From 85eab0e18493d6b27c8bda95a0081268d316268f Mon Sep 17 00:00:00 2001 From: Laura Portell Silva <74184187+lauportell@users.noreply.github.com> Date: Mon, 16 Sep 2024 12:41:54 +0200 Subject: [PATCH] Update text based on Nazeefa's comments --- pages/your_tasks/data_discoverability.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pages/your_tasks/data_discoverability.md b/pages/your_tasks/data_discoverability.md index 88c95d10c..9b43ad2e6 100644 --- a/pages/your_tasks/data_discoverability.md +++ b/pages/your_tasks/data_discoverability.md @@ -37,7 +37,7 @@ Data discovery involves processes and tools that help users understand what data ### Description -Discovering research data for re-analysis can occur at different levels of granularity. Initially, researchers browse online catalogues that describe studies, datasets, related publications, variables, and some data distributions. This basic discovery may suffice if the datasets meet all the criteria. However, to find dataset that meet specific combinations of attributes, such as “adults diagnosed with COVID-19 in the last year, fully vaccinated, with no underlying health conditions,” researchers must either contact the authors or request data access and verify themselves. This process is feasible for a small number of datasets and cooperative data controllers but it is usually time-consuming and uncertain. To streamline this, data discovery at the source allows users to query data non-disclosively, determining its relevance before requesting full access. +Discovering research data for re-analysis can occur at different levels of granularity. Initially, researchers browse online catalogues that describe studies, datasets, related publications, variables, and some data distributions. This basic discovery may suffice if the datasets meet all the criteria. However, to find dataset that meet specific combinations of attributes — such as identifying datasets with particular combinations of attributes, like 'adults diagnosed with COVID-19 in the last year, fully vaccinated, with no underlying health conditions' (as an example) — researchers must either contact the authors or request data access and verify themselves. This process is feasible for a small number of datasets and cooperative data controllers but it is usually time-consuming and uncertain. To streamline this, data discovery at the source allows users to query data non-disclosively, determining its relevance before requesting full access. ### Considerations