The flexibility of this import type is mainly founded in the possibility to map columns in the source files to specific properties or other characteristics of the feature or observation to be imported. The column mapping is part of the import type's specific settings. The column mapping consists of some general settings (see table 3) and a series of column associations (table 4).
Setting |
Description |
Feature type |
Defines the feature type of the data to be imported. |
Feature sub type |
Defines the sub feature type of the data to be imported. |
Container feature type |
This import format supports the creation of container features and the mapping of features to these container features. This setting defines the feature type of container features to be created. |
Source for sensor |
Defines if the sensor should be read from the file or if it should be a fixed sensor. If a fixed is used, you must have a focus domain and then choose a sensor. |
Type of sensor |
Defines weather a created or mapped sensor should be of the type generic or person. |
Create sensors |
This has to be enabled for sensors to be created from the imported file. Otherwise only pre-existing sensors will be mapped. |
Feature name resolving |
With this import type you have different possibilities how the import shall detect the name of the feature for which data is imported. •Fixed feature: Import data for a fixed (see below) feature. •Read from file name: Read feature name from (a part of) the file name. You can use a regular expression to filter out the part of the file name that defines the feature name. •Read from column: Read feature name from a specific column of the source file. If set to this option you will have to define a column mapping for the feature name. |
Feature |
This setting is only available if the Feature name resolving is set to Fixed feature. Defines the feature for which data shall be imported. |
Container Feature |
This setting is only available if the Feature name resolving is set to Fixed feature. Defines the container feature for which data shall be imported. |
Regular expression for feature name |
This setting is only available if the Feature name resolving is set to Read from file name. Here you specify a regular expression that is used to define the part of the file name that specifies the feature name. The actual feature name will be the match for the first sub-expression of that regular repression. Example: Original file name: AB_123-4.csv Regular expression: AB_([0-9]{3}-[0-9])\.csv Resulting feature name: 123-4 |
Regular expression for container feature name |
This setting is only available if the Feature name resolving is set to Read from file name. See above for a description how to use regular expressions for defining the feature name. |
Spatial system of feature |
Defines the type of spatial system to use for newly created features. |
Spatial System of container feature |
Defines the type of spatial system to use for newly created container features. |
Axis reference system |
Only available if Spatial system of feature is set to Axis reference. Defines the axis reference that shall be used with newly created features. |
Match feature with GUID |
By using this setting features will not be match by name. They will instead be used by the GUID. This enables you to export features, change their name and import with GUID matching. Should you have imported a GUID from another database, you can use that GUID to match. |
Table 1: General settings for the column mapping
Setting |
Description |
Column index in file |
This is the 1-based (meaning first column as index 1) index of the column(s) that is/are mapped to a single property or characteristic of a feature ore observation. User can define a single column index or a range or collection of column indices that will be read from the source file and written to a property that is mapped. Multiple columns can simply be defined by specifying a comma separated list of column indices, or column ranges. Examples: •1-3, 5 will map column 1, 2, 3 and 5 •7-9 or will map column 7, 8, 9 •1, 2, 3, 4, 7-9 will map column 1, 2, 3, 4, 7, 8, 9 Multiple column indices will only be respected if you choose Join Columns with delimiter as pre-processing type (see below). If not only the first index will be mapped. |
Pre-processing type. |
You can select a pre-processing step that is performed before the source string is treated as value. Following pre-processing types are available: •None: No pre-processing will be performed •Join Column with delimiters: Multiple columns in the source file are concatenated using the specified delimiter. Example: •Input file has following data: •Expected output is •Then user can configure the import like so: |
Post-processing type |
Post processing takes the result of the pre-processing as input and processes the text accordingly. If there is no pre-processing then it simply takes the content of a single column. Post processing takes place after pre-processing, the output of the post processing is then mapped to the property of the feature. •None: No post processing is performed. •Split and take word: Split the value with given split character and take the word at given (1 based) index . •Skip from beginning and end: Defines how many characters to be ignored from the beginning and from the end of the input text. This processor has two settings: Characters to skip at the beginning and characters to skip at the end. Example: the post processor gets an text: "abc4957xyz" as input. User wants to extract the numeric part of the text i.e. 4957 and map to a column. The post processing settings will be: Characters to skip at the beginning: 3, Characters to skip at the end: 3. Output is: 4957 |
Property unit |
If a mapping is done for a property of property type quantity. you have to choose the unit of the values in the source file. All imported values will be interpreted as values in this unit. |
Table 2: Settings for each mapped column