A Data Model represents the way data is structured in a dataset or a database, such as Lab Booster’s data ocean.

The data model defines how the data lake or data ocean is connected to:

- The data input i.e. ELN, LIMS systems, connected instruments etc.

- The data output i.e. the WebApp DataLab in which users can access data

Context

As of mid-2023, each market in Lab Booster has its own data model i.e. its own way to structure data.

At each new project, connections to the data lake must be built again

Objective

Our aim is to have a common data model for all markets, to bring:

• Accelerated delivery of new projects
• Better performance
• Less maintenance

This page is divided two sections

1. Entity-Relationship Diagram (ERD), which served as a basis to design the data model
2. Data model

Entity-Relationship Diagram (ERD)

Data Models are generally based on a diagram or schema called Entity-Relationship Diagram defining

• Entities i.e. a definable object or concept within a system
• Relationships i.e. how entities are related to one another

Building the ERD is a preliminary step to designing the actual data model to ensure that all required entities and relationships are accurately defined and represented.

This section is split in two parts

1. Entity-Relationship Diagram design
2. ERD mapping with R&I workflows

Entity-Relationship Diagram design 

Entity dictionary 

Entity-Relationship Diagram 

ERD mapping with R&I workflows (WIP)

Three types of R&I workflows were identified

• Formulation workflows
• Synthesis workflows
• Analysis workflows

This was done in order to ensure that the ERD defined accomodates all types of R&I workflows.

The mapping done for different workflows is summarized in the table below.