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Pure Basics: How to quality assure research data

This class covers how staff responsible for checking and validating research data handle these tasks on a daily basis using workflows.

Target Audience: Pure administrators/super users/editors

Index:
00:00 Intro and agenda
03:27 What is QA in Pure?
04:30 Why is QA important?
06:15 QA aspects to consider / Metadata
11:52 Relevant roles in Pure
14:50 Useful functionality
14:55 - Editor tasks
18:20 - Filters to monitor and prioritise with
23:30 - List view vs. matrix view
27:55 - Default menu points (Research outputs)
30:00 Validating research outputs
31:50 Other aspects to consider
31:53 3 vs. 4 workflow steps
33:20 Validate external content (See also Matrix view)
33:59 Revalidation
35:35 Communication within Pure
39:23 Merge duplicate research outputs
45:23 Claim / Disclaim handling
49:15 Questions
Recorded Sep 25 2017 57 mins
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Presentation preview: Pure Basics: How to quality assure research data

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