Input data and outputs for the OCALM project
<p>This repository contain a zip file with input and output data for an experiment with OCALM (<a href="https://github.com/fanavarro/ocalm">https://github.com/fanavarro/ocalm</a>):</p> <ul> <li>input <ul> <li>ontologies: ontologies used as input (FoodOn, LKIF, GeneOntology), together with their normalized form.</li> <li>text <ul> <li>food_text: natural language text corpus about food, including the original and the processed text.</li> <li>gene_text: natural language text corpus about genetics, including the original and the processed text.</li> <li>legal_text: natural language text corpus about legal topics, including the original and the processed text.</li> </ul> </li> </ul> </li> <li>results: the results derived from comparing each ontology with each natural language text corpus by using OCALM.</li> <li>NCBO_Recommender_results: the results of the NCBO Recommender with the same experiment performed by OCALM.</li> <li>analysis.R: R script to get figures summarizing the results.</li> </ul> <p>The SNOMED ontology and the medical text corpus used for input were not included due to licensing issues; however, the results are included in this repository.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0