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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As a tool of Knowledge Management, knowledge cartography is used, in this paper, to enhance knowledge identification, sharing, representation and visualization in a healthcare organization as well as to deliver healthcare services and improve communication between healthcare professionals. The Know-How and Knowing-That concepts are used, in this paper, instead of the knowledge concept. Know-How is defined as the capacity to perform an action and Knowing-That is defined as a belief state related to a description which can be factual or prescriptive. For the construction of Know-How and Knowing-That cartography, a knowledge cartography methodology is proposed. It is composed of three steps: (i) identifying the concepts to visualize, (ii) identifying the graphical elements and (iii) choosing the cartography technique. This cartography is experimented in the ASHMS (Association of Protection of Motor Disabled of Sfax) to facilitate Know-How and Knowing-That identification, characterization and visualization. [ABSTRACT FROM AUTHOR]

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This paper proposes a Core Ontology of Know-How and Knowing-That (COOK). Know-How and Knowing-That are two types of knowledge according to the epistemological point of view. COOK is founded on work analysis in epistemology, philosophy of capacity/disposition and philosophy of action. This work allows to establish a conceptual analysis of Know-How and Knowing-That. Know-How is defined as the disposition to perform a type of action, whereas Knowing-That is defined as a belief state and concerns a description which can be factual or prescriptive. Taking into account the whole amount of data for an organisation, COOK enhances knowledge identification, decision-making and knowledge sharing among organisation or between different organisations geographically dispersed. Furthermore, COOK is used for the semantic refinement of knowledge evaluation criteria family. These criteria can be related to (i) functional point of view which aims to calculate the contribution degree of Know-How/Knowing-That to the organisation’s objectives, (ii) generic point of view which determines the duration use of Know-How/Knowing-That in the organisation or (iii) ontological point of view which determines vulnerability criteria. [ABSTRACT FROM AUTHOR]

This paper discusses the issues of classification, evaluation and cartography of organizational knowledge in the medical field. Its aim is to propose an Organizational Know-How/Knowing That Decision Support System (O2K-DSS) which can be applied to practical decision situations. O2K-DSS aims to propose a preference model based on multi-criteria decision support tools which allow the selection, the classification and the sorting of decision objects like know-how/knowing that in our case. Our goal is to propose a new category of decision class for ‘likely crucial know-how’/‘likely crucial knowing that’ which represents the subset of knowledge insufficient for knowledge capitalisation at time t. In fact, we classify know-how/knowing that into three decision classes: (1) the first class Cl1 for ‘non crucial know-how’/‘non crucial knowing that’ which represents the subset of knowledge whose level of validation is sufficient for not capitalising it, (2) the second class Cl2 for ‘likely crucial know-how’/‘likely crucial knowing that’ which represents the subset of knowledge whose level of validation is insufficient for capitalising it at time t and (3) the third class Cl3 for ‘crucial know-how’/‘crucial knowing that’ which represents the subset of knowledge whose level of validation is sufficient for capitalising it. These knowledge decision class categories are represented in cartography. [ABSTRACT FROM PUBLISHER]

New performance requirements to adapt to the changing environment and to maintain a competitive advantage have contributed since the 1980s to the emergence of new types of organizations focused on projects or processes. To facilitate the implementation of this process view of organizations, many theorists and practitioners have proposed analysis and modelling frameworks, ontologies being considered as a relevant tool to conduct a ‘semantic analysis’ of business processes. This analysis provides a referential of concepts defined through consensus between domain experts. These concepts should improve the commensurability of the interpretation schemas of the decision makers. Thus, in general, any decision-making process consists of four phases, which are: (1) intelligence, (2) design, (3) choice and (4) evaluation and revision. The ‘design’ phase is aimed at building a repository of concepts collected from the first phase. These concepts model the activity of the organization in terms of knowledge. This knowledge should be shared and adopted by the group decision makers in order to perform any collective decision. Approaches in this area are, however, based on ad hoc, often implicit modelling principles, and the proposed ontologies remain poor in terms of expressiveness. The objective of this paper is to analyse the ontological foundations of the processes of organizations following a formal approach. We propose a core ontology of organization processes which specializes the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) foundational ontology and supplementing Bottazzi and Ferrario’s DOLCE-based formal ontology of organizations. This ontology comprises several modules to reflect both the ‘static’ aspects of organizations and their behaviours, including intentional ones. In this article, we present the contents of the ontology, the formal ontological tools reused for its design, and the various theories the ontology is committed to. [ABSTRACT FROM PUBLISHER]

Copyright of Journal of Decision Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents a formal ontology which accounts for the general nature of artefacts. The objective is to help structure application ontologies in areas where specific artefacts are present - in other words, virtually any area of activity. The conceptualization relies on recent philosophical and psychological research on artefacts, having resulted in a largely consensual theoretical basis. Furthermore, this ontology of artefacts extends the foundational DOLCE ontology and supplements its axiomatization. The conceptual primitives are as follows: artificial entity, intentional production of entities, (state of) capacity, capacity to play a role in actions of a given type, function and functional object. These primitives enable artefacts in general to be characterized as intentionally and successfully produced entities, and isolate an important subclass of 'technical' artefacts to which a function is ascribed. Lastly, we emphasize the novelty of this ontology by comparing it with other works with similar objectives. [ABSTRACT FROM AUTHOR]

Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply superseded by grid services. This paper describes the NeuroLOG platform design and implementation, shedding light on its Data Management Layer. It addresses the integration of brain image files, associated relational metadata and neuroscience semantic data in a heterogeneous distributed environment, integrating legacy data managers through a mediation layer. [ABSTRACT FROM AUTHOR]

This paper describes the design of the NeuroLOG middleware data management layer, which provides a platform to share heterogeneous and distributed neuroimaging data using a federated approach. The semantics of shared information is captured through a multi-layer application ontology and a derived Federated Schema used to align the heterogeneous database schemata from different legacy repositories. The system also provides a facility to translate the relational data into a semantic representation that can be queried using a semantic search engine thus enabling the exploitation of knowledge embedded in the ontology. This work shows the relevance of the distributed approach for neurosciences data management. Although more complex than a centralized approach, it is also more realistic when considering the federation of large data sets, and open strong perspectives to implement multi-centric neurosciences studies.

Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply superseded by grid services. This paper describes the NeuroLOG platform design and implementation, shedding light on its Data Management Layer. It addresses the integration of brain image files, associated relational metadata and neuroscience semantic data in a heterogeneous distributed environment, integrating legacy data managers through a mediation layer.