A data point’s journey
- Sensor reading.
- Recording of data points.
- Transfer of data to required systems for rig visualization.
- Movement from remote site to town.
- Visualized in town and recorded in a database.
This is of course oversimplifying the process, however what we are trying to point out here is that data is often collected and used for the immediate need. A data point is often not future-proofed or made available in a manner that ensures easy consumption by the myriad of applications and parties involved in the data points lifecycle. So, how do we overcome this to support 4IR applications, all while avoiding an over complicated process and manual intervention?
Two Options are:
- Defining a single standard that everyone must adhere to. This is good in principle but not in practice. Several systems are hardcoded to data specifics and having a single standard can often cause the need for multiple uncontrolled versions of the data, manual overheads and delays in data preparation prior to use.
- Break data into silos. These silos would host differing standards and most likely hosted by different parties. The data can often be duplicated and uncontrolled with access provided outside of intended parties. It can often be extremely difficult to then bring the different data readings together for analysis.