Jekyll 2025-11-06T14:24:17+00:00 https://training.galaxyproject.org/training-material/topics/fair/feed.xml Recently added tutorials, slides, FAQs, and events in the fair topic https://training.galaxyproject.org/training-material/assets/images/GTN-60px.png https://training.galaxyproject.org/training-material/topics/fair/tutorials/inveniordm-integration/tutorial.html 2025-11-06T14:24:17+00:00

Overview

Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ David López https://training.galaxyproject.org/training-material/hall-of-fame/davelopez/ Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ Teresa Müller https://training.galaxyproject.org/training-material/hall-of-fame/teresa-m/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ David López https://training.galaxyproject.org/training-material/hall-of-fame/davelopez/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/zenodo-in-galaxy/tutorial.html 2025-11-06T14:24:17+00:00

Discover a more streamlined approach to research data management with Galaxy’s integration with Zenodo.

Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ David López https://training.galaxyproject.org/training-material/hall-of-fame/davelopez/ Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ Teresa Müller https://training.galaxyproject.org/training-material/hall-of-fame/teresa-m/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ David López https://training.galaxyproject.org/training-material/hall-of-fame/davelopez/ https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-cite/tutorial.html 2025-11-06T14:24:17+00:00

Overview

Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ Gareth Price https://training.galaxyproject.org/training-material/hall-of-fame/GarethPrice-Aus/ Mirela Minkova https://training.galaxyproject.org/training-material/hall-of-fame/mirelaminkova/ Marisa Loach https://training.galaxyproject.org/training-material/hall-of-fame/MarisaJL/ Tristan Reynolds https://training.galaxyproject.org/training-material/hall-of-fame/tflowers15/ Teresa Müller https://training.galaxyproject.org/training-material/hall-of-fame/teresa-m/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ David López https://training.galaxyproject.org/training-material/hall-of-fame/davelopez/ https://training.galaxyproject.org/training-material/news/2025/09/02/gtn-workflowhub.html 2025-09-02T00:00:00+00:00

Thanks to a collaborative effort between the teams at Galaxy Training Network (GTN), WorkflowHub, and Australian BioCommons, GTN workflows are now registered automatically with WorkflowHub. The existing set of workflows can be viewed here: GTN on WorkflowHub. For every new tutorial that is added to the GTN, any workflows that it contains will now also be pushed to WorkflowHub.

Johan Gustafsson https://training.galaxyproject.org/training-material/hall-of-fame/supernord/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Finn Bacall https://training.galaxyproject.org/training-material/hall-of-fame/fbacall/ Bert Droesbeke https://training.galaxyproject.org/training-material/hall-of-fame/bedroesb/ Eli Chadwick https://training.galaxyproject.org/training-material/hall-of-fame/elichad/ Armin Dadras https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Frederik Coppens https://training.galaxyproject.org/training-material/hall-of-fame/frederikcoppens/ Carole Goble https://training.galaxyproject.org/training-material/hall-of-fame/carolegoble/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Finn Bacall https://training.galaxyproject.org/training-material/hall-of-fame/fbacall/ Bert Droesbeke https://training.galaxyproject.org/training-material/hall-of-fame/bedroesb/ Uwe Winter https://training.galaxyproject.org/training-material/hall-of-fame/uwwint/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Frederik Coppens https://training.galaxyproject.org/training-material/hall-of-fame/frederikcoppens/ Carole Goble https://training.galaxyproject.org/training-material/hall-of-fame/carolegoble/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/earth_system_rocrate/slides.html 2024-12-02T09:01:23+00:00

Workflow context

Marie Josse https://training.galaxyproject.org/training-material/hall-of-fame/Marie59/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/dataplant-arcs/slides.html 2024-10-24T14:04:48+00:00

