Organise Data
The best time to think about organising your data for sharing is BEFORE you collect it - but the next best time is now! Resources in this collection introduce practical strategies for good data management and organization that can be incorporated into your everyday workflow.
Tips for Getting Started
Go for the small wins first - it's easiest to organise data to be machine readable BEFORE it's collected; if you're working with archival/historical data start with the simplest components of your dataset, then expand to the more complex ones
Organise data in a format that is most useful to you - the ODCs accept data organised in wide, semi-long, or long format; use the organisation strategy that is most useful for how you will analyse the data (e.g., semi-long or long for datasets with lots of repeated measures data)
Don't reinvent the wheel - this is the time to reuse past work (yours AND others); avoid creating new variable names/titles/definitions every time you create a dataset and data dictionary by using variable names/titles/descriptions already established as:
Common Data Elements
Community Data Elements (CoDEs)
or in related published datasets
Stick to the same formatting and conventions - always keep an eye on the details! Be consistent in your use of capitalisation, underscores, spelling, abbreviations, etc.
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