Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.

Ontology-based error detection in SNOMED-CT.

Abstract: Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential areas of improvement. We demonstrate the methodology by applying the algorithms to one of the most popular terminologies, SNOMED-CT. Analysis of the results provides evidence for the thesis that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.

Distributed artificial intelligence and knowledge management : ontologies and multi-agent systems for a corporate semantic web

Abstract: This work concerns multi-agents systems for the management of a corporate semantic web based on an ontology. It was carried out in the context of the European project CoMMA focusing on two application scenarios: support technology monitoring activities and assist the integration of a new employee to the organisation. Three aspects were essentially developed in this work: the design of a multi-agents architecture supporting both scenarios, and the organisational top-down approach followed to identify the societies, the roles and the interactions of agents; the construction of the ontology O'CoMMA and the structuring of a corporate memory exploiting semantic Web technologies; the design and implementation of the sub-societies of agents dedicated to the management of the annotations and the ontology and of the protocols underlying these groups of agents, in particular techniques for distributing annotations and queries between the agents.

A core ontology for business process analysis

Abstract: Business Process Management (BPM) aims at supporting the whole life-cycle necessary to deploy and maintain business processes in organisations. An important step of the BPM life-cycle is the analysis of the processes deployed in companies. However, the degree of automation currently achieved cannot support the level of adaptation required by businesses. Initial steps have been performed towards including some sort of automated reasoning within Business Process Analysis (BPA) but this is typically limited to using taxonomies. We present a core ontology aimed at enhancing the state of the art in BPA. The ontology builds upon a Time Ontology and is structured around the process, resource, and object perspectives as typically adopted when analysing business processes. The ontology has been extended and validated by means of an Events Ontology and an Events Analysis Ontology aimed at capturing the audit trails generated by Process-Aware Information Systems and deriving additional knowledge.

An ontology approach to support FMEA studies

Abstract: FMEA (Failure Modes and Effects Analysis) is a method to analyze potential reliability problems in the development cycle of the project, making it easier to take actions to overcome such issues, thus enhancing the reliability through design. FMEA is used to identify actions to mitigate the analyzed potential failure modes and their effect on the operations. Anticipating these failure modes, being the central step in the analysis, needs to be carried on extensively, in order to prepare a list of maximum potential failure modes. However, the information stored in risk assessment tools is in the form of textual natural language descriptions that limit computer-based extraction of knowledge for the reuse of the FMEA analyses in other designs or during plant operation. To overcome the limitations of text-based descriptions, FMEA ontology has been proposed that provides a basic set of standard concepts and terms. The development of the ontology uses an upper ontology based on ISO-15926, which defines general-purpose terms and act as a foundation for more specific domains. The ontology is developed so that engineers can build new concepts from the basic set of concepts. This paper evaluates the proposed ontology by means of use cases that measure the performance in finding relevant information used and produced during the safety analyses. In particular, the extraction of knowledge is performed using JTP (An object oriented Modular Reasoning System) that is used for querying the ontology.

DOGMA-MESS: a meaning evolution support system for interorganizational ontology engineering

Abstract: In this paper, we explore the process of interorganizational ontology engineering. Scalable ontology engineering is hard to do in interorganizational settings where there are many pre-existing organizational ontologies and rapidly changing collaborative requirements. A complex socio-technical process of ontology alignment and meaning negotiation is therefore required. In particular, we are interested in how to increase the efficiency and relevance of this process using context dependencies between ontological elements. We describe the DOGMA-MESS methodology and system for scalable, community-grounded ontology engineering. We illustrate this methodology with examples taken from a case of interorganizational competency ontology evolution in the vocational training domain.