About DataPLANT

Dominik Brilhaus https://training.galaxyproject.org/training-material/hall-of-fame/Brilator/ Cristina Martins Rodrigues https://training.galaxyproject.org/training-material/hall-of-fame/CMR248/ Kevin Frey https://training.galaxyproject.org/training-material/hall-of-fame/Freymaurer/ Martin Kuhl https://training.galaxyproject.org/training-material/hall-of-fame/Martin-Kuhl/ Sabrina Zander https://training.galaxyproject.org/training-material/hall-of-fame/SabrinaZander/ Stella Eggels https://training.galaxyproject.org/training-material/hall-of-fame/StellaEggels/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/dataplant-arcs/tutorial.html 2024-10-22T15:22:19+00:00

In this tutorial we will guide you through the process of creating your ARC (Annotated Research Context)

Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Dominik Brilhaus https://training.galaxyproject.org/training-material/hall-of-fame/Brilator/ Sabrina Zander https://training.galaxyproject.org/training-material/hall-of-fame/SabrinaZander/ Cristina Martins Rodrigues https://training.galaxyproject.org/training-material/hall-of-fame/CMR248/ Kevin Frey https://training.galaxyproject.org/training-material/hall-of-fame/Freymaurer/ Martin Kuhl https://training.galaxyproject.org/training-material/hall-of-fame/Martin-Kuhl/ Stella Eggels https://training.galaxyproject.org/training-material/hall-of-fame/StellaEggels/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/data-management-peatlands/tutorial.html 2024-09-13T12:19:47+00:00

Peatland monitoring and research generates data that is used for management, conservation and policy related to these ecosystems. To ensure that your project data is collected systematically and can be analysed, shared, and re-used it is important to have a data management plan.

Gabriela Lopez-Gonzalez https://training.galaxyproject.org/training-material/hall-of-fame/GabrielaLopez/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Emily Angiolini https://training.galaxyproject.org/training-material/hall-of-fame/angiolini/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/bioimage-REMBI/recordings/#tutorial-recording-12-september-2024 2024-09-12T00:00:00+00:00

A 48M14S long recording is now available.

Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-clinical/recordings/#tutorial-recording-12-september-2024 2024-09-12T00:00:00+00:00

A 1H2M54S long recording is now available.

Sandra Ng https://training.galaxyproject.org/training-material/hall-of-fame/SNG888/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/data-management-peatlands/recordings/#tutorial-recording-12-september-2024 2024-09-12T00:00:00+00:00

A 1H1M41S long recording is now available.

Gabriela Lopez-Gonzalez https://training.galaxyproject.org/training-material/hall-of-fame/GabrielaLopez/ https://training.galaxyproject.org/training-material/topics/computational-chemistry/tutorials/med-chem-data/recordings/#tutorial-recording-12-september-2024 2024-09-12T00:00:00+00:00

A 48M1S long recording is now available.

Julia Jakiela https://training.galaxyproject.org/training-material/hall-of-fame/wee-snufkin/ https://training.galaxyproject.org/training-material/events/2024-06-18-FAIR-data-management.html 2024-06-04T15:45:47+00:00

This course will introduce the Galaxy Platform, covering the basic functionality for single-cell data processing. It will include an overview of various common single-cell datatypes used in bioinformatics. Participants will gain hands-on experience loading single-cell data from external resources into Galaxy, parsing academic literature to find relevant metadata, and converting the data into the common AnnData format, ready for further analysis in Galaxy.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Morgan Howells https://training.galaxyproject.org/training-material/hall-of-fame/hexhowells/ Wendi Bacon https://training.galaxyproject.org/training-material/hall-of-fame/nomadscientist/ https://training.galaxyproject.org/training-material/news/2024/05/13/fair.html 2024-05-13T00:00:00+00:00

We are happy to report that over the years of our fruitful collaboration with ELIXIR TeSS, all GTN materials should receive a perfect score on the FAIR-Checker.

Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Bérénice Batut https://training.galaxyproject.org/training-material/hall-of-fame/bebatut/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-rna/tutorial.html 2024-03-27T09:25:48+00:00

RNA sequencing is chosen here as an example of how to FAIRify data for a popular assay in the Life Sciences. RNAseq data can be shared and curated in designated public repositories using established ontologies (and controlled vocabularies) for describing protocols and biological material (metadata).

