This is a high level introduction to conceptual areas of OrgVue expressions. The examples provided will get you started, but for detailed coverage, see the Gizmo Cookbook
Introduction to Gizmo
 Data in OrgVue is stored as nodes which have properties. Expressions allow you to manipulate these node:property values.
 Gizmo is a scripting language that is used to write these expressions
 It has its roots in JavaScript, but has been added to and modified by the OrgVue development team
 Expressions are the OrgVue equivalent of Excel formulas
 OrgVue’s scripting language Gizmo allows you to perform querying, calculations, aggregations and transformations.
They can be written in several places:
 In the expressions manager
 Within a cell (to return a value for that cell)
 Within the default value box of a property (preferred)
OrgVue generates meta data properties that can be accessed
 OrgVue generates meta data properties automatically. These properties describe the node itself, and are present as options in a dataset regardless of what other data it contains.
 Metadata properties are listed in italics at the bottom of the sidebar property list and the filter control.
 Typing node.<metadata property name> will return a value as it would for other properties
Node relationships are stored as a special type of meta data
Node relationship syntax allows you to reference nodes through their hierarchical relationships to one another
Expression 
Result 

node 
node 
Reece Harris 

node.parent 
node.p 
Returns his manager 

node.siblings 
node.s 
Returns all nodes under the same parent node (team members) 

node.children 
node.c 
Returns all his direct reports 

node.descendants 
node.d 
Returns all his reports 

node.d(start,end level) 

node.d(2) 
Returns all descendants starting two levels below the selected node 

node.d(1,2) 
Selects all descendants between 1 and 2 levels below the node 

node.d(0,2) 
Includes the node itself 

node.d(1,2) 
Selects all ancestors between 1 and 2 levels above the node (parent, grandparent) 
Draft expressions in the expressions manager
 The expressions manager is useful because it can evaluate expressions on the fly.
 It is a great way of testing whether your expression is valid, or finding out some data
 without having to alter the value of any cell in the dataset.
Gizmo expressions are written differently to other functions
 When writing in Excel, or speaking English for that matter, we use a VerbObject approach, ie. the first thing you do specify the operation you are performing, and then define the variables / parameters on which it acts.
 OrgVue is very different. It uses a series of objects one after another to gradually specify functions*
 An expression does two things:
 it specifies an input (typically a subset of your dataset), and
 it outputs a value based on the operations performed on that subset.
Expressions are constructed using building blocks called objects
 In OrgVue, expressions are built up gradually by adding together objects separated by dots ('.').
 You start with the highest level object you can, 'node' or 'nodes()' and then you access properties or values from this object to define a subset of the data on which to perform an operation.
Every time you add something after a dot ('.') it is acting on the input data specified before the dot.
e.g. (For the object 'node', give me its children, from the object 'this node's children', give me the current salaries, from the object 'this node’s children’s salaries’, give me the sum)
There are 4 types of property you can access for a node:
1.Dataset properties (e.g. ‘Full name’, ‘Grade’)
node.fullname // node.grade
2.Metadata (OrgVue generated) properties (e.g. depth, orphan)
node.depth // node.isorphan
3.Relations e.g. child, parent, sibling
node.parent // node.sibling
4.Methods / functions e.g. ‘if’, ‘join’, ‘map’
node.if() // node.map()
Any property in the dataset can be theoretically accessed
Building expressions from objects
• Typing into the expression manager or a cell primes OrgVue to interpret what follows as an expression
• The most common objects to follow are data properties
• Dataset properties come in 4 main types (these can be set within the Edit Property dialogue):
– Number
– String (text)
– Date
– Boolean (true or false)
You can also use mathematical operators on objects
Because each expression defines an object that can be acted on, you can also write add, subtract, multiply and divide values easily:
Use standard operator symbols to add ‘+’ , subract ‘’ , multiply ‘*’ , divide ‘/’
There is also syntax to express more complex operations:
Mathematical functions are some of the simpler expressions
 As well as chaining together properties to return a value  you might want to perform some function.
 Once you have the appropriate subset of your data, adding a method to your expression will do something to it.
 Mathematical operations are clear examples of these:
More examples:
nodes().count // the total number of nodes in the dataset // .cnt is another option that only counts numbers nodes().age.avg // the average age of people in the dataset node.salary / node.s.salary.avg * 100 // an employee’s salary as a percentage // of the average salary of their peers
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