相关论文: CODO: An Ontology for Collection and Analysis of C…

Artificial intelligence (AI) has become indispensable for managing and processing the vast amounts of data generated during the COVID-19 pandemic. Ontology, which formalizes knowledge within a domain using standardized vocabularies and…

The ROC ontology for country responses to COVID-19 provides a model for collecting, linking and sharing data on the COVID-19 pandemic. It follows semantic standardization (W3C standards RDF, OWL, SPARQL) for the representation of concepts…

The outbreak of the SARS-CoV-2 pandemic of the new COVID-19 disease (COVID-19 for short) demands empowering existing medical, economic, and social emergency backend systems with data analytics capabilities. An impediment in taking…

This comprehensive study conducts an in-depth analysis of existing COVID-19 ontologies, scrutinizing their objectives, classifications, design methodologies, and domain focal points. The study is conducted through a dual-stage approach,…

The covid19 pandemic is a global emergency that badly impacted the economies of various countries. Covid19 hit India when the growth rate of the country was at the lowest in the last 10 years. To semantically analyze the impact of this…

Motivated by the global unrest related to the COVID-19 pandemic, we present a system prototype for ontology-based, integration of national data published from various countries. COVID-related data is published from different authorities, in…

Public health authorities perform contact tracing for highly contagious agents to identify close contacts with the infected cases. However, during the pandemic caused by coronavirus disease 2019 (COVID-19), this operation was not employed…

The COVID-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on COVID-19 and related historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information retrieval…

Infectious diseases remain a critical global health challenge, and the integration of standardized ontologies plays a vital role in managing related data. The Infectious Disease Ontology (IDO) and its extensions, such as the Coronavirus…

We provide an insight into the open data resources pertinent to the study of the spread of Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behaviour, regional mortality…

To present the biodiversity information, a semantic model is required that connects all kinds of data about living creatures and their habitats. The model must be able to encode human knowledge for machines to be understood. Ontology offers…

Objective: This study aims to consider small graphs of concepts and exploit them for expressing graph searches over existing COVID-19-related literature, leveraging the increasing use of graphs to represent and query scientific knowledge…

The widely spread CoronaVirus Disease (COVID)-19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively…

Recently ontologies have been exploited in a wide range of research areas for data modeling and data management. They greatly assists in defining the semantic model of the underlying data combined with domain knowledge. In this paper, we…

The Core Data Ontology (CDO) and the Informatics Domain Model represent a transformative approach to computational systems, shifting from traditional node-centric designs to a data-centric paradigm. This paper introduces a framework where…

Data quality assessment and data cleaning are context-dependent activities. Motivated by this observation, we propose the Ontological Multidimensional Data Model (OMD model), which can be used to model and represent contexts as logic-based…

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. Topic modelling can provide, psychological, social and cultural insights for understanding human behaviour in…

Because of the rapid spread of COVID-19 to almost every part of the globe, huge volumes of data and case studies have been made available, providing researchers with a unique opportunity to find trends and make discoveries like never…

CoCoE stands for Complexity, Coherence and Entropy, and presents an extensible methodology for empirical analysis of Linked Open Data (i.e., RDF graphs). CoCoE can offer answers to questions like: Is dataset A better than B for knowledge…

An ontology of the DDI 3 data model will be designed by following the ontology engineering methodology to be evolved based on state-of-the-art methodologies. Hence DDI 3 data and metadata can be represented in form of a standard web…