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/learning-pathways/fair-training.html 2024-03-26T08:27:31+00:00

The FAIR data management training learning pathway teaches you how to organise, describe, and store research data according to the FAIR principles (Findable, Accessible, Interoperable, Reusable).

https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-data-registration/tutorial.html 2024-03-26T08:27:31+00:00

The concept of data registration is defined as well as ways in which data registration can be achieved. Learners will be able to describe why indexed data repositories are important as well as resources enabling you to choose a searchable repository.

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Nick Juty https://training.galaxyproject.org/training-material/hall-of-fame/nsjuty/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Nicola Soranzo https://training.galaxyproject.org/training-material/hall-of-fame/nsoranzo/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Kellie Snow https://training.galaxyproject.org/training-material/hall-of-fame/kellsnow/ Korneel Hens https://training.galaxyproject.org/training-material/hall-of-fame/khens/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Saskia Lawson-Tovey https://training.galaxyproject.org/training-material/hall-of-fame/saskia-lawson-tovey/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-origin/tutorial.html 2024-03-26T08:27:31+00:00

FAIR as an acronym, its origins and its guiding principles are introduced. Learners will be able to explain the difference between FAIR and open data and contextualise the main principles of FAIR around the common characteristics of identifiers, access, metadata and registration.

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Nick Juty https://training.galaxyproject.org/training-material/hall-of-fame/nsjuty/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Nicola Soranzo https://training.galaxyproject.org/training-material/hall-of-fame/nsoranzo/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Kellie Snow https://training.galaxyproject.org/training-material/hall-of-fame/kellsnow/ Korneel Hens https://training.galaxyproject.org/training-material/hall-of-fame/khens/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Saskia Lawson-Tovey https://training.galaxyproject.org/training-material/hall-of-fame/saskia-lawson-tovey/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-persistent-identifiers/tutorial.html 2024-03-26T08:27:31+00:00

The persistent identifier is defined. Learners will be able to define the structure of an identifier and explain its importance.

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Nick Juty https://training.galaxyproject.org/training-material/hall-of-fame/nsjuty/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Nicola Soranzo https://training.galaxyproject.org/training-material/hall-of-fame/nsoranzo/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Kellie Snow https://training.galaxyproject.org/training-material/hall-of-fame/kellsnow/ Korneel Hens https://training.galaxyproject.org/training-material/hall-of-fame/khens/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Saskia Lawson-Tovey https://training.galaxyproject.org/training-material/hall-of-fame/saskia-lawson-tovey/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-metadata/tutorial.html 2024-03-26T08:27:31+00:00

The term metadata is defined along with what constitutes rich metadata. Learners will be able to recall examples of community/domain standards that apply to data and metadata.

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Nick Juty https://training.galaxyproject.org/training-material/hall-of-fame/nsjuty/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Nicola Soranzo https://training.galaxyproject.org/training-material/hall-of-fame/nsoranzo/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Kellie Snow https://training.galaxyproject.org/training-material/hall-of-fame/kellsnow/ Korneel Hens https://training.galaxyproject.org/training-material/hall-of-fame/khens/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Saskia Lawson-Tovey https://training.galaxyproject.org/training-material/hall-of-fame/saskia-lawson-tovey/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-access/tutorial.html 2024-03-26T08:27:31+00:00

Data access including levels of access are described. Learners will be able to illustrate data access in terms of the FAIR Principles using companion terms including communications protocol and authentication. Learners will also be able to interpret the data usage licence associated with different data sets

