Over the past few years we've seen a lot of data sets go into tDAR. In that time, we've learned a great deal about what makes a data set ready for archiving, and conversely, what some of the common problem-spots are. Within tDAR, we try to catch many of these errors and provide users with warnings. Below are a few tips to avoid the most common issues we see when archiving a CSV, TAB or Excel data set.
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Best Practices
Add Column Names
Verify that each data table in your data set has column names. Column names are critical to proper archiving. Without column names, it becomes difficult to understand what data or type of data is in each column. Make sure the column name is descriptive and clear.
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Example: Workbook with data-conversion errors (note level data)
DON'T
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Common Issues / Problems
Merged Column Headers
Avoid merged column headers. Make sure that each column has its own unique header column. For example: the material column should be two columns.
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