The Knowledge Set Builder is a web based module through which search queries can be joined together to create a denormalised flat table – a Knowledge Set. This video covers some of the main capabilities provided by the Knowledge Set Editor – the Why? of the Knowledge Set Builder.

   

The knowledge set builder can make use of data in the information model, Data Sources saved in the Data Source Editor Tool and other Knowledge Sets. When multiple sources are joined together, mapping columns are used to match the data. Every joined source can be filtered with a queries, and calculated columns can be added as additional columns to the Knowledge Set. Use Knowledge Sets as a foundation for applications, to join, match, and filter data sources together, to deliver sets of knowledge to external tools via the API and much, much more.

The sidebar provides an overview of the available Knowledge Sets. Select an existing item to view details and to make changes. The Sidebar can be toggled by pressing the  pin.

Use the Search Field located at the top of the Sidebar to search with contains for any Data Source or Connection.

Usage

Used X time(s) displays the number of times the Knowledge Set is being used in inorigo. Select an item and press Used X times in the top-right corner to see where it is being used.

Open in new tab	Opens Knowledge Set in new tab
Open in Knowledge Set	Opens Knowledge Set
Copy ID	Copies the ID of the Knowledge Set
Create copy	Opens a Copy of the selected Knowledge Set with the given name Copy of [Unit Name]. Notice that the copy is not saved to the database until you press
Bookmark Knowledge Set	Adds Knowledge Set to the Library

Video tutorial on how to build a Knowledge Set

Knowledge Sets are built by joining multiple Queries together.

The Base Query is the first query in a Knowledge Set, just like any other query it can contain data the model in inorigo, an external data source or a Knowledge Set. Through the base query you may join to a new query.

Video tutorial on the query function

The Query function lets you formulate a search query by writing criteria connected through the logical operators AND and OR. This way of writing Queries is easy to overview and to edit since the entire query is visible and editable on one page.

To specify a query, first select the initial data type that you are looking for and then fill out a criterion. The AND operator is chosen per default.

Say that I want my query to find all Associations that are a kind of Business Improvement Initiative. When I set the data type to Association a criterion with the definition is a kind of is automatically added, since an association always require a definition. If you know that your definition doesn’t have any sub classes it’s more efficient to change the criterion to equals – that way inorigo will not search through the whole classification structure.

Running this query now returns all business improvement initiatives, that is – associations defined as business improvement initiatives.

If an initial base query starts with Definition is a kind of  X the query is named Table #1

If the initial base query however starts with a definition = X, the query is named automatically named X.

Click an operator lets you add attributes, references or relations as criteria to the query.

You may choose to include disabled attributes (1) and abstract attributes (attributes that are prohibited to instantiate) (2), and to reload the units (3). Use the search field to quickly find your units and either select it and press OK, or double click to add the Attribute, reference or relation.

Unavailable connections are automatically disabled, see Definition in the image above.

What Attributes, Relations and References that are available is decided in the following way

Attributes	Simple Search Query All attributes (regardless of existing actual instances of the definition) that are defined on given definition(s) and super classes in the search query. Only the class attributes is displayed if no definition or is a kind of is given. Example: Definition = A, Definition = A AND Definition = B (etc), Is a kind of = A, Is a kind of = A AND Is a kind of = B (etc), Definition = A AND Is a kind of = B (etc) Complex Search Query Only attributes that are defined on given definition(s) and super classes in the search query that actually have instances. Only the class attributes is displayed if no definition or is a kind of is given. Example: Definition = A OR Definition = B (etc), Definition = A OR Is a kind of = B (etc)
References	The result of the search query is matched with all available references. if there are instances with given definitions, and, the attributes that are pointing to a unit and displays any unit in in the query.
Relations	Simple Search Query All relations (regardless of existing instances to the relation) that are defined on given definition(s) and super classes in the search query. Complex Search Query Only relations that are defined on given definition(s) and super classes in the search query that actually have instances. Only the class attributes is displayed if no definition or is a kind of is given.

Once a query has been created it appears in the knowledge set builder as displayed in the image below. Press the rightmost edit button to make changes to the query, and press Attributes to select what attributes that are to be included in the knowledge set.

The attribute ID is per default enabled. This attribute refers to the units unique ID that will enable inorigo to recognize the unit in the database. Thus, the ID needs to be included if a Knowledge Set containing inorigo units is to be used in an application.

If no attributes are included, the knowledge set will be empty.

Joining a query with another query may at first appear similar to applying criteria to a query. But the two are not to be confused.

When creating a query, connections to other units in inorigo are used to filter content.

 

Example:

This query returns all persons that has a permanent employment.

 

 

When joining a query with another query however, the knowledge set returns the content of both queries divided over columns. Filters can be added to every Query in a Knowledge Set by pressing the pen symbol.

