# SWISH data sources A data source allows you to make external data available from SWISH programs. A data source _declaration_ declares how the data must be loaded. The following data sources are provided: - Attach [CSV](example/data_source_csv.swinb) from the web - [Scrape](example/data_source_scrape.swinb) web pages - Query [SPARQL](example/data_source_sparql.swinb) endpoints ## Using SWISH data sources The actual loading happens _lazily_, while the loaded data is _shared_ between SWISH queries. The overall structure is as below, where `Name` is an atom denoting the data source and `Spec` is a term that tells the system how to obtain the data. Different SWISH programs may use a different name for the data source; the data is shared as long as the secure hash of the `Spec` is equal. ``` :- data_source(Name, Spec). ``` _Materializing_ the data source results in a predicate with _facts_ and a declaration of the _argument names_. The following predicates are available after declaring a data source: - [[data_record/2]] - [[data_row/2]] - [[data_property/2]] ### Our first example: accessing a CSV file Below we attach a CSV file from the Plotly project. Details on the CSV data source are at [CSV demo](example/data_source_csv.swinb).

After declaring the data source the first action is typically to ask for a record of it to validate that the source is attached collectly and to see which columns are present.

In the next step we typically define rules on top of the plain data record that make the relations we need for further processing the data available. For this purpose a _dict_ is translated into a goal using _goal_expansion/2_. So, we can define a traditional Prolog predicate as below and list it to see what happens:

Finally we show the connection to the rendering libraries to vizualise the data.