Robert Andrews https://training.galaxyproject.org/training-material/hall-of-fame/robertmand/ Nick Juty https://training.galaxyproject.org/training-material/hall-of-fame/nsjuty/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Nicola Soranzo https://training.galaxyproject.org/training-material/hall-of-fame/nsoranzo/ Sara Morsy https://training.galaxyproject.org/training-material/hall-of-fame/saramorsy/ Kellie Snow https://training.galaxyproject.org/training-material/hall-of-fame/kellsnow/ Korneel Hens https://training.galaxyproject.org/training-material/hall-of-fame/khens/ Philippe Rocca-Serra https://training.galaxyproject.org/training-material/hall-of-fame/proccaserra/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/lcooper/ Xenia Perez Sitja https://training.galaxyproject.org/training-material/hall-of-fame/sitjart/ Andrew Mason https://training.galaxyproject.org/training-material/hall-of-fame/asmasonomics/ Branka Franicevic https://training.galaxyproject.org/training-material/hall-of-fame/bfranicevic/ Saskia Lawson-Tovey https://training.galaxyproject.org/training-material/hall-of-fame/saskia-lawson-tovey/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/news/2024/03/26/FAIR-pointers.html 2024-03-26T00:00:00+00:00

ELIXIR-UK’s Data Stewardship Fellowship is excited to announce a new learning pathway focused on FAIR Data Management! This program equips researchers and research support staff with the skills to effectively manage their research data.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ https://training.galaxyproject.org/training-material/news/2024/01/17/sc-fair-data.html 2024-01-17T00:00:00+00:00

New single cell section: Changing data formats & preparing objects

Julia Jakiela https://training.galaxyproject.org/training-material/hall-of-fame/wee-snufkin/ Morgan Howells https://training.galaxyproject.org/training-material/hall-of-fame/hexhowells/ Wendi Bacon https://training.galaxyproject.org/training-material/hall-of-fame/nomadscientist/ https://training.galaxyproject.org/training-material/topics/computational-chemistry/tutorials/med-chem-data/tutorial.html 2024-01-08T09:55:32+00:00

The development of medicinal chemistry is advancing very rapidly. Big pharmaceutical companies, research institutes and universities are working on ground-breaking solutions to help patients combat all kinds of diseases. During that development process, tons of data are generated – not only from the lab environment but also from clinical trials. Given that the discovery of more potent, safer and cheaper drugs is the ultimate goal of all research bodies, we should all focus on making the data we gather FAIR: Findable, Accessible, Interoperable, and Reusable to push the boundaries of drug development even further.

Julia Jakiela https://training.galaxyproject.org/training-material/hall-of-fame/wee-snufkin/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Simon Bray https://training.galaxyproject.org/training-material/hall-of-fame/simonbray/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-ena/tutorial.html 2023-11-01T08:38:03+00:00

DNA sequencing has become one of the key technologies in molecular biology, with applications in diagnostics, evolutionary biology, drug discovery, forensics and much more. Drop in sequencing costs and breakthroughs in sequencing technologies has seen increasing utilization of sequencing as a research tool, featuring in thousands of life-science publications every year.

Sonal Henson https://training.galaxyproject.org/training-material/hall-of-fame/sonalhenson/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Munazah Andrabi https://training.galaxyproject.org/training-material/hall-of-fame/smza/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Gareth Price https://training.galaxyproject.org/training-material/hall-of-fame/GarethPrice-Aus/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-clinical/tutorial.html 2023-10-24T09:11:59+00:00

The life science community is generally very good at sharing omics data on platforms such as GEO and ArrayExpress. However, the metadata and clinical data associated with the omics datasets are often incredibly sparse. Tracking down the meta- and clinical data of omics datasets can be time-consuming for both data owner and researcher and is a significant hurdle when trying to explore enriched omics data.