In this Knowledge Set a query with Person has been joined with a Data Source, identifiable by the dashed borders.

 

Once a base query has been created, you will be able to join from that Query to all available connections (Definitions, Instances,Attributes, References, Relations, Data Sources and other Knowledge Sets). This procedure may be continued, by joining from any queries in a knowledge set we are able to create Knowledge Sets from chains of the information in the model or external sources.

 

 

Join a new query to an existing one by pressing join under the query you intend to join with.

The available Attributes, References and Relations to join with are automatically loaded and unavailable options are automatically disabled. In this case instances are disabled since Business Improvement Initiatives in the base query are Associations.

When a new query is added it is automatically selected. When joining to another query than the latest one added, you need to click inside the box of the query to reveal its respective join function as the image below displays.

Joining a query through the join in the left image results in a join with the initial base query Business Improvement Initiative. Joining through the join on the right results in a join with the sub-query Initiative Person Resource.

 

The information icon reveals information regarding a join.

A green pen indicates that there is at least at least one criterion in the query.

Video tutorial on how to build a Knowledge Set that incorporates external Data Sources

A data source can be used both as an initial base query, or be joined to via another query in the knowledge set builder.

All Data Sources added to the context is by default available in the knowledge set builder, under external in the Data Type and Join menu. You can read more about how to use the Data Source Editor Tool to set up a Data Source here.

A Knowledge Set can be built with a Data Source as the Initial Base Query, by choosing a Data Source as Data Type, as displayed in the image below.

 

It’s possible to join both from a Data Source – to units in inorigo, and to a Data Source – from inorigo.

 

Joining to a Data Source

To join to a data source to another data source, a knowledge set, or from units in inorigo – find your Data Source from the joins menu. Data Sources that have been created in your context are by default available from the Knowledge Set Builder.

The mapping columns should contain identical rows for the two sources to join correctly. Select from available columns for both queries and click join. Run the Knowledge Set to confirm that the join worked as you intended.

 

Joining from a Data Source

Joining from a Data Source to another Data Source or a Knowledge Set is achieved in the same way as when joining to a Data Source, as described above. However, when joining from a Data Source to units in inorigo, you are required to make a few additional entries.

Begin by choosing a column to join from.

Once selected the popup in image below appears.

To find the attribute of an inorigo unit to join with, you must first select a Data Type. Depending on your choice you have to make additional entries.

For association type units, a definition is always required to locate them. Thus, when joining to associations, first provide the association definition that instantiate them – then choose what attribute to join with. You can learn more about inorigo units here.

Press join to complete the join, and Run the Knowledge Set to confirm that it works as you intended. To join on additional Columns, follow the same procedure as described above, under Joining to a Data Source

 

 

Add criteria to Join sources on multiple columns

It is possible to add additional criteria to a join, just as criteria can be added in a query. This is useful if there is no one column that can be used as unique identifier when two tables are joined together.

Example:

The following table is taken from an Excel document where Employees has been logging the number of hours they worked with various initiatives. The goal is to join the document with the Persons and Initiatives that are kept in inorigo, to see how many hours each person has worked with each initiative.

Person	Initiative	Total Hours
Amy Higgins	Competence Development Program	80
Amy Higgins	OKR Implementation	280
Delbert Schwartz	Six Sigma inpraxis	20
Floyd Parsons	OKR Implementation	380
Floyd Parsons	Six Sigma inpraxis	40

 

After joining on Person, the Knowledge Set will be returned as the image below and we will not be able to determine how many hours that has been spent on what project, and if we were to join on Initiative, we could not determine the person that spent those hours.

We can solve that by adding additional statements to the join between the two sources:

First carry through a regular join by mapping a column from each of the source, as described in the chapter above, Joining with Data Sources

then press Edit on the to open the Query for the joined Data Source as seen below

Use the Query function to add your desired statement.

If you want to enforce two columns you should use the AND operator as seen in the image below. In even more complex scenarios you can simply continue to add statements to this query to set up the join.

Press the arrow rightmost of the entry field to select the column.

Notice that the data needs to be in the in the Knowledge Set and that the column needs to be enabled to be displayed in the drop-down list.

 

Joining a Knowledge Set to another Knowledge Set allows bigger reusability of the sets of data used throughout the inorigo instance. By keeping knowledge sets of frequently used information they can quickly be implemented and kept updated in applications or external tools that communicate with the Knowledge Set via the API.

To join a Knowledge Set to another knowledge Set, select the desired Knowledge Set from the joins menu.

Choose attributes to join the knowledge sets together. Since multiple inorigo units are allowed to have the same name or presentation, using their unique ID for the joining column will guarantee a unique identifiers for each row in the joining column. Thus, joining on ID is always recommended when inorigo units are joined.

Columns holds all available columns for every Query that has been included in a Knowledge Set. Simply tick to enable or disable a column.

