An Ontology-Based Knowledge Modelling for a Sustainability Assessment Domain

Abstract

Sustainability assessment has received more and more attention from researchers and it offers a large number of opportunities to measure and evaluate the level of its accomplishment. However, proper selection of a particular sustainability assessment approach, reflecting problem properties and the evaluator's preferences, is a complex and important issue. Due to an existing number of different approaches dedicated to assessing, supporting, or measuring the level of sustainability and their structure oriented on the particular domain usage, problems with accurate matching frequently occur. On the other hand, the efficiency of sustainability assessment depends on the available knowledge of the ongoing capabilities. Additionally, actual research trends confirm that knowledge engineering gives a method to handle domain knowledge practically and effectively. Unfortunately, literature studies confirm that there is a lack of knowledge systematization in the sustainability assessment domain, however. The practical application of knowledge-based mechanisms may cover this gap. In this paper, we provide formal, practical and technological guidance to a knowledge management-based approach to sustainability assessment. We propose ontology as a form of knowledge conceptualization and using knowledge engineering, we make gathered knowledge publicly available and reusable, especially in terms of interoperability of collected knowledge.

Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base

“…Ontologies in computer science represent multi-tasking artefacts [18,20] that create a framework for such a view of objects and processes in a given field, in which every emerging concept has a precisely defined meaning [14,25]. The aim of development of ontology is analyzing and organizing our knowledge about the elements of a given field and the ways of expressing it [16,26,27]. From a practical point of view, ontology construction allows making all assumptions underlying our way of capturing the modelled field (including those more or less hidden) [16,24], a multifaceted representation of dependencies between different fragments of the presented slice of reality and defining criteria allowing to unambiguously classify data from a given field [24,28].…”

“…From a formal point of view, concepts and relationships Sustainability 2019, 11, 4208 5 of 41 included in an ontology may be formally processed by intelligent agents [22,26]. As a consequence, the description of a given field of knowledge using an ontology can handle as a basis for inferring the properties of the described ontology [27]. Therefore, an ontology is more than a close representation of our knowledge, because it can provide a flexible platform for building or integrating information and elements of information systems based on them [14].…”

“…Although the ontology concept originated from philosophy, ontology was introduced into the fields of artificial intelligence, information system, knowledge management and others [148], becoming a necessary and important component of professional language in the computer field [149]. The aim of usage of ontology in the field of green-oriented supplier selection criteria is the assurance of knowledge capturing in this field, as well as providing a common understanding of this domain knowledge [27]. To meet this aim, ontology allows identifying common recognition vocabularies, and gives a clear definition of the relationship between these vocabularies from different levels of formal patterns [16].…”

“…Giving the ontology formal description based on the set theory representation is widely adopted and presented in Section 4.2. An ontology's formal description requires specifying components such as individuals, classes, attributes and relations as well as restrictions, rules and axioms [27,33]. As a result, ontologies do not only introduce a sharable and reusable knowledge representation but can also add new knowledge about the domain, as well as they are capable of using a reasoning model [16,31].…”

“…Various ontology construction approaches have been presented recently, offering a systemic and formal way to ontology construction, development and maintenance, i.e., Noy and McGuiness, METHONTOLOGY, and On-To-Knowledge [28,151,152]. Nevertheless common assumptions for a proper ontology design and construction are noticeable, for example term extraction, taxonomy construction and using competency questions to verify the coherence and correctness of constructed ontology [26,27,149]. The aim of the validation process is to provide activities of knowledge structuring and checks the correctness of the implemented knowledge base.…”