Ontology

In recent years, teaching-learning methods have emerged into a completely new dimension from what used to be a traditional approach. The in-person lectures have been converted into online virtual learning, the traditional record-keeping has been replaced by robust learning management systems which have made the teaching-learning process lot more efficient and convenient.
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This data represent a knowledge graph (KG) that has been populated using a set of diagnostic documents provided by the CSTB (Scientific and technical center for building). This KG contains 51970 triples that describe 2998 product instances, 341 locations, 214 structures and 94 buildings. The construction year of those buildings varies between 1948 and 1997. We have 1525 products that contain asbestos and 1473 products are asbestos-free. To evaluate our approaches, CRA-Miner and the hybrid approache, we divided the KG data into 3 tiers, and we performed cross-validation.
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TreatO is a rice disease control ontology that focuses on modeling biological control agents and chemical controls agent of each rice pest (e.g., rice diseases and insects).
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RiceDO is a rice disease ontology that focuses on modeling abnormal appearances of a rice plant when damaged by pests (e.g., rice diseases and insects).
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An ontology for the multidisciplinary phenomenon of creating web application ove encrypted data
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The compressed file contains:
- Data files in spreadsheet format from three different networks (friendship, companionship and acquaintances).
- Analysis files from UCINET, Pajek, Cytoscape and Gephi.
It is thus possible to corroborate the results mentioned in different studies that refer to these data.
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OntoSNAQA is the name that combines Social Network Analysis (SNA), People and Questionnaires (Question and Answers - QA).
This ontology will be updated in this project of github and in the url http://www.jabenitez.com/ontologies/OntoSNAQA.owl.
It's an ontology that combines three different domains:
- People
- Questionnaires
- Social Network Analysis terms
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