Love Your Code: Building common standards for reproducibility with administrative and survey data
14 February 2020
Sharing code is good research practice and helps actors in the research domain to be reproducible. Data producers benefit from including syntax in data documentation to demonstrate how derived variables were constructed; data users benefit from publishing code that underpins research findings; and data users can helpfully share back value-added work they have done in the course of their analysis so that ne users can benefit.
A number of leading journals now require code and syntax to be uploaded and some rerun this code to ensure that results in an article are indeed replicable. ‘Showing the code’ can help demonstrate trust in published work, but how far should we go to validate code or enforce that it is reproducible? Can we define a baseline best practice recommendations for publishing code in the social and behavioural sciences? How far might Reproducibility Services go towards demonstrating robustness in research findings?
Come and join us for a knowledge exchange day with experts in the field to discuss and debate these issues.
Prerequisites: data depositors, advanced statistics/secure lab data users, data or peer reviewers curators with statistical knowledge and experience
This event supports the 2020 Love Data week