# Form Datasets¶

ODK forms can use datasets in a variety of ways. These datasets can be either internal or external to the form.

Internal datasets are defined in the choices sheet of an XLSForm and are typically used as choices for selects. You can also define a dataset in the choices sheet to look up values based on user input. Learn how to define internal datasets in the section on selects.

External datasets are useful when:

• data comes from another system. Using data files attached to the form generally requires fewer steps than adding the data to a form definition.
• data changes frequently. One or more data file attached to the form can be updated without modifying the form definition.
• data is reused between forms. It may be easier to attach the same data file to multiple forms instead of copying the data into all the form definitions.
• the same forms are used in different contexts. For example, the exact same form definition could be used in multiple countries with different data files listing regions, local products, etc.

Note

Most mobile devices released in 2019 or later can handle lists of 50,000 or more without slowdowns. If you experience slowdowns, please share the size of the dataset, the device you are using, and any expressions that reference the dataset on the community forum or to support@getodk.org.

## Building selects from CSV files¶

CSV files can be used as datasets for select questions using select_one_from_file or select_multiple_from_file. CSV files used this way must have name and label columns. For each row in the dataset, the text in the name column will be used as the value saved when that option is selected and the text in the label column will be used to display the option. For select multiples, name must not contain spaces.

These files may also have any number of additional columns used in choice filters or other expressions. The example below uses one select from internal choices followed by selects from two different external CSV files.

survey
type name label choice_filter
select_one states state State
select_one_from_file lgas.csv local_gov_area Local Government Area state=${state} select_multiple_from_file wards.csv wards Wards lga=${local_gov_area}
choices
list_name name label population
states abia Abia 4112230
states ebonyi Ebonyi 2176947
lgas.csv
name label state
aba_n Aba North abia
aba_s Aba South abia
afikpo_n Afikpo North ebonyi
wards.csv
name label lga
eziama Eziama aba_n
umuogor Umuogor aba_n
ezeke_amasiri Ezeke amasiri afikpo_n
poperi_amasiri Poperi amasiri afikpo_n

## Building selects from XML files¶

XML files can be used as datasets that populate select questions using select_one_from_file or select_multiple_from_file. This is typically less convenient than using CSV files. However, knowing about the XML representation is helpful for understanding how to reference values in both CSV and XML files.

XML files used for selects must have the following structure and can have any number of item blocks:

<root>
<item>
<name>...</name>
<label>...</label>
...
</item>
...
</root>


The item blocks are analogous to rows in the CSV representation. Each item must have at least name and label nested nodes and can have any number of additional nodes. These nodes correspond to columns in the CSV representation.

## Referencing values in datasets¶

XPath paths can be used to reference values in internal or external datasets. These paths will start with the instance(<instance name>) function to identify which dataset is being accessed. The next part of the path is generally /root/item because of the XML structure used to represent datasets for selects. The only exception is when using custom XML files which may have arbitrary schemas if not used for selects.

For internal datasets, the instance name is the list_name specified on the choices sheet. For example, to reference the population of the selected state given the form above, the instance name to use is states. The expression would be instance("states")/root/item[name = ${state}]/population. To understand this expression better, read the section on XPath paths and especially the subsection about XPath paths for filtering. You could also do things like count the number of states with a population above a certain threshold using an expression like count(instance("states")/root/item[population >${pop_threshold}]).

For external datasets, the instance name is the filename specified in the select_one_from_file or select_multiple_from_file declaration without the file extension. For example, to look up a ward's label given the form above, the instance name to use is wards because the filename referenced is wards.csv. The expression would be instance("wards")/root/item[name = \${ward}]/label.