Data and metadata curation

The University of Birmingham (UoB) is implementing data management processes covering the entire data lifecycle, but mainly by moving the data curation process to the data generators. UoB understands that capturing the data and metadata as they are produced, if possible, will save substantial time and resources, while resulting in higher quality datasets. Thus, UoB is offering services on experimental workflow planning, preparation of pre-annotated data curation templates and pre-existing data curation services. UoB is also offering to complement these services with the use of electronic laboratory notebooks (ELN) that can be accessed either online or installed locally.

Experimental Workflows Design & Implementation, Data Storage & Online Accessibility
Data curation tool, Semantic annotation tool
Applicability domain:
Ontologies, Hazard assessment, Exposure assessment, Risk assessment, Risk characterisation, Bioinformatics
Read-across, Information extraction, Identifier mapping, Toxicology, Ecotoxicology
Targeted industry:
Food and feed, Cosmetics, Drugs, Nanotechnology, Chemicals, Other consumer products, Automotives, Textiles, Constructions
Targeted users:
Data managers, Researchers, Students, Risk assessors, Data modellers
Access type:

Provided by:
University of Birmingham
Login required:
Technology readiness level:
TRL 4 – technology validated in lab

Transnational access

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Resources & Training materials

Webinar recording
Introduction to data /metadata management in nanosafety assessment workflows
A. Papadiamantis, E. Valsami Jones, I. Lynch - University of Birmingham, UK M. Himly, University of Salzburg, AT
18 Oct 2019

Data management is the implementation and application of processes, which allow the acquisition, storage, manipulation, and analysis of data during its lifecycle.

The scope here is:
- to implement data management in scientific research
- to promote data harmonisation through data curation
- to promote data comparability and continuity
- to advance informatics
- to enable translational research
- to facillitate data FAIRness

The principle of FAIR data is explained and the entire data lifecycle is elaborated in the webinar enabling a high quality standard through incorporation of comprehensive metadata.

A case study in collaboration with Duke University is presented visualizing the need and importance of metadata. Instances for materials used, which undergo continuous transformation by time and due to operator management, are defined in form of an instance map.

An experimental workflow involving use of Scinote Online Lab Notebooks is described.

Target audience: Data providers, Data owners, Data managers, Students, Researchers
Open access: yes
Licence: Attribution 4.0 International (CC BY 4.0)
Organisations involved: UoB, PLUS, DU
Webinar recording
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