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DataStream Upload Template
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Version 1.7
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Last Updated: April 20, 2020
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• This template is a data entry spreadsheet that guides data stewards through organizing water quality data into DataStream's upload format.
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• Check DataStream's upload page to ensure you are using the most up to date version.
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• The upload template can be completed in Google Sheets or Excel. These instructions include steps for both.
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• Additional metadata (information about the dataset) is collected during the upload process.
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Step #1
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Create your own copy of this template
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Google Sheets: File > Make a Copy > Ensure "Copy Comments" is selected > OK
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Excel: File > Save As
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Step #2
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Review the blue tabs #1, #2, #3, and #4
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Colour Code: A colour code reference for validation errors and data categories.
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Allowed Values: Data must be entered as specified in this sheet in order to upload to DataStream.
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Glossary: Descriptions that explain what each of the column headings mean.
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Step #3
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Enter data into "Upload Template" (tab #5)
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Refer to LOOKUP tables (yellow tabs #6, #7, #8) for additional information on the following column headings: CharacteristicName, TimeZone, and HorizontalReferenceDatum.
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Google Sheets: If copying and pasting data from another file, use "Edit > Paste Special > Values Only"
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Excel: If copying and pasting data from another file, use "Edit > Paste Special > Text"
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Step #4
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Review and correct validation errors as required
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Google Sheets: To copy validation guides, use Edit > Paste Special > Data Validation Only followed by Edit > Past Special > Conditional Format Only
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Excel: To copy validation guides, use Edit > Paste Special > Validation followed by Edit > Paste Special > Format
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Step #5
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Export data from "Upload Template" as CSV.
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Google Sheets: File > Download As > Comma Seperated Values (CSV)
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Excel: File > Save As > Comma Seperated Values (CSV)
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Step #6
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Go to DataStream > Upload Data and Select "Create New DataSet"
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Step #7
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Enter appropriate program information and metadata for your dataset.
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Step #8
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Upload the CSV file via the on screen instructions.
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Step #9
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Review your data on DataStream.
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Need help? Contact us.
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