For inorigo units, columns hold the attributes defined for the units.

Volatile (calculated) attributes

Since volatile attributes might have a negative impact on performance, a warning is issued for attributes of this kind.

 

Multiple Attribute values

When an attribute has multiple attribute values (occurs whenever a multiplicity is set to more than one.), the values will be divided over separate rows.

The Single Value option will exclude all but the first attribute value from the Knowledge Set.

Calculated Columns for Knowledge Sets works similarly to the Calculated Columns function in Datasets, in Application Builder. By writing an expression in the expression editor a Calculated Column can be added to a Knowledge Set. While the content of a regular column in a knowledge set is determined through a search query, the content of a Calculated Column is determined by the expression used to generate it. A Calculated Column can for example contain calculations of values from the other content in the Knowlede Set.

This section covers how to create a Calculated Column in a Knowledge Set and how to make use of the Expression Editor. To fully understand the capabilities of Calculated Columns in Knowledge Set one must first learn how to format expressions in inorigo. You will find the documentation on functions used to write expressions from the help menu in the Expressions Editor.

To Create a Calculated Column, click the attributes list from any Query in the Knowledge Set and press Add calculated…

	Edit Calculated Column
	Remove Calculated Column

Name the Calculated Column (default: Calc #X), select a data type for the calculated column to appear in and write your expression. Notice that setting the Data Type to anything but Primitive will not enable you to create inorigo units in a calculated column, but rather to treat already existing inorigo units. Primitive type Data can however be generated.

Hotkeys
CTRL + G	$GET(@item,)
CTRL + I	@item
CTRL + SPACE	Reveal menu with available functions and  variables

 

Variables Menu

Use these shortcuts to fetch information regarding the given Knowledge Set.

Cell
columnDataType	Data Type for the given column
columnID	ID for the given column
columnIndex	index for the given column
columnKey	columnKey for the given column (column identifier, moving columns around in the knowledge set will effect the column keys)
columnNo	the number for the given column (moving columns around in the knowledge set will change their numbers)
columnTitle	the column header for a given column
rowIndex	rowindex for a given column
rowNo	row number for a given column

 

Row
$get(@row,ID)	Get the value given on the rows from the selected column
ColumnID	ID of the selected Column in the Knowledge Set
Column Name	Name of the selected Column in the Knowledge Set
Column Full Name	Full Name of the selected Column in the Knowledge Set

 

Data Set
@columnCount	Number of columns in the current Knowledge Set
@dataset	Current Knowledge Set
@rowCount	Number of rows in the current Knowledge Set

 

 

Examples of Use

Join two columns together

A Calculated Column can be used to join the First Name and Last Name columns together.

The following expression gets the rows from the provided Column ID. ” ” is added between the two expressions to add a space between the first and last name.

$get(@row,ID1) + ” ” + $get(@row,ID2)

You can find the ID through the CTRL + Space menu as displayed in the image above.

Resulting Knowledge Set

Examples of Use

2. Mean value.

To find the average value of the rows in a column, we must summarize all values and divide them with the number of rows in that column.

The following expression summarizes all values from the given Column Name/column ID. Set a the Data Type to integer or double to get a numeric value that can be used for further calculations or in Graphs.

$SUM(@dataset,”Column Name/ID”)

When using double you can add the function $ROUND($SUM(@dataset,”Column Name/ID”),X) to set a number of allowed decimals X.

 

The Calculated column returns a summary of the values in the column Worked Hours

 

add /@rowCount to the expression to divide by the amount of rows.

The result – rounded to two decimals.

$ROUND($SUM(@dataset,”Column Name“)/@rowCount,2)

Video tutorial on parameters in queries

Parameters are used to set up query statements that should be configurable. This is useful for statements that continuously change, or that are to be configurable outside of the Knowledge Set Builder, like the API.

A good example is to create a parameter with the variable @NOW, which returns always returns the current date and time, this allows us to set up queries that always use the current date, rather than a fixed one in a query. Another example is to let users change the content of a column by setting another defining unit over the API. We can use then use the knowledge set as a foundation for interactive, custom built solutions for the end users.

 

Parameters are defined per Knowledge Set and can be reused for multiple Queries within a Knowledge Set. Add and edit parameters either through the button in the header of a Knowledge Set, or next to the input field in a query

When creating a parameter we are required to make the following entries

Parameter	The name of the parameter
Data Type	The class of the parameter. Notice that we need a class that maches the statement. If a parameter is used for an attribute with the given class Integer, The parameter must be of the same class.
Default Expression	The expression that is executed when the query is run.

 

The parameters dialog provides an overview of all Parameters in the Knowledge Set. From here they can also be edited, by double-clicking in the desired cell. Parameters that are in use cannot be deleted (X appears as grey).

