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17 materials found

Keywords: R-programming  or metadata 


RDMbites | Bioimage metadata – REMBI

In this RDMbite we will be speaking about REMBI and its relevance to annotating bioimage metadata

Keywords: REMBI, metadata

Resource type: Video

RDMbites | Bioimage metadata – REMBI: study

In this RDMbite we will be talking about the first aspect of the REMBI metadata guidelines for bioimaging data.

Keywords: REMBI, metadata

Resource type: Video

RDMbites | Bioimage metadata – REMBI: study component

In this RDMbite you will learn about another aspect of REMBI metadata: the Study Component. More specifically, you will learn about the types of metadata that should be collected to describe each study component for bioimage data and how to store it.

Keywords: metadata, REMBI

Resource type: Video

RDMbites | Bioimage metadata – REMBI: biosample

You will learn about the metadata that should be used to describe each biosample for bioimage data and how to store it.

Keywords: REMBI, biosample, metadata

Resource type: Video

RDMbite | Bioimage metadata – REMBI: specimen

In this RDMbite, you will learn about REMBI Specimen, the metadata you should be collecting to describe it and how to store it.

Keywords: REMBI, Image Data, metadata

Resource type: Video

RDMbites | Bioimage metadata - REMBI: image acquisition

In this RDMbite you will learn about the Image Acquisition module of REMBI metadata. You will learn about the metadata that should be collected to describe the method of image acquisition and how to store it.

Keywords: Image, REMBI, metadata

Resource type: Video

RDMbites | Bioimage metadata – REMBI: image correlation

This RDMbite tells you about the the Image Correlation module of REMBI metadata

Keywords: REMBI, metadata

Resource type: Video

RDMbites | Bioimage metadata – REMBI: analysed data

Here you will learn about the analysed data module of REMBI metadata. You will see what metadata should be collected to describe the analysed data and how to store it

Keywords: REMBI, metadata, bioimage

Resource type: Video

From Swab to Server: Testing, Sequencing, and Sharing During a Pandemic

Discover how sample strategies can affect scientific research and results:
Sampling is a critical part of research in any field. In studying a disease such as Covid-19, it’s imperative that your sample and sampling methods are best-suited to reflect accurate results.

Supported by expert...

Keywords: metadata, Sequencing, genomics, Genomic data, data quality, scientific quality assurance, data sharing, ethics, data ethics, public health, coronavirus, sars-cov-2, covid-19, data linkage

Resource type: FREE online course

FAIR data - Module 3 (Metadata)

Les Métadonnées : les standards du domaine des données omiques en biologie et séances pratiques d’annotations de jeux de données

Scientific topics: Bioinformatics, Biology, Data management

Operations: Data handling

Keywords: metadata, data annotation, life science standards, data sharing

Resource type: Slides

FAIR data - Module 1 (research data)

Research data and their centrality in the research process.
This material is mostly in French.

Keywords: metadata, Data Life Cycle, Reproducibility, Data management plan

Resource type: Slides

Data Management Planning workshop for new Life Science Projects

Slides from Data Management Planning online workshop for Life Science Projects for researchers

Scientific topics: Data management

Operations: Deposition, Data handling, Data retrieval

Keywords: data management plan, NeLS, TSD, metadata, sensitive, data publication, data protection, storage, identifiers, DMP, licensing, Compliance, data life cycle - collect, data life cycle - reuse, data life cycle - analyse, data life cycle - process, data life cycle - preserve, data life cycle - share, data life cycle - plan

Resource type: Slides

FAIRify your data: data documentation and metadata

“Documentation is a love letter that you write to your future self.”
Damian Conway (2005)

Make your data as useful as possible for “your future self” and others
Never forget what you did or how or why you did it
Always find beck your precious data (easily)
Make data understandable,...

Scientific topics: Data management

Keywords: data documentation, metadata

Resource type: Presentation

Giving data context, structure and meaning

Metadata, standards and ontologies are common ways of providing data with context, structure and meaning. In this webinar Sira explores the idea of once data are ontologised (mapped to standard structured vocabulary), they become linkable to build a bigger infrastructure of knowledge network and...

Keywords: metadata, Ontologies

What happens to your data?

This webinar focuses on what happens to your data after you submit it to a public repository and addresses the question of data ownership.

Keeva and Nancy introduce the concepts of FAIR data, metadata and standards. They then show you where you can find an appropriate place to share your data...

Scientific topics: Data management

Keywords: metadata, ArrayExpress

Resource type: Video

FAIRification & Data modelling

Wikidata
fairification

Keywords: FAIR, linked data, ontologies, metadata

Resource type: Slides

Essential Steps of the FAIRification Process

Since 2014, a number of FAIR Stakeholders have developed tools and methods around the FAIRifcation of typical datasets. In the last 5 years, these efforts were field tested in a series of "Bring Your Own Data" Workshops" (https://www.dtls.nl/fair-data/byod/).

This document records the...

Keywords: FAIR, data stewardship, metadata, linked data

Resource type: Training materials