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Preparing Data and Using Templates

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Preparing Data for Upload

Check the following requirements before uploading data:

  • Data values must be accurately matched to their column headings.

  • Column headings must be recognized by FDW. When uploading ad hoc data, column names may need to be adjusted.

  • Metadata values must be recognized by FDW. New metadata must be added through the data series or metadata importing screen.

Using Templates

Templates for most domains require a straight table with one data point per row. Certain domains, such as Prices, will load cross-tabs (i.e., with markets down the side and products across the top). Submit a Help Desk ticket for support in preparing and uploading a template.

IPC Classification Data

  • The IPC Classification Data template allows multiple data collections to be created from one upload:

    • Food Security Area Classification, Humanitarian Food Assistance (HFA) and Internally Displaced People (IDP) data should be entered on separate tabs in the same Excel document.

    • Separate data collections will be automatically created for Food Security Area Classification and HFA data.

  • The source document must align with the date range included in the template or data will not be uploaded. Data collections should be uploaded one month at a time. The collection date should always be the first day of the month. 

  • The first month in the data collection period includes the CS (current situation), ML (near term projection three months), ML2 (medium term projection six months). The outlook collection date is the first date from the current state through four months. A new collection date begins after four months.

Food Assistance Outlook Brief (FAOB) Data

  • The FAOB template allows multiple data collections to be created from one upload (public and internal population estimates, and public and internal highest household).

  • Preparing internal and public FAOB data in the template will fall under one of the following three scenarios:

    • Public and internal data values are the same:

      • Provide values in the columns for public data and leave the columns for internal data blank. FDW will ascribe the values to both the public and internal source documents. 

    • Public and internal data values differ:

      • Provide values in the columns for public and internal data. FDW will separate out the data into the public and internal source documents. 

    • Internal data only:

      • Provide values in the columns for internal data, and either:

        • Specify NA values in the columns for public data to include the country as not analyzed in extracts of that month’s public data, or

        • Leave the columns for public data blank if you plan to add public data at a later time. If the values are blank, the country will not be reflected in extracts of that month’s public data.

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