GUILD: GUidance for Information about Linked Datasets
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About this item
| Description: |
Gilbert, R (University College London)
Tuesday 13th September 2016 - 14:00 to 14:30 |
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| Created: | 2016-09-15 16:45 |
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| Collection: | Data Linkage and Anonymisation |
| Publisher: | Isaac Newton Institute |
| Copyright: | Gilbert, R |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Co-authors: Lafferty, Hagger-Johnson, Harron, Smith, Zhang, Dibben, Goldstein
Linkage of large administrative datasets often involves different teams at the various steps of the linkage pathway. Information is rarely shared throughout the pathway about processes that might contribute to linkage error and potentially bias results. However, improved awareness about the type of information that should be shared could lead to greater transparency and more robust methods, including analyses that take into account linkage error. The Administrative Data Research Centre for England convened a series of 3 face-to-face meetings between data linkage experts to develop the GUILD guidance (GUidance for Information about Linked Datasets). GUILD recommends key items of information that should be shared at 4 steps in the data linkage pathway: data provision (how data was generated, extracted, processed and quality controlled), data linkage, analyses of linked data, and report writing. The guidance aims to improve transparency in data linkage processes and reporting of analyses, and to improve the validity of results based on linked data. GUILD guidance is desgined to be used by data providers, linkers, and analysts, but will also be relevant to policy makers, funders and legislators responsible for widening use of linked data for research, services and policy. The GUILD recommendations will be presented and discussed. |
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