Currently, many of our results files are denormalized and formatted in a way that assumes someone will be using these files programmatically and is able to easily merge the files with others. However, this is not very user friendly and makes the data harder to use than eGRID data for quick spreadsheet referencing. One key example is that our plant output data doesn't contain plant names or plant IDs. This may be impractical to use for hourly data, but for monthly and annual data files, it may be useful to denormalize these a bit. Another example is that we do not currently calculate generated emission rates in our power sector data, assuming that people can calculate this by dividing other columns. However, this makes the data harder to use.
Currently, many of our results files are denormalized and formatted in a way that assumes someone will be using these files programmatically and is able to easily merge the files with others. However, this is not very user friendly and makes the data harder to use than eGRID data for quick spreadsheet referencing. One key example is that our plant output data doesn't contain plant names or plant IDs. This may be impractical to use for hourly data, but for monthly and annual data files, it may be useful to denormalize these a bit. Another example is that we do not currently calculate generated emission rates in our power sector data, assuming that people can calculate this by dividing other columns. However, this makes the data harder to use.