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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| Locus | Quantity | Material (detailed) | Material (General) |
|---|---|---|---|
| 249 | 5 | stoneware | pottery |
| 250 | 71 | earthenware | pottery |
| 260 | 16 | coiled | pottery |
| 297 | 7 | earthenware | pottery |
| 299 | 1 | stoneware | pottery |
| 282 | 1 | stoneware | pottery |
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Multiple Data Tables
Don't include multiple data tables within the same excel worksheet. tDAR treats each workbook as its own data table. Adding multiple within the same workbook prevents the system from properly archiving or documenting the data within the columns.
Example 5: Workbook with two tables (incorrect)
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Data as Images or Graphics
Don't include data as images or graphics in Excel Workbooks. tDAR cannot read the image contents. The row data will not be a "valid" data set. In most cases, data like this should be made into a PDF and uploaded as a document.
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