# CODO: An Ontology for Collection and Analysis of Covid-19 Data

arXiv: https://arxiv.org/abs/2009.01210 · HTML: https://mlsanity.com/paper/2009.01210/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2020.

## Built on by (most cited first, 11 of 11)

- [AMV : Algorithm Metadata Vocabulary](https://mlsanity.com/paper/2106.03567/) (2021)
- [iTelos -- Purpose Driven Knowledge Graph Generation](https://mlsanity.com/paper/2105.09418/) (2021)
- [An Overview of Ontologies and Tool Support for COVID-19 Analytics](https://mlsanity.com/paper/2110.06397/) (2021)
- [An Approach for Automatic Construction of an Algorithmic Knowledge Graph from Textual Resources](https://mlsanity.com/paper/2205.06854/) (2022)
- [Bias in ontologies -- a preliminary assessment](https://mlsanity.com/paper/2101.08035/) (2021)
- [ROC: An Ontology for Country Responses towards COVID-19](https://mlsanity.com/paper/2104.07345/) (2021)
- [Development of the InBan_CIDO Ontology by Reusing the Concepts along with Detecting Overlapping Information](https://mlsanity.com/paper/2108.06742/) (2021)
- [User Experience Design for Automatic Credibility Assessment of News Content About COVID-19](https://mlsanity.com/paper/2204.13943/) (2022)
- [CIRO: COVID-19 infection risk ontology](https://mlsanity.com/paper/2308.09719/) (2023)
- [Rediscovering Ranganathan: A Prismatic View of His Life through the Knowledge Graph Spectrum](https://mlsanity.com/paper/2401.03343/) (2023)
- [Development of CODO: A Comprehensive Tool for COVID-19 Data Representation, Analysis, and Visualization](https://mlsanity.com/paper/2411.02423/) (2024)

## Abstract (arXiv)

The COviD-19 Ontology for cases and patient information (CODO) provides a model for the collection and analysis of data about the COVID-19 pandemic. The ontology provides a standards-based open-source model that facilitates the integration of data from heterogeneous data sources. The ontology was designed by analysing disparate COVID-19 data sources such as datasets, literature, services, etc. The ontology follows the best practices for vocabularies by re-using concepts from other leading vocabularies and by using the W3C standards RDF, OWL, SWRL, and SPARQL. The ontology already has one independent user and has incorporated real-world data from the government of India.