Expressions

The following variables are applicable in Parameter Expressions

 

For Parameters of the Class String, ” ” should always be used.

For a parameter that searches for all values that equals Amy, the expression used for the parameter should be: “Amy”

 

Use Parameters

Applicable parameters (those who matches the class of the statement) is available for selection from the menu within a query.

 

Examples of use

1. Example – Use a parameter to search for a specific name of a Person

Base Query

Parameter used

Query returns: All units defined as person, who’s First Name = Amy

 

2. Use a Parameter to return the Initiatives that launched less than a month ago

This Knowledge Set contains Business Improvement Initiatives and their start and end dates. By adding a statement for the From Date attribute on Time Period  we are able to say that:

The From Date is larger than…

and then add a parameter that returns the date one month ago from today.

The Knowledge Set will now always return Initiatives where the From Date is larger than A month ago, no matter when it is being run.

 

3. Use a Parameter to allow allow users to change the Defining unit over the API.

Create a Knowledge Set where the Definition is set with a Parameter

This Definition can now be replaced when the Knowledge Set is called over the API

Knowledge Sets can easily be exported over inorigo’s API, to Application Builder or to a CSV format.

 

API

The web services documentation houses instructions for how to work with Knowledge Sets over the API, its available under help in your inorigo instance.

 

CSV Export

Export a Knowledge Set to a CSV by pressing

You may also export individual queries within a Knowledge set:

Open up a Query

Run it and press export

 

The CSV file contains a Byte Order Mark, which informs Excel that it should be read as a UTF-8

You can easily convert a CSV file to the Excel formats xls or xlsx through the following steps:

• Open Excel and press Open file, then open the downloaded CSV file.
• Follow the import guide and make sure to start the import from row 1 and to include headers.

 

Expression functions

Utilize $KNOWLEDGE_SET to output a knowledge set as a dataset.

Example

$KNOWLEDGE_SET(440AE809-6928-7E99-7353-ABE2007CD72D)

Where 440AE809-6928-7E99-7353-ABE2007CD72D = an ID of a knowledge set.

Method Primitive

See the methods documentation

Once a Knowledge Set has been saved it will be available as a inorigo unit under the Generic Model Domain.

To import a Knowledge Set to an Application via Application Builder,

When a Knowledge Set is selected inorigo will ask if you want to add all columns.

Press Cancel to only add one advanced filter component containing all columns given in the Knowledge Set.

Press OK to add every column to a separate filter component, in addition to the advanced filter component.

 

Making changes to the queries that defines the content of a knowledge set will have immediate effects on the filter components in any application that make use of the given Knowledge Set. Notice however that adding or removing columns to the knowledge set will not automatically effect the content of an application. If additional queries are added to a Knowledge Set, it needs to be re-added to the application for the new columns/filter components to appear.

If a Knowledge Set has not yet been saved, name it and press Create. If changes are made to an existing knowledge set, Save is available.

	Create a Knowledge Set
	Apply changes (overwrites previous save)
	Delete Knowledge Set
	Unable  to delete Knowledge Set. Either because it has not yet been created, or because the knowledge set is  in use. See Usages

 

Choose what attributes that are to be included as columns in the Knowledge Set by ticking the boxes. The name of each attribute, displayed in the column header of the Knowledge Set, can be changed by pressing the pen. Notice that this list does not display disabled attributes for inorigo units.

Notice that ID needs to be included for inorigo units that are to be loaded from a knowledge set. If only Names for example are included and a knowledge set is opened in the Application Builder or somewhere else in the inorigo suite, the names will appear as strings, rather than inorigo units.

 

It’s possible to sort a Knowledge Set via the result grid on any of the columns by clicking anywhere inside the header. If the Knowledge Set is saved after sorting, the sorting will be persisted and also apply to API calls where no specific sorting is specified. More information is available on the documentation on API – Swagger UI.

 

The order of the columns in a knowledge set may also be customized by dragging and dropping the column header. Top headers can be reordered freely, and sub-headers can be reordered underneath the top header as the images displays.

It’s possible to copy cell values from the result matrix in Knowledge Sets and Queries by right-clicking and choosing Copy Cell Value

 

The order in which queries are added to a Knowledge Set effects which of the queries that know about the other Queries. This order can have an effect on statements added to queries that refer to columns in other queries, since it will not be possible for a query to refer to another query that it does not know about.

The image below demonstrates which queries a query will be able to refer to. The letters represent the order in which the queries were added (From A to G).

A	Can’t refer to any other Query
B	Can only refer to: A
E	Can’t refer to any other Query
C	Can refer to: A, B,
D	Can refer to: A, B ,C
F	Can refer to: A, B, C, D
G	Can refer to: A, B, C, D, F

This means that when adding a statement From the Query A,

it will not be possible to refer to a column from another query.