Sandra Ng https://training.galaxyproject.org/training-material/hall-of-fame/SNG888/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Tim Beck https://training.galaxyproject.org/training-material/hall-of-fame/tb143/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/bioimage-REMBI/tutorial.html 2023-09-13T09:31:14+00:00

Metadata guidelines for bioimaging data

Julia Jakiela https://training.galaxyproject.org/training-material/hall-of-fame/wee-snufkin/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/Laura190/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Leonid Kostrykin https://training.galaxyproject.org/training-material/hall-of-fame/kostrykin/ Beatriz Serrano-Solano https://training.galaxyproject.org/training-material/hall-of-fame/beatrizserrano/ Paul De Geest https://training.galaxyproject.org/training-material/hall-of-fame/pauldg/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/bioimage-metadata/tutorial.html 2023-09-13T09:31:14+00:00

FAIR Bioimaging

Julia Jakiela https://training.galaxyproject.org/training-material/hall-of-fame/wee-snufkin/ Laura Cooper https://training.galaxyproject.org/training-material/hall-of-fame/Laura190/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Leonid Kostrykin https://training.galaxyproject.org/training-material/hall-of-fame/kostrykin/ Beatriz Serrano-Solano https://training.galaxyproject.org/training-material/hall-of-fame/beatrizserrano/ Paul De Geest https://training.galaxyproject.org/training-material/hall-of-fame/pauldg/ https://training.galaxyproject.org/training-material/news/2023/06/21/fair.html 2023-06-21T00:00:00+00:00

Katarzyna Kamieniecka (University of Bradford), a member of the ELIXIR-UK Fellowship Programme, has just launched a new series of lessons to improve Findable Accessible Interoperable Reusable (FAIR) data management in the life sciences. The lessons are designed to help researchers and research support staff understand the principles of FAIR data management and apply them to their own work.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-gtn/tutorial.html 2023-05-30T12:53:37+00:00

Encouraging computational reproducibility in research, we will present a variety of data stewardship recommendations that we have found useful in the process of training development. As part of that process, we are exploring the application of the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines to the Galaxy Training Network (GTN) materials, in order to improve their secondary use and adaptation.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Wendi Bacon https://training.galaxyproject.org/training-material/hall-of-fame/nomadscientist/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/data-management/tutorial.html 2023-05-30T12:53:37+00:00

The FAIR (Findable, Accessible, Interoperable, Reusable) data stewardship created the foundation for sharing and publishing digital assets, especially data. This apply to machine accessibility and emphasize that all digital assets should share data in a way that will enable maximum use and reuse.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/fair-intro/tutorial.html 2023-05-30T12:53:37+00:00

The FAIR (Findable, Accessible, Interoperable, Reusable) principles emphasize machine-actionability. The main objective of FAIR is to increase data reuse by researchers. The core concepts of the FAIR principles are based on good scientific practice and intuitively grounded.

Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Krzysztof Poterlowicz https://training.galaxyproject.org/training-material/hall-of-fame/poterlowicz-lab/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Katarzyna Kamieniecka https://training.galaxyproject.org/training-material/hall-of-fame/kkamieniecka/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Khaled Jum'ah https://training.galaxyproject.org/training-material/hall-of-fame/khaled196/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-intro/tutorial.html 2023-05-23T10:15:15+00:00

This tutorial assumes you have already completed An overview of the RO-Crate concept and its implementations and have a basic understanding of working with JSON.

Stian Soiland-Reyes https://training.galaxyproject.org/training-material/hall-of-fame/stain/ Peter Sefton https://training.galaxyproject.org/training-material/hall-of-fame/ptsefton/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Martin Čech https://training.galaxyproject.org/training-material/hall-of-fame/martenson/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Armin Dadras https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-submitting-life-monitor/sort-and-change-case-workflow/sort-and-change-case.html 2023-05-11T12:51:10+00:00

Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-in-python/tutorial.html 2023-05-11T12:51:10+00:00

This tutorial will show you how to manipulate RO-Crates in Python using the ro-crate-py package. It is based on the ro-crate-py documentation.

Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Bruno P. Kinoshita https://training.galaxyproject.org/training-material/hall-of-fame/kinow/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Eli Chadwick https://training.galaxyproject.org/training-material/hall-of-fame/elichad/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Yvan Le Bras https://training.galaxyproject.org/training-material/hall-of-fame/yvanlebras/ Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Martin Čech https://training.galaxyproject.org/training-material/hall-of-fame/martenson/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Armin Dadras https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-submitting-life-monitor/tutorial.html 2023-05-11T12:51:10+00:00

Life Monitor (LM) is a service to support the

Luca Pireddu https://training.galaxyproject.org/training-material/hall-of-fame/ilveroluca/ Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Marco Enrico Piras https://training.galaxyproject.org/training-material/hall-of-fame/kikkomep/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Eli Chadwick https://training.galaxyproject.org/training-material/hall-of-fame/elichad/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Yvan Le Bras https://training.galaxyproject.org/training-material/hall-of-fame/yvanlebras/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-in-galaxy/tutorial.html 2023-05-11T12:51:10+00:00

Workflows are a powerful Galaxy feature that allows you to scale up your analysis by performing an end-to-end analysis with a single click of a button. In order to keep provenance of the workflow invocation (an invocation of a workflow means one run or execution of the workflow) it can be exported from Galaxy in the form of a Workflow Run Crate RO-Crate profile.

Paul De Geest https://training.galaxyproject.org/training-material/hall-of-fame/pauldg/ Marie Josse https://training.galaxyproject.org/training-material/hall-of-fame/Marie59/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Yvan Le Bras https://training.galaxyproject.org/training-material/hall-of-fame/yvanlebras/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-workflow-run-ro-crate/tutorial.html 2023-05-11T12:51:10+00:00

The Workflow Run RO-Crate working group is developing a series of RO-Crate profiles for representing the provenance of computational workflow executions. The set includes three profiles, which represent provenance with increasing level of detail:

Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.html 2023-05-11T12:51:10+00:00

A workflow, just like any other piece of software, can be formally correct and runnable but still lack a number of additional features that might help its reusability, interoperability, understandability, etc.

Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Eli Chadwick https://training.galaxyproject.org/training-material/hall-of-fame/elichad/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ Eli Chadwick https://training.galaxyproject.org/training-material/hall-of-fame/elichad/ Saskia Hiltemann https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/ Yvan Le Bras https://training.galaxyproject.org/training-material/hall-of-fame/yvanlebras/ Martin Čech https://training.galaxyproject.org/training-material/hall-of-fame/martenson/ Björn Grüning https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/ Armin Dadras https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/ https://training.galaxyproject.org/training-material/news/2023/05/11/ro-crate.html 2023-05-11T00:00:00+00:00

As part of the BY-COVID project, the RO-Crate team and BY-COVID members have

Simone Leo https://training.galaxyproject.org/training-material/hall-of-fame/simleo/ Paul De Geest https://training.galaxyproject.org/training-material/hall-of-fame/pauldg/ Stian Soiland-Reyes https://training.galaxyproject.org/training-material/hall-of-fame/stain/ Luca Pireddu https://training.galaxyproject.org/training-material/hall-of-fame/ilveroluca/ Marco Enrico Piras https://training.galaxyproject.org/training-material/hall-of-fame/kikkomep/ Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/ https://training.galaxyproject.org/training-material/topics/fair/tutorials/ro-crate-intro/recordings/#tutorial-recording-14-april-2023 2023-04-14T00:00:00+00:00

A 17M long recording is now available.

Stian Soiland-Reyes https://training.galaxyproject.org/training-material/hall-of-fame/stain/ https://training.galaxyproject.org/training-material/news/2021/12/01/FAIR.html 2021-12-01T00:00:00+00:00

The GTN does a lot of work to adhere to the best practices for FAIR training materials as set out in Garcia et al. 2020 and a lot of this work is behind-the-scenes or automatic from the infrastructure we provide, and we wanted to highlight that for educators and organisers who want to use GTN materials. This is one of the ways the GTN works to makes itself a fantastic platform training. Find out how contributing simple markdown tutorials can result in fantastically FAIR training.

Helena Rasche https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/