A data network is a network of interconnected data servers and one central portal server. Each server in a data network knows the same INTERLIS data models.
A data model described with INTERLIS 1 or INTERLIS 2.
A data server contains all necessary datasets to produce a data product. The datasets are stored in the data server as files or in a database.
A portal server is the center of a network of data servers. While the data servers contain datasets to produce data products, the portal server only contains meta data about the data servers. This meta data helps the portal server to find the proper data servers for a given order.
A data product is a well defined transformation of one or more INTERLIS data models to a final output format (i.e. ITF, XTF, DXF, PDF or others). Each data product has a unique name within the data network. The INTERLIS => Output Format transformation has to be implemented on each data server.
A data product may support any number of parameters. Each data server should at least support topic names and a range polygon as parameters.
The price function calculates the price for a given data product. It therefore supports the same parameters as the data product. While the data product maps one data model to a destination format, the price function maps one data model to a calculated price. More then one data product may share the same price function.
An order is a dataset describing the order information for an accepted order. The order is collected by the portal server and has at least the following attributes:
customer information (i.e. name, address, etc.).
name of the ordered data product
complete set of data product parameter values.
With the help of the order dataset an attached data server can calculate the price of an order or process the order by delivering the resulting data set.
Meta data describes a single INTERLIS dataset in a connected data server. In the context of a data network only the following meta data is relevant:
name of the data model.
name of the dataset. The dataset name has to be unique for a given data model.
geographic range covered by the dataset as a closed polygon.