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Applied ontology is a relatively new field which aims to apply theories and methods from diverse disciplines such as philosophy, cognitive science, linguistics and formal logics to perform or improve domain-specific tasks. To support the…
This paper is based on and advocates the trend in software engineering of extending the use of software patterns as means of structuring solutions to software development problems (be they motivated by best practice or by company interests…
Gene Ontology (GO) is the most important resource for gene function annotation. It provides a way to unify biological knowledge across different species via a dynamic and controlled vocabulary. GO is now widely represented in the Semantic…
The representation of workflows and processes is essential in materials science engineering, where experimental and computational reproducibility depend on structured and semantically coherent process models. Although numerous ontologies…
Ontologies are critical sources of semantic information for many application domains. Hence, there are ontologies proposed and utilized for domains such as medicine, chemical engineering, and electrical energy. In this paper, we present an…
Many platforms for benchmarking optimization algorithms offer users the possibility of sharing their experimental data with the purpose of promoting reproducible and reusable research. However, different platforms use different data models…
This paper studies the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation-Engine…
Ontologies provide a formal description of concepts and their relationships in a knowledge domain. The goal of ontology alignment is to identify semantically matching concepts and relationships across independently developed ontologies that…
The goal is to take a closer look at progress of knowledge engineering in the field of Semantic Web. Along with theory of Knowledge Representation (KR) and knowledge processing methods such as Description Logic (DL), reasoning mechanisms…
The rapid transformation of the labor market, driven by technological advancements and the digital economy, requires continuous competence development and constant adaptation. In this context, traditional competence management systems lack…
Enormous explosion in the number of the World Wide Web pages occur every day and since the efficiency of most of the information processing systems is found to be less, the potential of the Internet applications is often underutilized.…
This paper discusses the representation of ontologies in the first-order logical environment {\ttfamily FOLE}. An ontology defines the primitives with which to model the knowledge resources for a community of discourse. These primitives…
Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse. In this paper, we consider the problem of automated planning, where the objective is to…
The new era of the Web is known as the semantic Web or the Web of data. The semantic Web depends on ontologies that are seen as one of its pillars. The bigger these ontologies, the greater their exploitation. However, when these ontologies…
Understanding large, structured documents like scholarly articles, requests for proposals or business reports is a complex and difficult task. It involves discovering a document's overall purpose and subject(s), understanding the function…
Every business needs knowledge about their competitors to survive better. One of the information repositories is web. Retrieving Specific information from the web is challenging. An Ontological model is developed to capture specific…
Significant efforts have been made to understand and document knowledge related to scientific measurements. Many of those efforts resulted in one or more high-quality ontologies that describe some aspects of scientific measurements, but not…
Ontology alignment is the task of identifying semantically equivalent entities from two given ontologies. Different ontologies have different representations of the same entity, resulting in a need to de-duplicate entities when merging…
The quest for acquiring a formal representation of the knowledge of a domain of interest has attracted researchers with various backgrounds into a diverse field called ontology learning. We highlight classical machine learning and data…
A challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academic and industry. To address this challenge, semantic analysis of textual data is focused in this paper. We…