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Communication Dans Un Congrès Année : 2023

Data Quality Computation For Obsolescence Detection Within Connected Environments

Résumé

The unceasing growth in digital technologies has promoted the means of sensing, visualizing, and autonomously analyzing the environment encompassing us. These connected environments provide data interoperability producing and collecting a staggered quantity of information deemed forefront in better understanding the challenges our societies face. This has helped in enhancing the performance of new or existing entities with product life-cycle and smart cities being just two examples. However, making use of data is one perspective, and being able to detect which data is actually useful is a different perspective. The latter encounters a critical research gap as there is no clear procedure for identifying obsolete data. Therefore, this paper aims to clearly identify data quality metrics purposed for data obsolescence detection within a connected environment.
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Dates et versions

hal-04259753 , version 1 (26-10-2023)

Identifiants

  • HAL Id : hal-04259753 , version 1

Citer

Jean Raphael Richa. Data Quality Computation For Obsolescence Detection Within Connected Environments. 2023 International Conference on INnovations in Intelligent SysTems and Applications (INISTA), Sep 2023, Hammamet (Tunisie), Tunisia. ⟨hal-04259753⟩

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