Gilles Kassel

A Core Ontology of Business Processes Based on DOLCE

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 theoreticians and practitioners have proposed analysis and modeling frameworks, ontologies being considered as a relevant tool to conduct a “semantic analysis” of business processes. Approaches in this area are, however, based on ad hoc, often implicit modeling principles and the proposed ontologies remain poor in terms of expressiveness. The objective of this paper is to analyze the ontological foundations of the business processes following a formal approach. We propose a core ontology of business processes specializing the 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 behaviors, including intentional ones. In the 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.

Towards identifying sensitive processes for knowledge localization

In this paper we propose a set of criteria in order to identify the sensitive processes of an organization. The analysis of these processes is necessary to locate knowledge that need to be capitalized. We follow both bottom-up and top-down approach. The former consists on collecting concrete indicators to guide decision makers and to argue on decisions. These indicators should allow building an initial list of criteria. The latter consists on declining one or several global points of view. This new approach elicits preference of decision makers to identify sensitive process. The applicative framework of this research work was done in collaboration with the association of protection of motors disabled of Sfax - Tunisia (ASHMS).

COOP: A core ontology of organization’s processes for group decision making

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.

The Green Computing Observatory: A Data Curation Approach for Green IT

The Green Computing Observatory (GCO) creates a full-fledged data curation process for green IT, providing a unique facility for the Computer Science and Engineering community. The 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. A second barrier is making the collected 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).

A decision support system for identifying sensitive organization’s processes

In order to facilitate the implementation of the organization’s process view, many theorists and practitioners have proposed approaches to characterize and identify the organization’s processes. In this respect, we can cite the business process reengineering, the process innovation, the information system, the quality approach, and the strategic process identification. However, there are no scientific works which propose mathematical models and tools to support the operation of identifying sensitive organization’s processes, i.e. the processes that can mobilize crucial knowledge to be capitalized. The objective of this paper is to introduce OP-DSS, a Decision Support System for identifying a sensitive Organization’s Processes. OP-DSS is an implementation of a two phase-based methodology conducted in the association of protection of motors disabled of Sfax-Tunisia. The first phase is the construction of the preference model. The second is the classification of the potential sensitive organization’s processes. This methodology is based on the multi-criteria decision making approach. In particular, we use the Dominance based Rough Set Approach (DRSA) to infer the decision rules used to define the sensitive organization’s processes. In this paper the attention is especially devoted to present the conceptual and the functional architectures of OP-DSS.

A Multilayer Ontology of Instruments for Neurological, Behavioral and Cognitive Assessments.

Advances in neuroscience are underpinned by large, multicenter studies and a mass of heterogeneous datasets. When investigating the relationships between brain anatomy and brain functions under normal and pathological conditions, measurements obtained from a broad range of brain imaging techniques are correlated with the information on each subject’s neurologic states, cognitive assessments and behavioral scores derived from questionnaires and tests. The development of ontologies in neuroscience appears to be a valuable way of gathering and handling properly these heterogeneous data – particularly through the use of federated architectures. We recently proposed a multilayer ontology for sharing brain images and regions of interest in neuroimaging. Here, we report on an extension of this ontology to the representation of instruments used to assess brain and cognitive functions and behavior in humans. This extension consists of a ‘core’ ontology that accounts for the properties shared by all instruments supplemented by ‘domain’ ontologies that conceptualize standard instruments. We also specify how this core ontology has been refined to build domain ontologies dedicated to widely used instruments and how various scores used in the neurosciences are represented. Lastly, we discuss our design choices, the ontology’s limitations and planned extensions aimed at querying and reasoning across distributed data sources.

A decision support system for identifying and representing likely crucial organizational know-how and knowing that

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.

Présentation « sur mesure » d'informations : Une approche appliquée aux mémoires organisationnelles

Our research project aims at elaborating hybrid Organizational Semantic Webs (O-SWs), based on a strong coupling between a Knowledge Base (KB) and a Documents Base (DocB). The capitalized knowledge is hence distributed among the KB and the DocB. The interest of modeling pieces of knowledge is that it allows the OSW to reason about this knowledge in order to assist users in their knowledge management tasks. In counterpart the distribution of knowledge among heterogeneous sources renders its access more complicated. In order to overcome these difficulties, we propose, on the one hand, to introduce a model of the information contained in the OSW, while making abstraction of its mode of specification, and, on the other hand, to couple this model with a mechanism of dynamic generation of presentations of targeted information whose contents is adapted to the user. In this paper, we present an overview of this approach.

A Core Ontology of Know-How and Knowing-That for improving knowledge sharing and decision making in the digital age

Abstract 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.