CodeBook Room Data Collector Part 2

Part 2 – Room Data Collector,

Now the premise has been explained I would  like to talk about the practical side of the Room Data Collector.  I will break this down into sections that explain setup, data capture design, and use.


Before any data is collected we need to decide what information needs to be collected, how we would like to name and describe the fields that will hold the data structure that data, and their data types, for instance text, number, yes/no. We also need to either define a list of rooms, to which data is to be assigned. Or preferably a list of standard rooms that can be used to form templates, and later assigned to the full project room list.

For this stage of the process CodeBook PRD is used.

Creating the database,

Room data collector runs on our SQL platform so open CodeBook in SQL mode and select the new project wizard:


Codebook will now run though creating a new database for use with Room Data Collector and CodeBook.

Importing the list of Rooms

The list of rooms to populate data against can come from a variety of sources, it could be an XLS import, directly from Revit or even created by hand inside CodeBook.

Setting up data collection

Again with CodeBook PRD we can setup exactly what data you wish to collect, and how the data is to be collected, format, layout and type.

Open CodeBook PRD and the newly created Room data collector database, select the “build” option and then the Lookups option:


The values you wish to have in the Room data collector can be controlled by hiding or un-hiding fields,  setting the arrangement of the fields using the sequence value, and the method in which the data is collected. See the red boxed area above.

In the Activity noise level example we can see that this displays as a drop down in the RDC:


If we change the collection method to list we can capture data simply by selecting the item:


The location of each section can be controlled by changing the category of the lookup, or altering its lookup sequence to group with other similar values.

In the next blog, I will cover keeping track of the changes to the data as well as securing against unauthorised changes.

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