Name: PATRICIA MARÇAL CARNELLI CAMPOS
Type: MSc dissertation
Publication date: 21/10/2019
Advisor:
Name |
Role |
|---|---|
| JOÃO PAULO ANDRADE ALMEIDA | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| JOÃO PAULO ANDRADE ALMEIDA | Advisor * |
| MONALESSA PERINI BARCELLOS | Internal Examiner * |
Summary: Abstract
Data semantic heterogeneity poses a significant challenge to integrated environmental data reuse. This challenge can be addressed with the use of ontologies that can provide a common semantic background for data interpretation, supporting meaning negotiation. However, there are some barriers to build ontologies for data integration in complex domains such as the environmental one. A relevant problem is the development of new ontologies disregarding previous knowledge resources such as reference models and vocabularies. To deal with this problem, in this work, we propose a systematic approach for the identification and selection of reusable knowledge resources for building ontologies with the purpose of scientific research data integration. The approach (dubbed CLeAR) follows some principles of the Systematic Literature Review, supporting the search for knowledge resources in the scientific literature. We apply the approach to the environmental domain, focusing on water quality. A total of 543 publications were surveyed. The results obtained provide a set of 75 knowledge resources for the environmental domain, evaluated according domain coverage and some quality attributes. In the case of water quality data, there is an ample spectrum of subject domains covered (including geographical features, spatial coordinates, environmental quality parameters, measurement activities, sampling activities, involved organizations, etc.). None of the knowledge resources on their own covers all aspects required to address the integration of water quality data. In addition, they are not always explicitly related, which makes them unsuitable for data integration in their current form. Because of this, in this work, we propose the design of a network of reference ontologies for the integration of water quality data, based on some of the identified knowledge resources. The proposed ontology network is grounded in the Unified Foundational Ontology (UFO), which provides basic notions of object, relation, property, event, and others necessary to model the environmental domain, besides allowing the analysis and adaptation of the concepts represented by different knowledge resources, in order to enable their integration into the ontology network.
