Every company today is data-driven or at least claims to be. Business decisions are no longer made based on hunches or anecdotal trends as they were in the past. In this environment, data quality is a necessary conversation.

A research paper specifically focused on the railway point (also called a switch or turnout) – the asset utilised for switching and locking rails, “slipping a track into two or more different tracks”.

A case study that walks through the practical issues faced when trying to reduce maintenance costs with a manufacturing digital twin

An article heralding the launch of a scaled oil & gas digital twin involving up to 300 workers processing up to 250,000 B/D of oil

Data quality management systems are thoroughly researched but the advent of Big Data might pose some serious questions pertaining to the applicability of existing data quality concepts. This paper aims to investigate various components and activities forming part of data quality management such as dimensions, metrics, data quality rules, data profiling and data cleansing.

The Digital Twin Capabilities Periodic Table (CPT) is an architecture and technology agnostic requirements definition framework. It is aimed at organizations who want to design, develop, deploy and operate digital twins based on use case capability requirements versus the features of technology solutions.

A short, light opinion piece on the advantages of moving BIM to the cloud.

The key is in the title – 8 individual perspectives on the value of interoperability.

This paper seeks to outline a business case for interoperability as an enabler of business transformation - providing transparency, agility, productivity, experience and scalability.