have been attempts to develop theoretical foundations for conceptual models, in particular ontological models as axiomatic reference systems. Although the notion of ontology has become popular in modelling theories, criticism has risen as to its philosophical presuppositions. Taking on this criticism, we discuss the task of developing socially constructed ontologies for modelling domains and outline how to enhance the expressiveness of ontological modelling theories by developing them via qualitative research methods such as Grounded Theory

Ontology, Ontologies and the "I" of FAIR

According to the FAIR guiding principles, one of the central attributes for maximizing the added value of information artifacts is interoperability. In this paper, I discuss the importance, and propose a characterization of the notion of Semantic Interoperability. Moreover, I show that a direct consequence of this view is that Semantic Interoperability cannot be achieved without the support of, on one hand, (i) ontologies, as meaning contracts capturing the conceptualizations represented in information artifacts and, on the other hand, of (ii) Ontology, as a discipline proposing formal meth- ods and theories for clarifying these conceptualizations and articulating their representations. In particular, I discuss the fundamental role of formal ontological theories (in the latter sense) to properly ground the construction of representation languages, as well as methodological and computational tools for supporting the engineering of ontologies (in the former sense) in the context of FAIR

Towards an ontology for process monitoring and mining

Business Process Analysis (BPA) aims at monitoring, diagnosing, simulating and mining enacted processes in order to support the analysis and enhancement of process models. An effective BPA solution must provide the means for analysing existing e-businesses at three levels of abstraction: the Business Level, the Process Level and the IT Level. BPA requires semantic information that spans these layers of abstraction and which should be easily retrieved from audit trails. To cater for this, we describe the Process Mining Ontology and the Events Ontology which aim to support the analysis of enacted processes at different levels of abstraction spanning from fine grain technical details to coarse grain aspects at the Business Level