Exploring Data Value in Production Lines
Large organizations, such as Motor Oil Hellas (MOH), have been collecting data for years from various sources, including sensors monitoring different parts of a large production line. This extensive collection of data has primarily been used for its intended purpose: managing the infrastructure machinery and overall refinery operations. Through FAME, we are considering the idea that this data might have additional value. They could potentially be assessed, priced, and even traded, similar to other valuable commodities.
MOH in collaboration with other organizations, is employing a set of advanced tools and components managed within the comprehensive platform of the FAME Marketplace. This platform serves as a specialized toolkit designed to analyze and interpret data in innovative ways and provides a central location where MOH can offer its data. This platform is crucial because it provides the infrastructure for assessing the value of the data and facilitating any potential “trading” that might occur.
Quality Assessment: Looking Closely at the Data
A key tool developed in MOH showcasing FAME marketplace innovative achievements is the Data Quality Assessment component. Before any data can be priced or traded, it’s essential to understand its quality: through this tool, the FAME participants can examine offered data assets.
When examining the data, several key aspects are considered: the volume of the data, as larger datasets can hold more value depending on the context; the completeness of the data, ensuring it is whole and without significant gaps. Additionally, the locality and context involve understanding where the data originated and its relevance to the subject at hand. Other relevant attributes include the data’s timeliness, accuracy, and consistency in collection.
This thorough quality analysis is like a detailed inspection, ensuring that everyone understands the strengths and limitations of the data being considered.
Author(s): Aristotelis Ntafalias (Motor Oil Hellas)
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