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Data · dataset · 2023

The Basics of Data Integrity

Listed in Borealis

We often talk about making data FAIR (findable, accessible, interoperable, and reusable), but what about data accuracy, reliability, and consistency?

Description

Research data are constantly being moved through stages of collection, storage, transfer, archiving, and destruction. This movement comes at a cost, as files stored or transferred incorrectly may be unusable or incomplete.

This session will cover the basics of data integrity, from collection to validation.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
Social Sciences
From keywords
Social Science
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
Borealisdoi:10.5683/SP3/BIU6DK13 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].dataverse_subject:social-sciencessource · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
created_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
descriptionsource · borealisdata caconnector:borealisdata_ca@1.0.0/description
publication_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
titlesource · borealisdata caconnector:borealisdata_ca@1.0.0/name
updated_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
version_labelsource · borealisdata caconnector:borealisdata_ca@1.0.0