Preparing Data at the Source to Foster Interoperability across Rare Disease Resources.
The ability to combine heterogeneous data distributed across the globe is critically important to boost research on rare diseases, but it presents a number of methodological, representational and automation challenges. In this scenario, biomedical ontologies are of critical importance for enabling c...
| Autores: | , , |
|---|---|
| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Instituto de Salud Carlos III (ISCIII) |
| Repositorio: | Repisalud |
| Idioma: | inglés |
| OAI Identifier: | oai:repisalud.isciii.es:20.500.12105/26095 |
| Acceso en línea: | https://hdl.handle.net/20.500.12105/26095 |
| Access Level: | acceso abierto |
| Palabra clave: | Data integration FAIR approach Linkable data Ontologies Semantic model Standardization Biomedical Research Data Accuracy Databases, Factual Guidelines as Topic Health Information Interoperability Humans Quality Control Rare Diseases Registries Research Design |
| Sumario: | The ability to combine heterogeneous data distributed across the globe is critically important to boost research on rare diseases, but it presents a number of methodological, representational and automation challenges. In this scenario, biomedical ontologies are of critical importance for enabling computers to aid in information retrieval and analysis across data collections.This chapter presents an approach to preparing rare disease data for integration through the application of a global standard for computer-readable data and knowledge. This includes the use of common data elements, ontological codes and computer-readable data. This approach was developed under a number of domain-relevant requirements, such as controlled access to data, independence of the original sources, and the desire to combining the data sources with other computational workflows and data platforms. |
|---|