Welcome to this demonstration on otools – Classification

 

Contents

 

Introduction

Classification is a process related to categorization. A BIM process in which objects are categorized in order to be recognized, differentiated and understood. In other words; Structuring model element data in an agreed way so that different actors can easily find what they need and understand it.

Our amazing tool can handle and manage BIM informations like never seen before. The toolset is configured using tasks containing one or several jobs. Using these features, you can make awesome rule based setups – making your BIM setup agile, scalable and flexible. We call it rule-based classification!

Create a task for each discipline and/or sub-discipline and make your classification setup available for any end-user. Your imagination is finally made possible; You will get the same data structure on all your projects and the ability to analyze them over time.

Remember a classification system is like a common language. In BIM relation, classification lets people, software and machines share and use building information efficiently and accurately.

This is the one and only tool that can help you to classifying objects – based on rules and algorithms.

It can be used for Cobie, Omniclass, Uniclass, CCS, TALO 2000, CoClass, SfB, BIM7AA ect…

How to use

  1. Start by creating a task

  1. Configure your rules

A.  Type a name for the tasks

B.  Select a category or categories

C.  Select target parameters where you want the output data to be placed

D.  Configure parameter output values for each classification in the field of Classification Data

E.  Configure your rules in the field of Data

Description on the image above:

  1. The application will first filter and identify every Structural Columns –> look at every instances of a family name (this is done by using *) –> Identify every instance of Family Type 
  2. All elements that matches these rules will be classified as Columns

  1. When the application finds a match of Columns specified in Classification Data, it will fill in the other output values, defined in Desc 1, Desc 2, Desc 3 ect.

The results after executing the task

Additional features

The tool is equiped with smart filtering options:

  • (*)  means, any instance
  • (*text ) means, every instance that ends with
  • (text*) means, every instance that starts with

Example

*sample_text –> every instance that ends with sample_text is a match and will be processed

sample_text* –> every instance that starts with sample_text is a match and will be processed

* Match any number of unspecified characters;

Can be used to match any number of unspecified characters. For example, “b*k” will match “bench kiosk”, “brick”, and “block”, other example *b*k* will match “bench kiosk”, “bricks” and “blocks” and also “Coarse bricks” and “block 2”.

For all number and integer parameter you have this option. To activate it you need to click twice on the cell.

Click Columns chooser for choosing additional parameter for making rules:

Export and Import from Excel

You can Save the Classification Data and Data to excel, modify them and import them back

 

Import Classification Data

  1. Click on Open excel
  2. Type the Column name from excel you want to export from

  1. Click OK
  2. Choose the excel you want to import (Note that the file has to be closed during import)

 

Import Data

  1. Click on Open excel

  1. Choose the excel file (notice that the cell must not to be empty, choose * or some other text you want to include your rules)

 

  1. Click Open

 

Reuse your settings in another project

You can save and reuse the settings in another projects. Simply save and open it in another projects.

With this option you can develop a setting for your company and get the best structure for your data.

 

Example 1:

The result is shown below:

 

Example 2:

In this example I have chosen additional parameter width(number) from Column Chooser

 

 

I click twice on the fields for activating the dialog box

Now I can classify the components based on the parameter in the width

See the results below after running the tasks