Before you upload your water quality data to Datashed, it is important to make sure that you properly prepare both your project and your data. While Step 1 must be completed before Step 2, the steps can generally be done in any order and/or simultaneously.
1. You will need to be an approved member of the project. See the Joining a Project tutorial if you don't know how. If a project does not yet exist, you will need to create one. See the Creating a New Project tutorial for more information.
2. You will need to make sure that all of the sample points for which you have data exist in Datashed. To view the existing sample points for a particular project, you will need to find the project. Then, click on the Sample Points link and choose "View Sample Points" from the dropdown menu. A list of sample points should appear. If a sample point does not exist in Datashed you can learn how to Create a Sample Point.
3. You will need to prepare the data so that it is in the right format to be uploaded.
- The data to be uploaded will need to be saved in a spreadsheet.
- While you can normally store your data in any spreadsheet you like, the spreadsheet that you use to upload to Datashed will need to be saved in a CSV (Comma Separated Values) file before uploading. These can also be referred to as Comma Delimited files.
- While you can normally store your data on multiple worksheets, the data that you upload to Datashed will need to be on one worksheet. Meaning if you normally store each sample point on its own separate worksheet, all data that you will be uploading for that project at that time will need to be on one spreadsheet.
- The spreadsheet to be uploaded can only contain data for that specific project. Unfortunately, you can not upload data for multiple projects at one time.
- The spreadsheet should only contain new data to be uploaded. If there is old data that is already on Datashed, the old data should be removed from the spreadsheet prior to upload, so as not to create duplicate data in Datashed. If you keep all of your data on a spreadsheet, it would make sense to make a copy of that spreadsheet and then prepare the copy for upload. Alternatively, some people like to copy data from an existing spreadsheet into a new spreadsheet, although this requires care to be taken so as to not make mistakes.
- The data on the spreadsheet to be uploaded should be organized such that each row of data is for one sample, collected on one day, for a specific sample point. The far left column (Column A) should be the name of the sample point. Column B should be for the Sample Date. Each water quality parameter (such as pH, alkalinity, iron) or piece of metadata (sampler, flow method, etc) should have its own separate column, but can be in any order.
- The Sample Point names in the spreadsheet needs to match the Sample Point names in Datashed. The Datashed upload tool does provide some ability to change this during the process IF it detects they do not match or IF you remember. It is recommended to make sure they match prior to uploading.
- The data labels such as pH, Alkalinity, Iron, Flow, etc do not have to exactly match those in Datashed, as you will match these during the upload process, although the closer they match to Datashed, the easier it will be for Datashed to take a guess and potentially reduce the time to complete the process.
- This is a good opportunity to review the data and look for missing data, typos, or other erroneous data. Make sure that all of the available data and information has been entered into the spreadsheet to be uploaded. This should include field measurements such as flow, field pH, temperature, etc as well as any metadata you wish to include such as sampler person, sample organization, lab, method of flow, etc.
- Flow measurements need to be uploaded as gallons per minute. Datashed does not automatically convert it.
- Most metals including iron, manganese, and aluminum must be uploaded as mg/L. Datashed does not automatically convert it.
- Water temperature must be uploaded as Celsius. Datashed does not automatically convert it.
- Values presented as "ND" should be changed to a value of "0".
- Values that indicate below detection limit such as "< 0.2" can be imported. In Datashed, they will be displayed as below detection limit, but treated as a "0".