TeSS Training eSupport System

Applying data standards to the harmonization of COVID-19 datasets from different sources

This video describes how public health genomics has played a key role in international responses to the COVID-19 pandemic, and how data standards are being used to harmonize data across jurisdictions for Canadian COVID-19 surveillance and outbreak investigations.

Scientific topics: Data integration and warehousing

Keywords: Data integration, Standards, Standardised vocabulary, data harmonization, Ontologies

Resource type: Video

Applying data standards to the harmonization of COVID-19 datasets from different sources https://www.youtube.com/watch?v=Z20ZOrtQ7Cs http://tess.elixir-uk.org/materials/applying-data-standards-to-the-harmonization-of-covid-19-datasets-from-different-sources This video describes how public health genomics has played a key role in international responses to the COVID-19 pandemic, and how data standards are being used to harmonize data across jurisdictions for Canadian COVID-19 surveillance and outbreak investigations. Emma Griffiths Data integration and warehousing Data integration, Standards, Standardised vocabulary, data harmonization, Ontologies Anyone interested in data standardization and/or the ontology approach (i.e. public, end users).

Useful ontologies for harmonizing cohort data

This video describes a community of practice for interoperable ontology building called the OBO Foundry, and highlights a number of well curated and maintained ontologies that are useful for annotating cohort data.

Scientific topics: Ontology and terminology, Data management, Data integration and warehousing

Keywords: Ontologies, Cohort data, data annotation

Resource type: Video

Useful ontologies for harmonizing cohort data https://www.youtube.com/watch?v=7m6xtJEh1WE http://tess.elixir-uk.org/materials/useful-ontologies-for-harmonizing-cohort-data This video describes a community of practice for interoperable ontology building called the OBO Foundry, and highlights a number of well curated and maintained ontologies that are useful for annotating cohort data. Emma Griffiths Ontology and terminology Data management Data integration and warehousing Ontologies, Cohort data, data annotation Anyone interested in data standardization and/or the ontology approach (i.e. public, end users).

Annotating data using ontologies

This video highlights examples of tools and ontologies which can be used for annotating health data, and how ontologies help to support data ecosystems.

Scientific topics: Ontology and terminology, Data integration and warehousing, Data management

Keywords: Ontologies, Annotation, Data integration

Resource type: Video

Annotating data using ontologies https://www.youtube.com/watch?v=lFqpuZfv_8o http://tess.elixir-uk.org/materials/annotating-data-using-ontologies This video highlights examples of tools and ontologies which can be used for annotating health data, and how ontologies help to support data ecosystems. Emma Griffiths Ontology and terminology Data integration and warehousing Data management Ontologies, Annotation, Data integration

Solutions for overcoming cohort data integration challenges using ontology: an introduction

Ontologies are collections of well-defined, hierarchical, controlled vocabulary, linked by logical relationships. This video introduces the concept and benefits of implementing ontologies for solving data integration issues when data is generated by different research groups.

Scientific topics: Data management, Data integration and warehousing, Ontology and terminology

Keywords: Ontologies, Data integration, Annotation

Resource type: Video

Solutions for overcoming cohort data integration challenges using ontology: an introduction https://www.youtube.com/watch?v=mk7LfUIQe6U http://tess.elixir-uk.org/materials/solutions-for-overcoming-cohort-data-integration-challenges-using-ontology-an-introduction Ontologies are collections of well-defined, hierarchical, controlled vocabulary, linked by logical relationships. This video introduces the concept and benefits of implementing ontologies for solving data integration issues when data is generated by different research groups. Emma Griffiths Data management Data integration and warehousing Ontology and terminology Ontologies, Data integration, Annotation

Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics https://bioinformaticsdotca.github.io/metabolomics_2018 http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-6-future-of-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. David Wishart Researchers Post-Doctoral Fellows Graduate students Biologists, Genomicists, Computer Scientists

Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data https://bioinformaticsdotca.github.io/metabolomics_2018 http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-3-databases-for-chemical-spectral-and-biological-data Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. David Wishart Researchers Post-Doctoral Fellows Graduate Students Biologists, Genomicists, Computer Scientists

Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation https://bioinformaticsdotca.github.io/metabolomics_2018 http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-2-metabolite-identification-and-annotation Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. David Wishart Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists

Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics https://bioinformaticsdotca.github.io/metabolomics_2018 http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-1-introduction-to-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. David Wishart Researchers Graduate Students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists

Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics