Processes endure, whereas events occur

In this essay, we aim to help clarify the nature of so-called 'occurrences' by attributing distinct modes of existence and persistence to processes and events. In doing so, we break with the perdurantism claimed by DOLCE’s authors and we distance ourselves from mereological analyzes like those recently conducted by Guarino to distinguish between 'processes' and 'episodes'. In line with the works of Stout and Galton, we first bring closer (physical) processes and objects in their way of enduring by proposing for processes a notion of dynamic presence (contrasting with a static presence for objects). Then, on the events side, we attribute to them the status of abstract entities by identifying them with objects of thought (by individual and collective subjects), and this allows us to distinguish for themselves between existence and occurrence. We therefore identify them with psychological (or even social) endurants, which may contingently occur

Physical processes, their life and their history

Here, I lay the foundations of a high-level ontology of particulars whose structuring principles differ radically from the 'continuant' vs. 'occurrent' distinction traditionally adopted in applied ontology. These principles are derived from a new analysis of the ontology of “occurring” or “happening” entities. Firstly, my analysis integrates recent work on the ontology of processes, which brings them closer to objects in their mode of existence and persistence by assimilating them to continuant particulars. Secondly, my analysis distinguishes clearly between processes and events, in order to make the latter abstract objects of thought (alongside propositions). Lastly, I open my ontological inventory to properties and facts, the existence of which is commonly admitted. By giving specific roles to these primitives, the framework allows one to account for static and dynamic aspects of the physical world and for the way that subjects conceive its history: facts account for the life of substances (physical objects and processes), whereas events enable cognitive subjects to account for the life story of substances

Integration of the DOLCE top-level ontology into the OntoSpec methodology

This report describes a new version of the OntoSpec methodology for ontology building. Defined by the LaRIA Knowledge Engineering Team (University of Picardie Jules Verne, Amiens, France), OntoSpec aims at helping builders to model ontological knowledge (upstream of formal representation). The methodology relies on a set of rigorously-defined modelling primitives and principles. Its application leads to the elaboration of a semi-informal ontology, which is independent of knowledge representation languages. We recently enriched the OntoSpec methodology by endowing it with a new resource, the DOLCE top-level ontology defined at the LOA (IST-CNR, Trento, Italy). The goal of this integration is to provide modellers with additional help in structuring application ontologies, while maintaining independence vis-\`{a}-vis formal representation languages. In this report, we first provide an overview of the OntoSpec methodology's general principles and then describe the DOLCE re-engineering process. A complete version of DOLCE-OS (i.e. a specification of DOLCE in the semi-informal OntoSpec language) is presented in an appendix

An ontological approach to the construction of problem-solving models

Our ongoing work aims at defining an ontology-centered approach for building expertise models for the CommonKADS methodology. This approach (which we have named "OntoKADS") is founded on a core problem-solving ontology which distinguishes between two conceptualization levels: at an object level, a set of concepts enable us to define classes of problem-solving situations, and at a meta level, a set of meta-concepts represent modeling primitives. In this article, our presentation of OntoKADS will focus on the core ontology and, in particular, on roles - the primitive situated at the interface between domain knowledge and reasoning, and whose ontological status is still much debated. We first propose a coherent, global, ontological framework which enables us to account for this primitive. We then show how this novel characterization of the primitive allows definition of new rules for the construction of expertise models

Trois conceptions du processus : les raisons d'un choix

National audienceL'ontologie des entités qualifiées d'« occurrentes »-processus, états et événements-est un domaine actif de recherche auquel nous tâchons de contribuer. Nous avons ainsi proposé récemment un cadre ontologique combinant des processus endurants (plutôt qu'occurrents) et des événements abstraits (plutôt que concrets). L'ontologie des processus, plus particulièrement, continue de connaître des développements, comme en témoigne l'ouvrage édité en 2018 par Rowland Stout Process, Action, and Experience. Toutefois, un constat notoire est qu'aucun consensus ne se dégage sur la nature des processus. Au contraire, trois figures du processus sont actuellement promues : (1) le processus comme continuant dynamique, proche de l'objet dans sa façon d'endurer dans le temps ; (2) le processus comme occurrent étendu temporellement et constituant la « matière » d'événements ; enfin, (3) le processus comme forme temporelle abstraite réalisée par des occurrences concrètes. Dans cet article, nous approfondissons les bases conceptuelles et ontologiques de ces figures. En résultat, nous argumentons en faveur de la figure (1) et en défaveur de la figure (2). Par ailleurs, nous montrons que la figure (3) est compatible avec la figure (1), mais précisons qu'elle caractérise le mouvement plutôt que le processus

A plea for epistemic ontologies

In this article, we advocate the use of “epistemic” ontologies, i.e. systems of categories representing our knowledge of the world, rather than the world directly. We first expose a metaphysical framework based on a dual mental and physical realism, which underpins the development of these epistemic ontologies. To this end, we refer to the theories of intentionality and representation established within the school of Franz Brentano at the turn of the 20th century and choose to rehabilitate the notion of a ‘representation object’, as theorized by Kasimir Twardowski. We therefore propose that the categories of epistemic ontologies correspond to ‘general representation objects’. Secondly, we apply these proposals to the treatment of technical artefacts, material qualities of objects and events (notably as a continuation of our previous work on events). This leads us to sketch out a foundational epistemic ontology

Building a Know-How and Knowing-That Cartography to Enhance KM Processes in a Healthcare Setting

While knowledge management (KM) is becoming an established discipline with many applications and techniques, its adoption in healthcare has been challenging. It facilitates the creation, identification, acquisition, development, preservation, dissemination, and finally utilization of various facets of a healthcare enterprise’s knowledge assets. Knowledge identification and preservation are two facets of knowledge capitalization’s operations. Knowledge cartography is used nowadays as a tool for knowledge identification, sharing, and decision support. In this paper, we propose a Know-How and Knowing-That cartography for Healthcare Information System (HIS) and clinical decision support in the context of the organization of protection of the motor disabled children of Sfax-Tunisia (ASHMS). In fact, this cartography enables decision makers with general and detailed visibility of Know-How and Knowing-That mobilized in the ASHMS. It also facilitates clinical decision support by proposing the most appropriate alternatives for the continued treatment (or cessation) of each motor disabled child receiving treatment

The Green Computing Observatory: a data curation approach for green IT

International audienceThe first barrier to improved energy efficiency is the difficulty of collecting data on the energy consumption of individual components of data centers, and the lack of overall data collection. GCO collects monitoring data on energy consumption of a large computing center, and publish them through the Grid Observatory. These data include the detailed monitoring of the processors and motherboards, as well as the global site information, such as overall consumption and overall cooling. A second barrier is making the collected data usable. The difficulty is to make the data readily consistent and complete, as well as understandable for further exploitation. For this purpose, GCO opts for an ontological approach in order to rigorously define the semantics of the data (what is measured) and the context of their production (how are they acquired and/or calculated). The Green Computing Observatory (GCO) addresses the previous issues within the framework of a production infrastructure dedicated to e-science, providing a unique facility for the Computer Science and Engineering community. The overall goal is to create a full-fledged data curation process. This paper reports on the first achievements, specifically acquisition and ontology