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Table 3 Key recommendations for multifunctional, machine readable systematic review and map databases

From: Novel tools and methods for designing and wrangling multifunctional, machine-readable evidence synthesis databases

Objective Description
1. Select the right database format Carefully plan what format databases are the most appropriate for data extraction, visualisation, and analysis
2. Ensure design allows translation Select a database format and population method that allow translation between wide, long and condensed formats. Avoid condensing information where a loss of information or data linkage occurs
3. Choose an appropriate naming convention Particularly for wide formats, use machine readable column names for related variables to facilitate aggregation. Populate cells with actual data labels rather than using binary labels (‘0’ and ‘1’) to facilitate aggregation
4. Publish the highest resolution database Provide the database with the highest level of resolution and information as a digital, machine readable additional file, from which condensed or other formats can be translated
5. Document your data Include a detailed data dictionary or meta-data file/worksheet is included in the database file that fully describes each variable/column and coding, that is self-sufficient without the need to read the manuscript methods to understand