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An Ontology for Collection and Analysis of COviD-19 Data
Last uploaded:
October 8, 2020
Acronym | CODO |
Visibility | Public |
Description | This COVID-19 Ontology is a data model for publishing COVID-19 data on the Web as a Knowledge Graph. The primary focuses of the model are (1) COVID-19 cases: the data for COVID-19 cases (e.g., active, recovered, deceased, migrated) on daily basis across the geo-location (district, state (province), and country), available resources and requirements; (2) COVID-19 patient data: nationality, symptom, suspected level of COVID -19, treatment facility, COVID-19 clinical facility, patient's travel history, inter-personal relationships between patients, suspected transmission reason, tracking of patient test results, etc. |
Status | Beta |
Format | OWL |
Contact | Dutta, Biswanath , dutta2005@gmail.com, bisu@drtc.isibang.ac.in Michael DeBellis , mdebellissf@gmail.com |
Categories | Health, Human, Vocabularies |
- CIDOnto
- A COVID-19 diseases ontology for both before and after the COVID-19 is called CIDOnto. Just the nodes and node labels are shown here for the knowledge-based graph. Understanding Pakistan's data and the overall process would be made easier.
Classes | 90 |
Individuals | 271 |
Properties | 123 |
Maximum depth | 4 |
Maximum number of children | 13 |
Average number of children | 3 |
Classes with a single child | 6 |
Classes with more than 25 children | 0 |
Classes with no definition | 34 |